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] | open | false | null | [] | null | 0 | 2023-02-15T15:48:04 | 2023-02-15T15:48:04 | null | NONE | null | ### Problem
Streamlit requires Protobuf version < 4. Many modern libraries need > 4. This results in collision when managing project dependencies.
### Solution
Move to newer Protobuf.
Would be great to know if this can be done!
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] | open | false | null | [] | null | 0 | 2023-02-15T14:02:42 | 2023-02-15T14:04:20 | null | COLLABORATOR | null | ## π Context
Improve data editor and dataframe docstring for `width` and `height`.
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 0 | 2023-02-15T13:28:58 | 2023-02-15T13:28:58 | null | NONE | null | ### Problem
A user interacting with a slider might be interested in the distribution of the values in order to more appropriately filter relevant data. As far as I am aware, this is not yet possible.
### Solution
**MVP:** Use a histogram to show the distribution of each step/bin.
**Possible additions:** Move the range bar sideways, coloring steps/bins inside of the range.
### Additional context
For inspiration, it could look something like the [vue-histogram-slider](https://github.com/oguzhaninan/vue-histogram-slider):
<p align="center">
<img src="https://github.com/oguzhaninan/vue-histogram-slider/raw/master/resources/histogram-slider-demo.gif">
</p>
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] | open | false | null | [] | null | 0 | 2023-02-15T09:53:20 | 2023-02-15T09:53:20 | null | NONE | null | ### Problem
Quite often one would like to have multiple elements such as `st.button` next to each other. There is currently no ideal solution to do this.
Columns are an acceptable workaround, but elements such as `st.button` or `st.metric` do not fill the entire column (correctly), leaving large gaps between elements. Tricks like using `st.columns([1,1,10])` to lay out two buttons and a bunch of whitespace can be unpredictable.
### Solution
**MVP:** A container-type command, like `st.horizontal_array` or some such, which would allow for sequential horizontal layout of fixed-width elements such as `st.button`, `st.metric` side-by-side.
**Possible additions:** A consideration of tweaking the gap (like with `st.column`) and what happens in cases of overflow (multi-line sequence?).
### Additional context
Not an unpopular request on the forums:
https://discuss.streamlit.io/t/st-button-in-one-line/25966
https://discuss.streamlit.io/t/two-buttons-on-the-same-line/2749
https://discuss.streamlit.io/t/multiple-download-buttons-on-the-same-line/37706
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] | open | false | null | [] | null | 0 | 2023-02-15T03:45:08 | 2023-02-15T03:45:58 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Verified that "st.cache" is deprecated. No similar examples of document references were found.
### Reproducible Code Example
```Python
@st.cache(allow_output_mutation=True)
def cached_model():
model = SentenceTransformer('jhgan/ko-sroberta-multitask')
return model
@st.cache(allow_output_mutation=True)
def get_dataset():
df = pd.read_csv('wellness_dataset.csv')
df['embedding'] = df['embedding'].apply(json.loads)
return df
```
### Steps To Reproduce
1. @st.cache_resource(allow_output_mutation=True)
def cached_model():
model = SentenceTransformer('jhgan/ko-sroberta-multitask')
return model
@st.cache_resource(allow_output_mutation=True)
def get_dataset():
df = pd.read_csv('wellness_dataset.csv')
df['embedding'] = df['embedding'].apply(json.loads)
return df
### Expected Behavior
Page not found.
### Current Behavior
Please check the official document of st.cache.
### Is this a regression?
- [x] Yes, this used to work in a previous version.
### Debug info
<font class="papago-parent"><font class="papago-source" style="display:none;">- Streamlit version:</font>- μ€νΈλ¦ΌλΌμ΄νΈ λ²μ :</font><font class="papago-parent"><font class="papago-source" style="display:none;">
</font>
</font><font class="papago-parent"><font class="papago-source" style="display:none;">- Python version:</font>- Python λ²μ :</font><font class="papago-parent"><font class="papago-source" style="display:none;">
</font>
</font><font class="papago-parent"><font class="papago-source" style="display:none;">- Operating System:</font>- μ΄μ체μ :</font><font class="papago-parent"><font class="papago-source" style="display:none;">
</font>
</font><font class="papago-parent"><font class="papago-source" style="display:none;">- Browser:</font>- λΈλΌμ°μ :</font><font class="papago-parent"><font class="papago-source" style="display:none;">
</font>
</font><font class="papago-parent"><font class="papago-source" style="display:none;">- Virtual environment:</font>- κ°μ νκ²½:</font><font class="papago-parent"><font class="papago-source" style="display:none;">
</font>
</font>
### Additional Information
_No response_
### Are you willing to submit a PR?
- [X] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 0 | 2023-02-15T00:08:15 | 2023-02-15T12:48:24 | null | NONE | null | ### Problem
Streamlit not copying column headers when selecting and copying data is a borderline no-go for using the tool as our datasets are quite wide in some cases and without headers the overhead is very painful to get useful data into excel/JMP/jupyter. We don't use this often as streamlit is mostly a dashboard-y tool, easily cutting data is a huge bonus. Having the default include headers or optionally being able to configure headers on copy would be very positive.
### Solution
Minium Suggestion:
```python
st.dataframe(df) # default copy behavior is copying data and columns
```
**Possible additions:**
Ideally we could choose (though 90% of the time we want both)
``` python
#default config works like it does now not copying column headers but copying data
def dataframe(df,copy_headers=False,copy_data=True):
```
This allows us to write code like this:
``` python
st.dataframe(df) # Backwards compatible default state
st.dataframe(df,copy_headers=False,copy_data=True) # Explicity config to default state.
st.dataframe(df,copy_headers=True,copy_data=True) # Header
st.dataframe(df,copy_headers=True,copy_data=False) # Columns only ???...
```
Finally another useful...but remotely so, would be
``` python
st.dataframe(df,copy_schema=True) # return data types of each column perhaps int/str/datetime/float
```
I'm currently look at providing buttons with each data frame that use data frame code to save or download data based on solutions I've seen in here and on SO.
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This PR fixes a regression in reported by @snehankekre, where the `help` tooltip in `st.metric` would show up in the wrong place.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Added `display: flex;` to `StyleTruncateText` so we can place the `(?)` icon next to the label;
- Added `overflow: hidden;` to the `StyledStreamlitMarkdown` label container;
- Added `overflow: hidden;` and `text-overflow: ellipsis;` to the actual `<p>` tag inside the label container.
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
![Screenshot 2023-02-14 at 4 46 35 PM](https://user-images.githubusercontent.com/103376966/218846893-766efe61-2ba8-41af-861d-25f6d3067358.png)
![Screenshot 2023-02-14 at 4 46 38 PM](https://user-images.githubusercontent.com/103376966/218846954-05c3cb2c-f722-4118-879e-32754970295b.png)
**Current:**
![218045435-bc389e06-c5ae-4bd9-bd0b-74b1c4860976](https://user-images.githubusercontent.com/103376966/218847035-31609fe7-3923-44bd-b97d-469475e9f964.png)
## π§ͺ Testing Done
- [x] Screenshots included
- [ ] Added/Updated unit tests
- [x] Added/Updated e2e tests
## π References
- **Issue**: Closes #6093
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 0 | 2023-02-14T19:37:29 | 2023-02-15T14:29:22 | null | COLLABORATOR | null | Our `UnserializableReturnValueError` cache error currently refers to our old cache decorator names (`@st.experimental_memo|singleton`), and our old experimental cache decorator docs. This PR updates the error text to refer to the new decorators and the new cache docs. | {
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] | closed | false | null | [] | null | 0 | 2023-02-14T19:32:38 | 2023-02-14T20:52:27 | 2023-02-14T20:52:23 | COLLABORATOR | null | The data editor introduced a new kind of state for an element, being a widget only conditionally. Element replay code relied on the presence of an id field in the protobuf for determining what is a widget, but arrow dfs don't act like a widget, and don't call `register_widget`, unless used with the data editor. In this situation, the id isn't actually set on the protobuf, so we can use it being set for our widget detection.
Fixes #6103
## π Context
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
- **Issue**: #6103
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
I have a program with five tabs. In Chrome, Firefox, and Edge as you move from tab to tab, the lottie animation and eCharts gauge work in the tab you are in, but they both disappear in the previous tabs. However this does not happen in Safari.
### Reproducible Code Example
```Python
import streamlit as st
import requests, json, time
from PIL import Image
from streamlit_lottie import st_lottie
from streamlit_echarts import st_echarts
st.set_page_config(page_title="Test Lottie and Gauge", page_icon=Image.open('images/favicon.ico'), layout="wide")
govt = ['file://images/govt1.json','file://images/govt2.json']
##
def load_lottie_resource(resource: str):
if resource[:4] == 'http':
r = requests.get(resource)
if r.status_code !=200: return None
else: return r.json()
elif resource[:4] == 'file':
with open(resource[7:], 'r') as f:
return json.load(f)
##
def gov_total(df):
st.info('Testing')
st_lottie(govt_animation[1],key=time.time(),height=120,width=120,speed=0.7)
option = {
"tooltip": {"formatter": '{a} <br/>{b} : {c}%'},
"series": [{
"name": 'Test',
"type": 'gauge',
"radius": '90%',
"data": [{
"value": df,
"name": 'test'
}],
"progress": {
"show": "true"
},
"pointer": {
"length": '50%',
"valueAnimation": "true",
"width": 5,
"offsetCenter": [0, '3%']
},
"detail": {
"valueAnimation": "true",
"formatter": '{value}%',
"offsetCenter": [0, '70%'],
},
}]
}
st_echarts(options=option, renderer="svg", key=time.time())
return
##MAIN
govt_animation = list(map(load_lottie_resource,govt))
## -- navigation setup
tab1, tab2, tab3, tab4, tab5 = st.tabs(['Tab1',':hospital: Tab2',':hospital: Tab3',':globe_with_meridians: Tab4',':round_pushpin: Tab5'])
with tab1:
st.write('tab1')
gov_total(51)
with tab2:
st.write('tab2')
gov_total(52)
with tab3:
st.write('tab3')
gov_total(53)
with tab4:
st.write('tab4')
gov_total(54)
with tab5:
st.write('tab5')
gov_total(55)
```
### Steps To Reproduce
Click thru the tabs and return to a previous tab and the lottie animation and eCharts gauge will disappear
### Expected Behavior
the lottie animation and eChart gauge should remain as it does in the Safari broswer
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:1.170, 1.18.0, 1.18.1
- Python version:10.8
- Operating System:Ubuntu 22, Mac OS 13.1
- Browser: Chrome, Firefox, Edge (all latest)
- Virtual environment: Conda
### Additional Information
Any pointers would be greatly appreciated
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 5 | 2023-02-14T16:41:01 | 2023-02-14T18:34:04 | 2023-02-14T17:21:24 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
I have a Steamlit app that when I change tabs and use a selectbox to make a selection and the page(s) re-render, the st_lottie animation and echart gauge disappear on previous tabs.
I have tested this on Streamlit version 1.17.0 and 1.18.0 and I get the same results. Lottie version 0.0.3, echarts version 0.4.0. This happens consistently in Chrome but works correctly in Safari.
What is even more strange is that it works perfectly on Safari on Streamlit 1.17.0, however if I upgrade to Streamlit 1.18.0 I get a blank page in Safari.
### Reproducible Code Example
```Python
def draw_lottie_and_gauge(df):
st.info('Government program coverage')
st_lottie(govt_animation[1],key=time.time(),height=120,width=300,speed=0.7)
option = {
"tooltip": {"formatter": '{a} <br/>{b} : {c}%'},
"series": [{
"name": 'Government Programs',
"type": 'gauge',
"radius": '90%',
"data": [{
"value": round(df.loc[(df['Payor'] == 'Total Government')]['Percent'].sum() * 100),
"name": 'government'
}],
"progress": {
"show": "true"
},
"pointer": {
"length": '50%',
"valueAnimation": "true",
"width": 5,
"offsetCenter": [0, '3%']
},
"detail": {
"valueAnimation": "true",
"formatter": '{value}%',
"offsetCenter": [0, '70%'],
},
}]
}
st_echarts(options=option, renderer="svg", key=time.time())
return
```
### Steps To Reproduce
Click on a tab
select a criteria from the selectbox.
dashboard information generates, including the Lottie animation and echart gauge
go to a previous tab and everything is populated **except** the lottie animation and echarts gauge
### Expected Behavior
The lottie animation and echarts gauge should remain on each tab
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:1.17.0 and 1.18.0
- Python version:3.10.8
- Operating System:Ubuntu 22 and Mac OSx 13.1
- Browser: Chrome
- Virtual environment: Conda
If Streamlit Version 1.17.0 everything works in Safari and does not work in Chrome.
If Streamlit Version 1.18.0 Safari shows a blank page. Page shows up in Chrome but the lottie animation and echarts gauge disappear just like in 1.17.0
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 3 | 2023-02-14T14:56:40 | 2023-02-14T18:47:24 | 2023-02-14T18:47:24 | NONE | null | ### Summary
When configuring a page icon using `set_page_config`, the icon does not show up on tab of the Streamlit page.
### Reproducible Code Example
```Python
import streamlit as st
st.set_page_config(page_title="Test page", page_icon="π", layout="wide")
st.write("The page icon should be π")
```
### Steps To Reproduce
1. Run the Reproducible Code Example
2. Observe the tab icon in a browser
### Expected Behavior
The tab should show the icon given by `page_icon="π"`.
### Current Behavior
The tab shows an empty page as icon.
### Is this a regression?
I don't know, since it never worked since I started using Streamlit.
### Debug info
- Streamlit version: 1.11.0
- Python version: 3.8.10
- Operating System: Windows 10 Enterprise, Version 21H2, OS build 19044.2486
- Browser: Microsoft Edge Version 110.0.1587.41 (64-Bit)
### Additional Information
While diving into this issue, I found that the icon given above resolve to the following line in the HTML of the Streamlit page:
```
<link rel="shortcut icon" href="https://twemoji.maxcdn.com/2/72x72/1f4dd.png">
```
When entering this address directly into the browser, the file cannot be found. This seems to be due to an update within the folder structure of twemoji.
A working link would be
```
https://twemoji.maxcdn.com/2/svg/1f4dd.svg
```
### Are you willing to submit a PR?
- [X] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 0 | 2023-02-14T14:08:21 | 2023-02-14T14:37:49 | 2023-02-14T14:37:48 | COLLABORATOR | null | ## π Context
The CI pipeline is broken because it tries to install a newer version of `unixodbc-dev` (2.3.11). It fails to update the old version that already exists in the container (`2.3.9-5`).
![image](https://user-images.githubusercontent.com/2852129/218763629-37b837ea-9a71-4221-91c4-bea451ac2a07.png)
![image](https://user-images.githubusercontent.com/2852129/218763689-a831e43b-5124-4253-8c9c-538cc50d5111.png)
![image](https://user-images.githubusercontent.com/2852129/218763766-e1a7f351-1d03-4a28-a868-f9bb2f5c0853.png)
![image](https://user-images.githubusercontent.com/2852129/218763736-35f730f2-c322-406d-b411-aa3151c47192.png)
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- As a quick fix, we pin the `unixodbc-dev` dependency to the old version.
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 0 | 2023-02-14T13:37:07 | 2023-02-14T17:38:52 | 2023-02-14T17:38:52 | COLLABORATOR | null | ## π Context
The current implementation does not allow the deprecated numeric index types in Pandas: `Int64Index`, `Float64Index` and `UInt64Index`. Even so, they are deprecated, there isn't any specific reason why we should not support them when used with older Pandas versions.
- What kind of change does this PR introduce?
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Allow numeric indices as well. We need to check based on the string type name, since they are planned to be removed from pandas in future versions. This would potentially break if we do an instance check.
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 2 | 2023-02-14T13:19:21 | 2023-02-14T18:16:25 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
One particular Polygon is not showing any color but when you hover over it, it's showing the value with the particular ICS Code it refers to. All the other polygon values are showing color and are being plotted without any problem. I want to fix this issue so that all polygons show color in the map.
### Reproducible Code Example
```Python
import streamlit as st
import json
import geopandas as gpd
import pyproj
import plotly.graph_objs as go
# FLU Full Shape File Read
# reading in the points shapefile
FLU_Full_map_df = gpd.read_file(data_dir_shape + f'FLU_Full.shp') # project GeoPandas dataframe
# set GeoJSON file path
FLU_Full_map_df.to_file(data_dir_shape + f'geojson_FLU_Full.json', driver = "GeoJSON")
with open(data_dir_shape + f'geojson_FLU_Full.json') as geofile1:
j_file_FLU_Full = json.load(geofile1) # index geojson
i = 0
for feature in j_file_FLU_Full["features"]:
feature['id'] = str(i).zfill(1)
i += 1
# FLU Short Shape File Read
# reading in the points shapefile
FLU_Short_map_df = gpd.read_file(data_dir_shape + f'FLU_Short.shp') # project GeoPandas dataframe
# set GeoJSON file path
FLU_Short_map_df.to_file(data_dir_shape + f'geojson_FLU_Short.json', driver = "GeoJSON")
with open(data_dir_shape + f'geojson_FLU_Short.json') as geofile1:
j_file_FLU_Short = json.load(geofile1) # index geojson
i = 0
for feature in j_file_FLU_Short["features"]:
feature['id'] = str(i).zfill(1)
i += 1
# Typhoid Full Shape File Read
# reading in the points shapefile
Typhoid_Full_map_df = gpd.read_file(data_dir_shape + f'Typhoid_Full.shp') # project GeoPandas dataframe
# set GeoJSON file path
Typhoid_Full_map_df.to_file(data_dir_shape + f'geojson_Typhoid_Full.json', driver = "GeoJSON")
with open(data_dir_shape + f'geojson_Typhoid_Full.json') as geofile1:
j_file_Typhoid_Full = json.load(geofile1) # index geojson
i = 0
for feature in j_file_Typhoid_Full["features"]:
feature['id'] = str(i).zfill(1)
i += 1
# Hepatitis A Full Shape File Read
# reading in the points shapefile
Hepatitis_A_Full_map_df = gpd.read_file(data_dir_shape + f'Hepatitis_A_Full.shp') # project GeoPandas dataframe
# set GeoJSON file path
Hepatitis_A_Full_map_df.to_file(data_dir_shape + f'geojson_Hepatitis_A_Full.json', driver = "GeoJSON")
with open(data_dir_shape + f'geojson_Hepatitis_A_Full.json') as geofile1:
j_file_Hepatitis_A_Full = json.load(geofile1) # index geojson
i = 0
for feature in j_file_Hepatitis_A_Full["features"]:
feature['id'] = str(i).zfill(1)
i += 1
# Hepatitis A Full Shape File Read
# reading in the points shapefile
Yellow_fever_Full_map_df = gpd.read_file(data_dir_shape + f'Yellow_fever_Full.shp') # project GeoPandas dataframe
# set GeoJSON file path
Yellow_fever_Full_map_df.to_file(data_dir_shape + f'geojson_Yellow_fever_Full.json', driver = "GeoJSON")
with open(data_dir_shape + f'geojson_Yellow_fever_Full.json') as geofile1:
j_file_Yellow_fever_Full = json.load(geofile1) # index geojson
i = 0
for feature in j_file_Yellow_fever_Full["features"]:
feature['id'] = str(i).zfill(2)
i += 1
print(FLU_Short_map_df['NIC_Per_Pe'])
# mapbox token
mapboxtoken = 'MAPBOXTOKEN'
# define layers and plot map
FLU_Full = go.Choroplethmapbox(z = FLU_Full_map_df['NIC_Per_Pe'], locations = [x['id'] for x in j_file_FLU_Full['features']], colorscale='Cividis', geojson=j_file_FLU_Full, text = FLU_Full_map_df['ICS_CODE'])
# define layers and plot map
FLU_Short = go.Choroplethmapbox(z = FLU_Short_map_df['NIC_Per_Pe'], locations = [x['id'] for x in j_file_FLU_Short['features']], colorscale='Cividis', geojson=j_file_FLU_Short, text = FLU_Short_map_df['ICS_CODE'])
# define layers and plot map
Typhoid_Full = go.Choroplethmapbox(z = Typhoid_Full_map_df['NIC_Per_Pe'], locations = [x['id'] for x in j_file_Typhoid_Full['features']], colorscale='Cividis', geojson=j_file_Typhoid_Full, text = Typhoid_Full_map_df['ICS_CODE'])
# define layers and plot map
Hepatitis_A_Full = go.Choroplethmapbox(z = Hepatitis_A_Full_map_df['NIC_Per_Pe'], locations = [x['id'] for x in j_file_Hepatitis_A_Full['features']], colorscale='Cividis', geojson=j_file_Hepatitis_A_Full, text = Hepatitis_A_Full_map_df['ICS_CODE'])
# define layers and plot map
Yellow_fever_Full = go.Choroplethmapbox(z = Yellow_fever_Full_map_df['NIC_Per_Pe'], locations = [x['id'] for x in j_file_Yellow_fever_Full['features']], colorscale='Cividis', geojson=j_file_Yellow_fever_Full, text = Yellow_fever_Full_map_df['ICS_CODE'])
layout = go.Layout(title_text = 'Map of Total NIC Per Person', width = 800, height = 700, mapbox = dict(center = dict(lat=54.5, lon=-3), accesstoken=mapboxtoken, style="light", zoom=4.5))
activity = ['FLU_Full', 'FLU_Short', 'Typhoid_Full', 'Hepatitis_A_Full', 'Yellow_fever_Full']
choice = st.sidebar.selectbox('Drug Selection: ', activity)
if choice == 'FLU_Full':
fig = go.Figure(data=FLU_Full, layout=layout) # display streamlit map
elif choice == 'FLU_Short':
fig = go.Figure(data=FLU_Short, layout=layout)
elif choice == 'Typhoid_Full':
fig = go.Figure(data=Typhoid_Full, layout=layout)
elif choice == 'Hepatitis_A_Full':
fig = go.Figure(data=Hepatitis_A_Full, layout=layout)
else:
fig = go.Figure(data=Yellow_fever_Full, layout=layout)
st.title('NIC Per Person: ')
st.plotly_chart(fig)
```
### Steps To Reproduce
If you run this code after generating a mapboxtoken and run it with streamlit, it's showing something like this:
<img width="1399" alt="Screenshot 2023-02-14 at 13 17 14" src="https://user-images.githubusercontent.com/84929423/218750000-7e574c31-99f2-4f7e-94d9-bc0889f5f9f9.png">
### Expected Behavior
<img width="1399" alt="Screenshot 2023-02-14 at 13 17 47" src="https://user-images.githubusercontent.com/84929423/218750110-2ed8bbc3-804a-4e1f-96c5-bd97cc859647.png">
If you see, I want that white spot where Lincolnshire is to be filled with color. All the other counties in UK are being filled with color.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 1 | 2023-02-14T09:41:03 | 2023-02-14T17:22:25 | 2023-02-14T17:22:25 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
I am trying to reboot my streamlit app
https://mehulgupta2016154-resume-builder-streamlit-app-ajmqjx.streamlit.app/
but when trying the reboot button, it says I have view-only access and cant reboot. Please help
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 4 | 2023-02-14T09:23:31 | 2023-02-14T20:53:16 | 2023-02-14T18:49:44 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
I have an `if` statement that depends on the state of a button. When there is no slider inside the `if` statement, everything works fine.
```
import streamlit as st
if st.button("Validate"):
st.write("Hello")
else:
st.write("Bye")
```
When I add a slider within the if-statement, once I use the slider, the code in the else part is executed.
```
import streamlit as st
if st.button("Validate"):
st.write("Hello")
st.slider("Slider example", min_value=0, max_value=10)
else:
st.write("Bye")
```
I don't know why the slider impacts the state of the button (as the `else` statement is executed)
### Reproducible Code Example
```Python
import streamlit as st
if st.button("Validate"):
st.write("Hello")
st.slider("Slider example", min_value=0, max_value=10)
else:
st.write("Bye")
```
### Steps To Reproduce
_No response_
### Expected Behavior
The code within the `else` statement shouldn't be executed when one uses the slider that is within the `if`.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18.1
- Python version: 3.7.13
- Operating System: Mac OS Ventura 13.2
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 1 | 2023-02-14T07:34:13 | 2023-02-14T18:51:39 | 2023-02-14T18:51:38 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
![image](https://user-images.githubusercontent.com/81905209/218669367-760950b5-823b-44d4-b5c4-db320f9a7189.png)
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 2 | 2023-02-14T04:59:53 | 2023-02-14T21:44:33 | null | CONTRIBUTOR | null | ### Problem
When using Poetry with a project that does not contain a main package, Streamlit Cloud fails to install the dependencies.
An example project structure that fails is below.
```
some-project
βββ LICENSE
βββ README.md
βββ app.py
βββ poetry.lock
βββ pyproject.toml
```
It is because `poetry install` emits the following error.
```shell
$ poetry install
(...)
Installing dependencies from lock file
(...)
/path/to/some-project/some_project does not contain any element
```
The command `poetry install` expects this project contains a package root like `some-project/some_project/__init__.py` and tries to install the package itself in addition to its dependencies, while it actually doesn't exist.
### Solution
`poetry install` provide an option to deal with this case, `--no-root`.
(See https://python-poetry.org/docs/cli/#install)
I think Streamlit Cloud should run `poetry install` with the `--no-root` option because usually we don't need to deal with the Streamlit app projects as packages to install, but we just want to install the dependencies managed with Poetry.
### Additional context
[This repo](https://github.com/whitphx/streamlit-webrtc-hugging-face-transformer-example) is an actual project with which I encountered this problem.
[This revision](https://github.com/whitphx/streamlit-webrtc-hugging-face-transformer-example/tree/a6b77c2aacd182c7bb8409b725021aca1c6f7b6e) of the repo caused this error, and I fixed it by adding `streamlit_webrtc_hugging_face_transformer_example/__init__.py` as a workaround in [this commit](https://github.com/whitphx/streamlit-webrtc-hugging-face-transformer-example/commit/237026ca4b19dcb6e9b94240cfe1adb0657946fe) so that it works on Streamlit Cloud now.
---
The same error was reported at [this thread in the forum](https://discuss.streamlit.io/t/streamlit-cloud-deploy-is-failing-with-error-does-not-contain-any-element/31541)
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | closed | false | null | [] | null | 1 | 2023-02-14T03:07:38 | 2023-02-14T13:43:33 | 2023-02-14T13:43:33 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
When running a steamlit server, the icon cannot fetch (404).
![image](https://user-images.githubusercontent.com/13399458/218627230-08d8d9f2-c03e-4ee3-a0ed-dd9b55006f98.png)
### Reproducible Code Example
```Python
import streamlit as st
if __name__ == "__main__":
st.set_page_config(
page_title="wocao",
page_icon="random",
layout="wide",
initial_sidebar_state="expanded",
)
x = st.slider("Select a value")
st.write(x, "squared is", x * x)
```
### Steps To Reproduce
streamlit run demo.py
### Expected Behavior
Show the icon I selected or random
### Current Behavior
Cannot show the icon but a blank icon
![image](https://user-images.githubusercontent.com/13399458/218628525-69080bb0-e8fc-4c53-b999-4374a4bfdcc1.png)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0
- Python version: 3.7.12
- Operating System: Ubuntu 20
- Browser: Edge
- Virtual environment: Conda
### Additional Information
_No response_
### Are you willing to submit a PR?
- [X] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 1 | 2023-02-14T01:40:34 | 2023-02-14T17:23:23 | 2023-02-14T17:23:22 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Dear Streamlit
I have 'stream_app.py' on GitHub.com
https://github.com/JohnTan38/Telco-Customer-Churn-Prediction/blob/main/stream_app.py
This file 'model_C_1.bin' is on GutHub.com too
https://github.com/JohnTan38/Telco-Customer-Churn-Prediction/blob/main/model_C_1.bin
Code snippet:
model_file = (r"https://raw.githubusercontent.com/JohnTan38/Telco-Customer-Churn-Prediction/blob/main/model_C_1.bin")
with open(model_file, 'rb') as f_in:
dv, model = pickle.load(f_in)
Here's the error message when I tried to deploy s'tream_app.py'
--------------------------------------------------------------------------------------------------------------------------------------------
File "/home/appuser/venv/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/app/telco-customer-churn-prediction/stream_app.py", line 7, in <module>
with open(model_file, 'rb') as f_in:
--------------------------------------------------------------------------------------------------------------------------------------------
### Reproducible Code Example
```Python
model_file = (r"https://raw.githubusercontent.com/JohnTan38/Telco-Customer-Churn-Prediction/blob/main/model_C_1.bin")
with open(model_file, 'rb') as f_in:
dv, model = pickle.load(f_in)
```
### Steps To Reproduce
_No response_
### Expected Behavior
A page opens for user input
Contact email
[email protected]
[email protected]
### Current Behavior
_No response_
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
----------------------
Python 3.9
Windows 10
Chrome Browser
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 0 | 2023-02-14T01:30:46 | 2023-02-14T19:40:52 | 2023-02-14T19:40:48 | COLLABORATOR | null | We have a regression in caching - starting in 1.18, using `@st.cache_data` (or `@st.cache_resource`) on a class member function will fail with an error when the cached function was called:
```python
class TestClass:
@cache_decorator
def foo(_self):
# We underscore-prefix `_self`, because our class is not hashable.
return "it works!"
obj = TestClass()
result = obj.foo() # Explode!
```
This is the result of a refactor that moved "cached function wrapper" logic into a class, `CachedFunc`, (from a closure). `functools.update_wrapper` (and `functools.wraps`) has unexpected behavior when applied to a class member function: the wrapped function no longer passes the "self" argument through to the underlying member function.
I don't know why this is! I couldn't find anything in the `functools` docs (or in a quick Google search) to explain the behavior. My guess is that using `update_wrapper` on a class instance ends up overwriting one or more instance properties that break its member function call semantics.
But the fix is simple: we hoist the `functools.wraps` call outside of `CachedFunc`, rather than using `functools` to modify the `CachedFunc` member function itself.
Fixes https://github.com/streamlit/streamlit/issues/6109 | {
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] | closed | false | null | [] | null | 0 | 2023-02-13T22:55:51 | 2023-02-14T11:16:29 | 2023-02-14T11:16:28 | COLLABORATOR | null | ## π Context
We currently print out the full stack trace as an info log when the Arrow serialization fails. This was added #6022 as debugging help during development but isn't that useful for the users. This PR removes the stack trace and only shows the Arrow exception message.
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [x] Refactoring
- [ ] Other, please describe:
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 2 | 2023-02-13T20:00:58 | 2023-02-13T20:57:15 | 2023-02-13T20:57:14 | NONE | null | widget st.date_input don't have option to view Monday as first day of week. | {
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] | closed | false | null | [] | null | 0 | 2023-02-13T17:55:16 | 2023-02-14T15:09:01 | 2023-02-14T15:09:00 | COLLABORATOR | null | ## π Context
In the current version, as soon as the `data_editor` widget is removed it will lose all state (e.g. edits). This also happens when another element is added above the `data_editor`. Other widgets handle this situation by initializing some of the state from the widget state. We need to do the same with the data editor.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Split up the `useDataLoader` into two hooks: One hook for loading the columns and one for handling the cell data.
- Save widget state whenever the value changes (and not just on trigger reload)
- Initialize from the widget state JSON if the widget state already exist in the widget state manager.
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 2 | 2023-02-13T10:30:59 | 2023-02-14T19:40:49 | 2023-02-14T19:40:49 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Previously using experimental_memo the following worked fine. After deprecation and changing to cache_data, the methos isn't called with underscored parameters anymore.
Interestingly, using experimental_memo ALSO fails now.
### Reproducible Code Example
```Python
import streamlit as st
class MyView:
def __init__(self, txt):
self.txt = txt
self.view()
def view(self):
st.write(self.txt)
st.write(self.load_data())
@st.cache_data(ttl=60)
def load_data(_self):
return _self.txt
MyView("OH YES")
```
### Steps To Reproduce
streamlit run code.py
### Expected Behavior
Working
### Current Behavior
TypeError: load_data() missing 1 required positional argument: '_self'
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18.1 (working with 1.14.0)
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 2 | 2023-02-13T09:54:54 | 2023-02-14T22:22:42 | null | NONE | null | The `st.cache` is really useful (I'm still on 1.13) but I think its user-friendliness can be improved. Now, the first run still takes a long time for the first user. But it would be useful if we can "pre-cache" the result of a function so that even the first user does not have to wait too long for long running processes, e.g. for downloading a ML model behind the scenes. A solution would be to add an option to st.cache like "precache" that accepts a list of dicts, where each dict is a kwarg for the function. On app start up, the function is then run for all those different types of kwargs.
It's just an idea but I think it could be useful! | {
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https://api.github.com/repos/streamlit/streamlit/issues/6107 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6107/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6107/comments | https://api.github.com/repos/streamlit/streamlit/issues/6107/events | https://github.com/streamlit/streamlit/issues/6107 | 1,581,704,405 | I_kwDODCoeTs5eRuTV | 6,107 | date_input on sidebar has a display issue | {
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] | open | false | null | [] | null | 1 | 2023-02-13T05:48:23 | 2023-02-13T18:35:44 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
The `st.sidebar.date_input()` has a display issue when the sidebar is too thin. It cuts the left part of the calendar widget.
### Reproducible Code Example
```Python
import streamlit as st
st.sidebar.date_input('Foo')
```
### Steps To Reproduce
1. Create the date_input on the sidebar;
2. With the cursor, set the sidebar to a thinner width;
3. Click on the date_input and see the calendar's left side cut off
### Expected Behavior
I expect the calendar to adjust its position when the sidebar width is thinner than the calendar width.
### Current Behavior
It cuts the left part of the calendar widget.
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: Streamlit, version 1.17.0
- Python version: Python 3.10.6
- Operating System: Linux Pop Os
- Browser: Firefox & Chrome
- Virtual environment: Standard Python Env
### Additional Information
I've checked that on both my monitors (19 & 24 inch) and both Firefox and Chrome browsers. Here are the images showing the display issue:
![Screenshot from 2023-02-13 02-27-20](https://user-images.githubusercontent.com/95307858/218380180-46be77b0-a477-46a9-bd80-f0a2efd2acc9.png) ![Screenshot from 2023-02-13 02-27-31](https://user-images.githubusercontent.com/95307858/218380182-e3b9535e-d014-457f-b91f-f7df81017cd2.png)
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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### Problem
When using file_uploader with accept_multiple_files=True, a list of uploaded files is being displayed. However, when PDF preview is added using displayPDF, the previews are displayed below this list while missing the relation of each preview to its file.
### Solution
Add the preview under each file in the file list
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https://api.github.com/repos/streamlit/streamlit/issues/6105 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6105/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6105/comments | https://api.github.com/repos/streamlit/streamlit/issues/6105/events | https://github.com/streamlit/streamlit/issues/6105 | 1,581,231,645 | I_kwDODCoeTs5eP64d | 6,105 | Update images in table to st.cache_data instead of st.experimental_memo | {
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] | open | false | null | [] | null | 1 | 2023-02-12T12:01:06 | 2023-02-12T14:23:39 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
When I use images in table extra, I get this error message
'st.experimental_memo is deprecated. Please use the new command st.cache_data instead, which has the same behavior. More information [in our docs](https://docs.streamlit.io/library/advanced-features/caching).'
just need to update the source code with st.cache_data
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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https://api.github.com/repos/streamlit/streamlit/issues/6104 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6104/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6104/comments | https://api.github.com/repos/streamlit/streamlit/issues/6104/events | https://github.com/streamlit/streamlit/issues/6104 | 1,580,873,788 | I_kwDODCoeTs5eOjg8 | 6,104 | Audio widget not working on iOS Chrome/Safari and Safari | {
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] | closed | false | null | [] | null | 2 | 2023-02-11T14:53:50 | 2023-02-13T08:43:06 | 2023-02-13T08:43:05 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
It seems that st.audio() stopped working on iOS and Safari. Similar [issue](https://github.com/streamlit/streamlit/issues/2113) was already resolved in 2020 soβ¦potential regression?
![image](https://user-images.githubusercontent.com/115263325/218264501-a8e1340d-ea24-4fe3-ba73-d7c57424695b.png)
issue was confirmed by other streamlit users: https://discuss.streamlit.io/t/st-audio-stopped-working-on-ios-safari-again/37049
### Reproducible Code Example
_No response_
### Steps To Reproduce
1. Go to https://adventure.streamlit.app/
2. Enter your name
3. Check if audio is working (it is on windows and android :) )
4. Github repo: https://github.com/tomjohnh/streamlit-game/blob/main/streamlit_app.py
### Expected Behavior
Audio widget is working
### Current Behavior
Audio widget is not working ("Error" message)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17
- Python version:
- Operating System: iOS
- Browser: Chrome on iOS / Safari
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 5 | 2023-02-11T13:31:17 | 2023-02-14T20:52:26 | 2023-02-14T20:52:26 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
AttributeError
Traceback:
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "C:\Users\A260219\Jupyter\bloomberg\prova.py", line 2126, in <module>
ottimizzazione(num_variabili, fun_varianza, ptf_weights_equally, expected_returns, lista_asset_pairplot)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 186, in __call__
return self._get_or_create_cached_value(args, kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 211, in _get_or_create_cached_value
return self._handle_cache_miss(cache, value_key, func_args, func_kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 265, in _handle_cache_miss
computed_value = self._info.func(*func_args, **func_kwargs)
File "C:\Users\A260219\Jupyter\bloomberg\prova.py", line 1555, in ottimizzazione
st.write(pd.DataFrame(data=np.round(ptf_weights.reshape([1, num_variabili])*100, decimals=1), columns=dati_ritorni.columns, index=["Pesi"]))
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\write.py", line 200, in write
self.dg.dataframe(arg)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\dataframe_selector.py", line 116, in dataframe
return self.dg._arrow_dataframe(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\arrow.py", line 117, in _arrow_dataframe
return self.dg._enqueue("arrow_data_frame", proto)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\delta_generator.py", line 563, in _enqueue
caching.save_element_message(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\__init__.py", line 50, in save_element_message
CACHE_RESOURCE_MESSAGE_REPLAY_CTX.save_element_message(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cached_message_replay.py", line 293, in save_element_message
raise AttributeError
### Reproducible Code Example
```Python
@st.cache_resource ##al momento non funzionante con la funzione di cui di seguito e la versione 1.18 di Streamlit (ma st.experimental_singleton funzionava nella 1.17)
def ottimizzazione(num_variabili: int, _fun_varianza: Callable[[np.array], float], ptf_weights_equally: np.array, expected_returns: np.array, lista_asset_pairplot: list) -> None:
#l'underscore serviva per dire a streamlit di non fare l'hash della funzione
fun_varianza=_fun_varianza
#qui si specificano i vincoli (min, max) per le singole variabili (NB: il numero di vincoli deve essere esattamente uguale al numero di variabili)
bnds = tuple([(valore_minimo_per_singola_asset_class, valore_massimo_per_singola_asset_class) for i in range(num_variabili)])
st.write("--------------------------------------------------------------------")
st.write("Elaborazione portafoglio di minima varianza")
#di seguito la chiamata all'ottimizzatore con argomenti: la funzione-oggetto da minimizzare, X0 ovvero un initial guess delle variabili, il metodo scelto ('SLSQP' Γ©
#l'unico metodo che supporta ogni tipo di vincolo), i bounds sui valori delle singole variabili, i vincoli su piΓΊ variabili simultaneamente, infine le opzioni
opt={'maxiter': maxiter, 'disp': True, 'ftol': 1e-12, 'eps': 1.4901161193847656e-08} #valori di default 'eps': 1.4901161193847656e-08, 'ftol': 1e-06 (si tratta rispettivamente della step size (eps) usata per l'approssimazione numerica della jacobiana ovvero il vettore del gradiente, e dell'obbiettivo di precisione (ftol) sulla funzione obbiettivo)
res = minimize(fun_varianza, x0=ptf_weights_equally, method='SLSQP', bounds=bnds, constraints=st.session_state.vincoli_generali, options=opt)
ptf_weights=res.x #attribuisce al vettore pesi i pesi ottimali calcolati da minimize (relativi al portafoglio di minima varianza)
st.write("Di seguito i pesi degli asset in portafoglio espressi in percentuale:")
st.write(pd.DataFrame(data=np.round(ptf_weights.reshape([1, num_variabili])*100, decimals=1), columns=dati_ritorni.columns, index=["Pesi"]))
ptf_min_var_return=(ptf_weights.T).dot(expected_returns) #calcola il rendimento del portafoglio ottimale di minima varianza
ptf_min_var_variance=res.fun #attribuisce ad apposita variabile il valore finale minimizzato della funzione obbiettivo (ovvero la varianza dei rendimenti di portafoglio)
st.write("La deviazione standard annualizzata percentuale del portafoglio Γ© %0.03f" % (np.sqrt(ptf_min_var_variance)*np.sqrt(periodicity)*100))
st.write("Il rendimento percentuale del portafoglio Γ© %0.03f" % (ptf_min_var_return*100))
##di seguito si calcola il portafoglio di massimo rendimento (da fare per il caso in cui vi siano vincoli complessi)
#qui si specifica la funzione da minimizzare per il portafoglio di massimo rendimento
def fun_rendimento(ptf_weights: np.array) -> float:
return -(ptf_weights.T).dot(expected_returns) #si minimizza l'opposto del rendimento per massimizzarlo
st.write("--------------------------------------------------------------------")
st.write("Elaborazione portafoglio di massimo rendimento")
#di seguito la massimizzazione del rendimento (minimizza l'opposto) con vincoli invariati
res_return = minimize(fun_rendimento, x0=ptf_weights_equally, method='SLSQP', bounds=bnds, constraints=st.session_state.vincoli_generali, options=opt)
#estrae il valore finale del rendimento (massimizato); ovviamente va invertito di segno perchΓ© la funzione obbiettivo Γ© l'opposto del rendimento
ptf_max_risk_return=-res_return.fun
st.write("Di seguito i pesi degli asset in portafoglio espressi in percentuale:")
st.write(pd.DataFrame(data=np.round((res_return.x).reshape([1, num_variabili])*100, decimals=1), columns=dati_ritorni.columns, index=["Pesi"]))
st.write("Il rendimento percentuale del portafoglio Γ© %0.03f" % (ptf_max_risk_return*100))
step=(ptf_max_risk_return-ptf_min_var_return)/n_step
#si specifica la matrice dei pesi di portafoglio con shape variabili*portafogli
ptf_weights_matrix=np.zeros([num_variabili, (n_step+1)])
ptf_weights_matrix[:, 0]=ptf_weights #il primo portafoglio Γ© quello di minima varianza di cui giΓ‘ abbiamo calcolato i pesi
#si specifica il vettore delle varianze dei vari portafogli sulla frontiera efficiente
variance_vector=np.zeros([(n_step+1),])
variance_vector[0]=ptf_min_var_variance
#si specifica il vettore dei rendimenti dei vari portafogli sulla frontiera efficiente
returns_vector=np.zeros([(n_step+1),])
returns_vector[0]=ptf_min_var_return
desired_return=ptf_min_var_return+step
#la funzione destinata ad essere usata per il vincolo sul rendimento nella costruzione
#del resto della frontiera
def vincolo_rendimento(ptf_weights: np.array) -> float:
return (ptf_weights.T).dot(expected_returns) - desired_return
for i in range(n_step):
st.write("--------------------------------------------------------------------")
st.write("Elaborazione portafoglio n.ro %s" % (i+1))
#qui si specificano i vincoli (generali, ovvero su piΓΊ variabili) nella forma di un dictionary che contiene la specifica del tipo ('eq' per equality ed
#'ineq' per inequality) e la funzione del vincolo (che verrΓ‘ posta uguale a zero per i vincoli di equality e non-negativa per i vincoli di inequality)
res = minimize(fun_varianza, x0=ptf_weights, method='SLSQP', bounds=bnds,
constraints=[i for i in st.session_state.vincoli_generali] + [{'type': 'eq', 'fun': vincolo_rendimento}], #aggiunge il vincolo sul rendimento desiderato
options=opt)
ptf_weights=res.x
ptf_weights_matrix[:, i+1]=ptf_weights
st.write("Di seguito i pesi degli asset in portafoglio espressi in percentuale:")
st.write(pd.DataFrame(data=np.round(ptf_weights.reshape([1, num_variabili])*100, decimals=1), columns=dati_ritorni.columns, index=["Pesi"]))
variance_vector[i+1]=res.fun
st.write("La deviazione standard annualizzata percentuale del portafoglio Γ© %0.03f" % (np.sqrt(variance_vector[i+1])*np.sqrt(periodicity)*100))
returns_vector[i+1]=(ptf_weights.T).dot(expected_returns)
st.write("Il rendimento percentuale del portafoglio Γ© %0.03f" % (returns_vector[i+1]*100))
desired_return=desired_return+step
st.write("---------------------------------------------------------------------------------------------")
st.write("A seguire un riepilogo della composizione dei portafogli componenti la frontiera di Markowitz:")
sintesi_composizione_portafogli_markowitz=pd.DataFrame(data=np.round(ptf_weights_matrix*100, decimals=2), #i pesi in portafoglio
columns=[("Ptf n.ro "+str(i)) for i in range(n_step+1)],
index=dati_ritorni.columns, dtype="float")
sintesi_composizione_portafogli_markowitz.to_csv("sintesi_composizione_portafogli_markowitz.csv", sep=";", decimal=".")
st.write(sintesi_composizione_portafogli_markowitz)
st.write("Di seguito un riepilogo di rendimenti, rischio ed efficienza dei portafogli componenti la frontiera di Markowitz:")
sintesi_rendimento_rischio_portafogli_markowitz=pd.DataFrame(data=np.round([returns_vector*100, #i rendimenti
np.sqrt(variance_vector)*np.sqrt(periodicity)*100, #le deviazioni standard annualizzate
np.sqrt(variance_vector)*np.sqrt(periodicity)*2.566*100, #il VaR parametrico t-Student 6df con livello di confidenza 99%, orizzonte annuale, espresso in percentuale
np.divide((returns_vector*100-risk_free_rate*100), np.sqrt(variance_vector)*np.sqrt(periodicity)*100)], #gli sharpe ratio
decimals=2),
columns=[("Ptf n.ro "+str(i)) for i in range(n_step+1)],
index=["Rendimenti (%)", "Deviazioni Standard (%)", "VaR 99% t-Student 6df (%)", "Sharpe Ratio"],
dtype="float")
sintesi_rendimento_rischio_portafogli_markowitz.to_csv("sintesi_rendimento_rischio_portafogli_markowitz.csv", sep=";", decimal=".")
st.write(sintesi_rendimento_rischio_portafogli_markowitz)
#concateniamo i dati essenziali della frontiera di Markowitz, inframezzando una riga vuota e le intestazioni di colonna prima della parte rendimento-rischio
empty_row=pd.Series([None for _ in range(len(sintesi_composizione_portafogli_markowitz.columns.values.tolist()))], index=sintesi_composizione_portafogli_markowitz.columns.values.tolist(), name=" ")
sintesi_composizione_portafogli_markowitz_format=sintesi_composizione_portafogli_markowitz.append(empty_row, ignore_index=False)
intestazione_row=pd.Series([f"Ptf n.ro {i}" for i in range(len(sintesi_composizione_portafogli_markowitz.columns.values.tolist()))], index=sintesi_composizione_portafogli_markowitz.columns.values.tolist(), name=" ")
sintesi_composizione_portafogli_markowitz_format=sintesi_composizione_portafogli_markowitz_format.append(intestazione_row, ignore_index=False)
st.session_state.riassuntivo_markowitz=pd.concat([sintesi_composizione_portafogli_markowitz_format, sintesi_rendimento_rischio_portafogli_markowitz], axis=0)
#plotto il grafico con la composizione della frontiera di Markowitz
fig=px.area(sintesi_composizione_portafogli_markowitz.T, \
x=sintesi_composizione_portafogli_markowitz.T.index, \
y=sintesi_composizione_portafogli_markowitz.T.columns, \
labels = dict(index = "N.ro Portafoglio", value = "Percentuale in portafoglio"), \
title="Andamento composizione frontiera di Markowitz")
st.plotly_chart(fig, use_container_width=True)
#calcolo le deviazioni standard annualizzate
std_dev_annualized_vector=np.sqrt(variance_vector)*np.sqrt(periodicity)
#plotto la frontiera di Markowitz
fig=px.line(x=std_dev_annualized_vector*100, \
y=returns_vector*100, \
labels = dict(x = "Deviazione standard annualizzata di portafoglio (%)", y = "Rendimento annuale (%)"), \
title="Frontiera di Markowitz")
st.plotly_chart(fig, use_container_width=True)
st.write("Di seguito la matrice di correlazione:")
#calcolo la matrice di correlazione
df_corr=pd.DataFrame.corr(pd.DataFrame(data=returns, columns=dati_ritorni.columns), method='pearson')
#plotto la heatmap
fig=px.imshow(df_corr)
st.plotly_chart(fig, use_container_width=True)
if plotting_grafico_pairplot=="y":
st.write("Di seguito il grafico pairplot:")
#la riga di codice seguente elimina eventuali indici che fossero superiori al consentito (ad esempio 12 o 8 su un numero di variabili/asset pari a 8)
lista_asset_pairplot=[lista_asset_pairplot[i] for i in range(len(lista_asset_pairplot)) if lista_asset_pairplot[i]<num_variabili]
df_ritorni=pd.DataFrame(data=returns, columns=dati_ritorni.columns)
df_ritorni=df_ritorni.loc[:, [dati_ritorni.columns[i] for i in lista_asset_pairplot]]
##per debug
#st.write(df_ritorni)
#creo uno scatter plot
fig_scatter = px.scatter_matrix(df_ritorni, width=1500, height=1000)
#cambiamo dimensione ed opacitΓ‘ dei punti
fig_scatter.update_traces(marker={"size": 4,"opacity":0.7})
#stampo a schermo lo scatterplot (nota bene il mancato uso del metodo show)
fig_scatter
if uso_resampled_frontiers:
##di seguito il codice per il calcolo delle resampled frontiers
#crea un vettore numpy contenente le medie attese delle variabili, ovvero in questo caso i rendimenti periodicizzati (ovvero trasformati da annuali in settimanali o mensili)
means=(1+expected_returns)**(1/periodicity)-1 #esempio di come si possa vettorializzare il calcolo (velocizzandolo)
#inizializza la matrice 3d che contiene i pesi di tutte le frontiere efficienti
ptf_weights_3darray=np.zeros([num_variabili, (n_step+1), n_scenari])
#inizializza le matrici destinate a contenere varianze e ritorni (da resampling) delle varie frontiere efficienti
variance_vector_2darray=np.zeros([(n_step+1), n_scenari])
returns_vector_2darray=np.zeros([(n_step+1), n_scenari])
#inizializza le matrici destinate a contenere di volta in volta le covarianze ed i
#rendimenti ricampionati dei singoli scenari
covariance_matrix_sampling=np.zeros([num_variabili, num_variabili])
returns_sampling=np.zeros([num_variabili])
#crea matrice vuota n*num_variabili destinata ad accogliere i returns periodali ricampionati con t-Student multivariata
output_t=np.empty([n, num_variabili])
if plottare_andamenti_simulati=="y":
#crea matrice vuota n*num_variabili*n_scenari destinata alla storicizzazione dei dati contenuti nella matrice di cui sopra
output_t_3d=np.empty([n, num_variabili, n_scenari])
#qui si specifica la funzione da minimizzare che deve essere espressa come funzione di un array numpy
#notare che ora si usa la covarianza calcolata sui rendimenti campionati, ovvero covariance_matrix_sampling
def fun_varianza_resampling(ptf_weights: np.array) -> float:
return ((ptf_weights.T).dot(covariance_matrix_sampling)).dot(ptf_weights) #w*VAR*w ovvero la varianza di portafoglio
#notare che si usa returns_sampling in luogo di expected_returns (perchΓ© si usano i rendimenti dello scenario)
def vincolo_rendimento_resampling(ptf_weights: np.array) -> float:
return (ptf_weights.T).dot(returns_sampling) - desired_return
#qui si specifica la funzione da minimizzare per il portafoglio di massimo rendimento
#notare che si usa return_sampling ovvero i rendimenti ricampionati in luogo degli expected returns originali
def fun_rendimento_resampling(ptf_weights: np.array) -> float:
return -(ptf_weights.T).dot(returns_sampling) #si minimizza l'opposto del rendimento per massimizzarlo
#inizializza le grandezze destinate a tenere traccia di eventuali anomalie nell'ottimizzatore di scipy (minimize)
anomalies_count=0
anomalies_status=[]
##da qui si parte con la generazione degli scenari (via simulazioni monte carlo) e successivo calcolo delle relative
##frontiere efficienti
#annuncio ed inizializzo barra avanzamento per le simulazioni
st.write("\n")
st.write("\n")
st.write("\n")
st.write("\n")
st.write("\n")
st.write("Avanzamento elaborazione scenari e relative frontiere ricampionate (Resampled Frontiers)")
barra_avanzamento_simulazioni = st.progress(0)
st.write("\n")
for z in range(n_scenari):
#aggiorno barra avanzamento simulazioni
barra_avanzamento_simulazioni.progress(float((z+1)/n_scenari))
#genera n estrazioni (vettori) da una gaussiana multivariata con medie nulle e covarianza covariance_matrix
#(ergo una matrice n*num_variabili, ovvero estrazioni*variabili)
output_n=np.random.multivariate_normal(np.zeros(num_variabili), covariance_matrix, n)
##codice seguente Γ© necessario se si vuole trasformare l'estrazione di cui sopra in una estrazione da t-student multivariata
#degree of freedom di una t-student multivariata da cui si vuole estrarre campioni
df=6
#n estrazioni da distribuzione chi quadro che servono per il fattore di correzione del vettore dell'estrazione dalla gaussiana
w=np.random.chisquare(df, n) #attenzione che w Γ© un vettore di dimensione n, come del resto il fattore_correzione a seguire
#il fattore di correzione Γ© pari a radice_quadrata(df/estrazione_chi_q)
fattore_correzione=np.sqrt(w/df) #np.sqrt funziona element-wise
fattore_correzione=fattore_correzione**(-1) #inverte per ottenere radice_quadrata(df/estrazione_chi_q) ovvero il fattore di correzione da moltiplicare per l'estrazione dalla normale
#a seguire la moltiplicazione di ciascuna estrazione dalla gaussiana per il fattore di correzione corrispondente (element-wise)
for i in range(n):
output_t[i, :]=np.multiply(output_n[i, :], fattore_correzione[i]) #np.multiply funziona element-wise
#occorre risommare il vettore delle medie in quanto le estrazioni sono fatte da distribuzioni con medie nulle
output_n[i, :]=means+output_n[i, :]
#nel caso della t-student si normalizza anche per la deviazione standard della t-student standardizzata (che NON Γ© 1 come invece nel caso della gaussiana standardizzata)
output_t[i, :]=means+output_t[i, :]/(np.sqrt(df/(df-2))) #serve quindi per avere una matrice covarianza finale (calcolata sul sample multivariato estratto) asintoticamente uguale alla matrice covariance_matrix originale
if plottare_andamenti_simulati=="y":
#storicizza i rendimenti ricampionati con t-Student ad uso successivo (grafici)
output_t_3d[:, :, z]=output_t
#calcola i nuovi rendimenti medi (dello scenario z)
returns_sampling=np.mean(output_t, axis=0)
#calcola la nuova matrice covarianza a valere sui rendimenti da scenario z
covariance_matrix_sampling=np.cov(output_t, rowvar=False)
#riannualizza i rendimenti
returns_sampling=(1+returns_sampling)**(periodicity)-1
#qui si specificano i vincoli (min, max) per le singole variabili (NB: il numero di vincoli deve essere esattamente uguale al numero di variabili)
bnds = tuple([(valore_minimo_per_singola_asset_class, valore_massimo_per_singola_asset_class) for i in range(num_variabili)])
#di seguito la chiamata all'ottimizzatore con argomenti: la funzione-oggetto da minimizzare, X0 ovvero un initial guess delle variabili, il metodo scelto ('SLSQP' Γ©
#l'unico metodo che supporta ogni tipo di vincolo), i bounds sui valori delle singole variabili, i vincoli su piΓΊ variabili simultaneamente, infine le opzioni
opt={'maxiter': maxiter, 'disp': False, 'ftol': 1e-12, 'eps': 1.4901161193847656e-08} #valori di default 'eps': 1.4901161193847656e-08, 'ftol': 1e-06 (si tratta rispettivamente della step size (eps) usata per l'approssimazione numerica della jacobiana ovvero il vettore del gradiente, e dell'obbiettivo di precisione (ftol) sulla funzione obbiettivo)
res = minimize(fun_varianza_resampling, x0=ptf_weights_equally, method='SLSQP', bounds=bnds, constraints=st.session_state.vincoli_generali, options=opt)
#di seguito il codice che serve per tenere traccia di eventuali anomalie nell'ottimizzatore di scipy (minimize)
if res.success!=True:
anomalies_count+=1
anomalies_status.append(res.message)
ptf_weights=res.x #attribuisce al vettore pesi i pesi ottimali calcolati da minimize (relativi al portafoglio di minima varianza)
ptf_min_var_return=(ptf_weights.T).dot(returns_sampling) #calcola il rendimento del portafoglio ottimale di minima varianza
ptf_min_var_variance=res.fun #attribuisce ad apposita variabile il valore finale minimizzato della funzione obbiettivo (ovvero la varianza dei rendimenti di portafoglio)
##di seguito si calcola il portafoglio di massimo rendimento (da fare per il caso in cui vi siano vincoli complessi)
#di seguito la massimizzazione del rendimento (minimizza l'opposto) con vincoli invariati
res_return = minimize(fun_rendimento_resampling, x0=ptf_weights_equally, method='SLSQP', bounds=bnds, constraints=st.session_state.vincoli_generali, options=opt)
#di seguito il codice che serve per tenere traccia di eventuali anomalie nell'ottimizzatore di scipy (minimize)
if res_return.success!=True:
anomalies_count+=1
anomalies_status.append(res.message)
#estrae il valore finale del rendimento (massimizato); ovviamente va invertito di segno perchΓ© la funzione obbiettivo Γ© l'opposto del rendimento
ptf_max_risk_return=-res_return.fun
#come in precedenza calcola lo step di aumento dei rendimenti da aggiungere per ogni nuovo portafoglio da ottimizzare sulla frontiera
step=(ptf_max_risk_return-ptf_min_var_return)/n_step
ptf_weights_3darray[:, 0, z]=ptf_weights #il primo portafoglio Γ© quello di minima varianza di cui giΓ‘ abbiamo calcolato i pesi
#la matrice (resampled frontiers) delle varianze con shape n_step+1, n_scenari
variance_vector_2darray[0, z]=ptf_min_var_variance
#la matrice (resampled frontiers) dei rendimenti con shape n_step+1, n_scenari
returns_vector_2darray[0, z]=ptf_min_var_return
desired_return=ptf_min_var_return+step
for i in range(n_step):
#si minimizza la varianza ricampionata sotto il vincolo dei rendimenti ricampionati
res = minimize(fun_varianza_resampling, x0=ptf_weights, method='SLSQP', bounds=bnds,
constraints=[i for i in st.session_state.vincoli_generali] + [{'type': 'eq', 'fun': vincolo_rendimento_resampling}], #aggiunge il vincolo sul rendimento desiderato
options=opt)
#di seguito il codice che serve per tenere traccia di eventuali anomalie nell'ottimizzatore di scipy (minimize)
if res.success!=True:
anomalies_count+=1
anomalies_status.append(res.message)
ptf_weights=res.x
ptf_weights_3darray[:, i+1, z]=ptf_weights #si salvano i pesi di portafoglio nel cubo di dimensioni num_variabili, (n_step+1), n_scenari
variance_vector_2darray[i+1, z]=res.fun
returns_vector_2darray[i+1, z]=(ptf_weights.T).dot(returns_sampling)
desired_return=desired_return+step
#si inizializza la matrice dei pesi dei portafogli sulla frontiera ricampionata
ptf_weights_resampled=np.zeros([num_variabili, (n_step+1)])
#a seguire l'averaging dei pesi lungo la direzione degli scenari
for j in range(n_step+1):
for a in range(num_variabili):
ptf_weights_resampled[a, j]=np.average(ptf_weights_3darray[a, j, :])
#si inizializzano vettori contenenti varianze e rendimenti della resampled frontier
varianze_frontiera_ricampionata=np.zeros([(n_step+1)])
rendimenti_frontiera_ricampionata=np.zeros([(n_step+1)])
#qui si popolano i vettori di cui sopra
#si tenga ovviamente presente che si usa varianze e rendimenti "storici" (o comunque
#quelli usati nell'ottimizzazione di Markowitz)
for s in range(n_step+1):
varianze_frontiera_ricampionata[s]=((ptf_weights_resampled[:, s].T).dot(covariance_matrix)).dot(ptf_weights_resampled[:, s])
rendimenti_frontiera_ricampionata[s]=(ptf_weights_resampled[:, s].T).dot(expected_returns)
#si passa alle deviazioni standard annualizzate
dev_std_frontiera_ricampionata=(np.sqrt(varianze_frontiera_ricampionata))*np.sqrt(periodicity)
st.write("---------------------------------------------------------------------------------------------")
st.write("A seguire un riepilogo della composizione dei portafogli componenti la resampled frontier:")
sintesi_composizione_portafogli_resampled_frontiers=pd.DataFrame(data=np.round(ptf_weights_resampled*100, decimals=2), #i pesi in portafoglio
columns=[("Ptf n.ro "+str(i)) for i in range(n_step+1)],
index=dati_ritorni.columns, dtype="float")
sintesi_composizione_portafogli_resampled_frontiers.to_csv("sintesi_composizione_portafogli_resampled_frontiers.csv", sep=";", decimal=".")
st.write(sintesi_composizione_portafogli_resampled_frontiers)
st.write("Di seguito un riepilogo di rendimenti, rischio ed efficienza dei portafogli componenti la resampled frontier:")
sintesi_rendimento_rischio_portafogli_resampled_frontiers=pd.DataFrame(data=np.round([rendimenti_frontiera_ricampionata*100, #i rendimenti
dev_std_frontiera_ricampionata*100, #le deviazioni standard annualizzate
dev_std_frontiera_ricampionata*2.566*100, #il VaR parametrico t-Student 6df con livello di confidenza 99%, orizzonte annuale, espresso in percentuale
np.divide((rendimenti_frontiera_ricampionata*100-risk_free_rate*100), dev_std_frontiera_ricampionata*100)], #gli sharpe ratio
decimals=2),
columns=[("Ptf n.ro "+str(i)) for i in range(n_step+1)],
index=["Rendimenti (%)", "Deviazioni Standard (%)", "VaR 99% t-Student 6df (%)", "Sharpe Ratio"],
dtype="float")
sintesi_rendimento_rischio_portafogli_resampled_frontiers.to_csv("sintesi_rendimento_rischio_portafogli_resampled_frontiers.csv", sep=";", decimal=".")
st.write(sintesi_rendimento_rischio_portafogli_resampled_frontiers)
#concateniamo i dati essenziali della Frontiera Ricampionata, inframezzando una riga vuota e le intestazioni di colonna prima della parte rendimento-rischio
empty_row=pd.Series([None for _ in range(len(sintesi_composizione_portafogli_resampled_frontiers.columns.values.tolist()))], index=sintesi_composizione_portafogli_resampled_frontiers.columns.values.tolist(), name=" ")
sintesi_composizione_portafogli_resampled_frontiers_format=sintesi_composizione_portafogli_resampled_frontiers.append(empty_row, ignore_index=False)
intestazione_row=pd.Series([f"Ptf n.ro {i}" for i in range(len(sintesi_composizione_portafogli_resampled_frontiers.columns.values.tolist()))], index=sintesi_composizione_portafogli_resampled_frontiers.columns.values.tolist(), name=" ")
sintesi_composizione_portafogli_resampled_frontiers_format=sintesi_composizione_portafogli_resampled_frontiers_format.append(intestazione_row, ignore_index=False)
st.session_state.riassuntivo_resampled=pd.concat([sintesi_composizione_portafogli_resampled_frontiers_format, sintesi_rendimento_rischio_portafogli_resampled_frontiers], axis=0)
#plotto il grafico con la composizione della Frontiera Ricampionata
fig=px.area(sintesi_composizione_portafogli_resampled_frontiers.T, \
x=sintesi_composizione_portafogli_resampled_frontiers.T.index, \
y=sintesi_composizione_portafogli_resampled_frontiers.T.columns, \
labels = dict(index = "N.ro Portafoglio", value = "Percentuale in portafoglio"), \
title="Andamento composizione Frontiera Ricampionata")
st.plotly_chart(fig, use_container_width=True)
#calcola le deviazioni standard annualizzate
std_dev_annualized_vector_resampled=np.sqrt(variance_vector_2darray)*np.sqrt(periodicity)
returns_vector_resampled=returns_vector_2darray
##facciamo uno stack dei dati per il grafico a seguire
##shape degli array numpy coinvolti di seguito
#std_dev_annualized_vector_resampled: shape portafogli*scenari
#returns_vector_resampled: shape portafogli*scenari
#shape del risultato: portafogli*scenari*tipo_variabile (dove tipo_variabile Γ© pari a 2, ovvero: deviazioni standard e rendimenti)
array_resampled_frontiers=np.stack([std_dev_annualized_vector_resampled*100, returns_vector_resampled*100], axis=2)
#creiamo e visualizziamo il grafico inerente le singole frontiere di Markowitz ricampionate
fig = go.Figure([
go.Scatter(
x=array_resampled_frontiers[:, i, 0],
y=array_resampled_frontiers[:, i, 1],
mode='lines',
#marker=dict(color="#444"),
line=dict(width=1),
showlegend=False,
hoverinfo='none'
) for i in range(n_scenari)])
fig.update_layout(
yaxis_title='Return',
xaxis_title='Standard Deviation',
title='Resampled Frontiers',
xaxis={"tickformat": ".2f"},
yaxis={"tickformat": ".2f"},
width=1500,
height=1000
)
if n_scenari<=1000 or forza_plotting_interattivo:
st.plotly_chart(fig, staticPlot=True, use_container_width=True) #possibile aggiungere render_mode='auto' (oppure "webgl" o "svg")
else:
fig_png=pio.to_image(fig.update_layout(template='plotly_dark'), format="png", width=1500, height=1000, scale=None, validate=True, engine='auto')
st.image(fig_png)
#creiamo e visualizziamo il grafico inerente le singole frontiere di Markowitz ricampionate
#rappresentate sotto forma di punti invece che linee continue
fig = go.Figure([
go.Scatter(
x=array_resampled_frontiers[:, i, 0],
y=array_resampled_frontiers[:, i, 1],
mode='markers',
marker=dict(color='LightSkyBlue', size=3),
opacity=0.5, #effetto gradevole ma peggiora le performance
#line=dict(width=1),
showlegend=False,
hoverinfo='none'
) for i in range(n_scenari)])
fig.update_layout(
yaxis_title='Return',
xaxis_title='Standard Deviation',
title='Resampled Frontiers (singoli portafogli)',
xaxis={"tickformat": ".2f"},
yaxis={"tickformat": ".2f"},
width=1500,
height=1000
)
if n_scenari<=1000 or forza_plotting_interattivo:
st.plotly_chart(fig, staticPlot=True, use_container_width=True) #possibile aggiungere render_mode='auto' (oppure "webgl" o "svg")
else:
fig_png=pio.to_image(fig.update_layout(template='plotly_dark'), format="png", width=1500, height=1000, scale=None, validate=True, engine='auto')
st.image(fig_png)
#plottiamo la frontiera di Markowitz vs la Frontiera Ricampionata nel caso i rendimenti attesi e le volatilitΓ‘ e correlazioni
#siano perfette (nel qual caso ovviamente Markowitz si trova necessariamente sopra la Frontiera Ricampionata)
fig = go.Figure([
go.Scatter(
name='Frontiera di Markowitz',
x=std_dev_annualized_vector*100,
y=returns_vector*100,
mode='lines',
line=dict(width=1),
showlegend=True
),
go.Scatter(
name='Frontiera Ricampionata',
x=dev_std_frontiera_ricampionata*100,
y=rendimenti_frontiera_ricampionata*100,
mode='lines',
line=dict(width=1),
showlegend=True,
hoverinfo='none'
)
])
fig.update_layout(
yaxis_title='Return',
xaxis_title='Standard Deviation',
title='Resampled Frontiers vs Markowitz',
xaxis={"tickformat": ".2f"},
yaxis={"tickformat": ".2f"},
width=1500,
height=1000
)
st.plotly_chart(fig, staticPlot=True, use_container_width=True)
#di seguito si ricalcolano rendimenti e rischi di tutti i portafogli simulati
#ipotizzando che lo scenario base sia corretto (dunque usando i suoi rendimenti
#attesi e la sua matrice di covarianza)
if plotting_grafico_ptf_simulati_spazio_originario=="y":
#inizializza le matrici destinate a contenere varianze e ritorni (da resampling) delle varie frontiere efficienti ricalcolate sullo scenario base (rendimenti attesi e matrice covarianza originali)
variance_vector_2darray_recalc=np.zeros([(n_step+1), n_scenari])
returns_vector_2darray_recalc=np.zeros([(n_step+1), n_scenari])
#effettua il ricalcolo per singolo portafoglio
for s in range(n_scenari):
for p in range(n_step+1):
variance_vector_2darray_recalc[p, s]=fun_varianza(ptf_weights_3darray[:, p, s])
returns_vector_2darray_recalc[p, s]=-fun_rendimento(ptf_weights_3darray[:, p, s]) #si usa il segno meno perchè la funzione restituiva l'opposto causa uso con il minimizer
#calcola le deviazioni standard annualizzate
std_dev_ann_vector_2darray_recalc=np.sqrt(variance_vector_2darray_recalc)*np.sqrt(periodicity)
##shape degli array numpy coinvolti di seguito
#array_resampled_frontiers_spazio_originario=np.stack([(std_dev_ann_vector_2darray_recalc.flatten())*100, (returns_vector_2darray_recalc.flatten())*100], axis=2)
#creiamo e visualizziamo il grafico inerente le singole frontiere di Markowitz ricampionate
fig = go.Figure([
go.Scatter(
x=(std_dev_ann_vector_2darray_recalc.flatten())*100,
y=(returns_vector_2darray_recalc.flatten())*100,
mode='markers',
marker=dict(color='LightSkyBlue', size=3),
opacity=0.5, #effetto gradevole ma peggiora le performance
showlegend=False,
hoverinfo='none'
)])
fig.update_layout(
yaxis_title='Return',
xaxis_title='Standard Deviation',
title="Portafogli simulati in spazio rischio-rendimento originario",
xaxis={"tickformat": ".2f"},
yaxis={"tickformat": ".2f"},
width=1500,
height=1000
)
if n_scenari<=1000 or forza_plotting_interattivo:
st.plotly_chart(fig, staticPlot=True, use_container_width=True) #possibile aggiungere render_mode='auto' (oppure "webgl" o "svg")
else:
fig_png=pio.to_image(fig.update_layout(template='plotly_dark'), format="png", width=1500, height=1000, scale=None, validate=True, engine='auto')
st.image(fig_png)
#si recuperano e si plottano gli andamenti di portafoglio nei diversi portafogli/scenari
if plottare_andamenti_simulati=="y":
for n_ro_ptf in range(0, n_step+1, step_ptf_resamp_graph):
#inizializza la matrice destinata a contenere i rendimenti di portafoglio relativi ai diversi scenari
portfolio_returns_scenari=np.zeros([n, n_scenari])
#qui si calcolano i rendimenti di portafoglio partendo dai rendimenti ricampionati degli asset ed i relativi pesi (da frontiera ricampionata)
for z in range(n_scenari):
portfolio_returns_scenari[:, z]=(output_t_3d[:, :, z]).dot(ptf_weights_resampled[:, n_ro_ptf])
#di seguito si setta il numero di periodi di tempo (settimane o mesi) in modo tale che l'orizzonte temporale del grafico non superi l'anno
tempo_grafico=min(n, periodicity)
#inizializza la matrice destinata ad accogliere i valori del portafoglio nel suo andamento temporale e per i diversi scenari
andamento_portafoglio=np.zeros([tempo_grafico+1, n_scenari])
#ovviamente si parte dal valore di 100 ad inizio periodo
andamento_portafoglio[0, :]=np.array([100 for i in range(n_scenari)])
#di seguito si calcola l'andamento del portafoglio nel tempo e per i diversi scenari
for z in range(n_scenari):
for t in range(tempo_grafico):
andamento_portafoglio[t+1, z]=andamento_portafoglio[t, z]*(1+portfolio_returns_scenari[t, z])
#plottiamo gli andamenti di portafoglio
fig = go.Figure([
go.Scatter(
#name='Resampled Frontier',
#x=andamento_portafoglio[:, i],
y=andamento_portafoglio[:, i],
mode='lines',
line=dict(width=0.5, color='#c44e52'), #'#c44e52' oppure '#d62728'
showlegend=False,
hoverinfo='none'
) for i in range(n_scenari)])
fig.update_layout(
yaxis_title="Valore del portafoglio (fatto 100 iniziale)",
xaxis_title="Tempo",
title=f"Portafoglio simulato n.ro {n_ro_ptf} (da Resampled Fr.)",
width=1500,
height=1000
)
st.plotly_chart(fig, staticPlot=True, use_container_width=True)
```
### Steps To Reproduce
please read only the error
### Expected Behavior
cache the function
### Current Behavior
AttributeError
Traceback:
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "C:\Users\A260219\Jupyter\bloomberg\prova.py", line 2126, in <module>
ottimizzazione(num_variabili, fun_varianza, ptf_weights_equally, expected_returns, lista_asset_pairplot)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 186, in __call__
return self._get_or_create_cached_value(args, kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 211, in _get_or_create_cached_value
return self._handle_cache_miss(cache, value_key, func_args, func_kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cache_utils.py", line 265, in _handle_cache_miss
computed_value = self._info.func(*func_args, **func_kwargs)
File "C:\Users\A260219\Jupyter\bloomberg\prova.py", line 1555, in ottimizzazione
st.write(pd.DataFrame(data=np.round(ptf_weights.reshape([1, num_variabili])*100, decimals=1), columns=dati_ritorni.columns, index=["Pesi"]))
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\write.py", line 200, in write
self.dg.dataframe(arg)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\dataframe_selector.py", line 116, in dataframe
return self.dg._arrow_dataframe(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\metrics_util.py", line 311, in wrapped_func
result = non_optional_func(*args, **kwargs)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\elements\arrow.py", line 117, in _arrow_dataframe
return self.dg._enqueue("arrow_data_frame", proto)
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\delta_generator.py", line 563, in _enqueue
caching.save_element_message(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\__init__.py", line 50, in save_element_message
CACHE_RESOURCE_MESSAGE_REPLAY_CTX.save_element_message(
File "C:\Users\A260219\Anaconda3\envs\lavoro\lib\site-packages\streamlit\runtime\caching\cached_message_replay.py", line 293, in save_element_message
raise AttributeError
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18
- Python version: 3.10
- Operating System: windows
- Browser: chrome
- Virtual environment: -
### Additional Information
no problems at all with st.experimental_singleton (streamlit version 1.17)
but with st.cache_resource in streamlit 1.18 i get the error above
the function is very very large and computationally expensive, but the behavior was very fine with st.experimental_singleton and streamlit version 1.17
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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"description": "This issue hasn't yet been triaged by the Streamlit team"
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] | closed | false | null | [] | null | 1 | 2023-02-11T13:26:58 | 2023-02-13T17:11:55 | 2023-02-13T17:11:54 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
add logo extra is no longer working either in my project or to visualise on streamlit extras website
### Reproducible Code Example
```Python
import streamlit as st
from streamlit_extras.app_logo import add_logo
add_logo("https://logos-world.net/wp-content/uploads/2020/06/Manchester-United-logo.png")
```
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 0 | 2023-02-10T17:15:49 | 2023-02-10T18:43:36 | 2023-02-10T18:43:36 | COLLABORATOR | null | ## π Context
As stated in https://github.com/streamlit/streamlit/issues/6087, iframe embedded Streamlit apps might break in Chrome wit third party cookie blocking setting.
The main problem is that we are accessing the localStorage for `sidebarWidth` without properly checking the availability of localStorage.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Move `localStorageAvailable` method to `storageUtils`
- Check availability for localStorage before caching the current sidebar width (the caching here is more of an optional feature anyways).
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #6087
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 1 | 2023-02-10T17:11:18 | 2023-02-10T18:04:39 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Hello there,
When doing a compound plot in altair with interval interactions, the lines are not displayed properly.
The images below will make it very clear.
Thanks a lot for your help !
### Reproducible Code Example
```python
# requirements.txt
streamlit==1.18.0
altair==4.2.2
pandas==1.3.3
altair_viewer==0.4.0
```
```python
# webapp.py
import streamlit as st
from altair_demo import main_altair
def main():
st.write("Hello")
chart = main_altair()
st.altair_chart(altair_chart=chart)
if __name__ =="__main__":
main()
```
```python
# altair_demo.py
import pandas as pd
import altair as alt
alt.renderers.enable('mimetype')
def main():
data = pd._testing.makeTimeDataFrame(freq='H')
data = data.reset_index().melt(id_vars="index")
interval = alt.selection_interval(encodings=["x"])
base = (
alt.Chart(data=data)
.mark_line(point={"filled": False, "fill": "white"}, strokeWidth=2)
.encode(
x=alt.X("index:T", title="Date"),
y=alt.Y("value", title="Cible"),
)
)
line_chart = (
base.encode(
x=alt.X("index:T", title="Date", scale=alt.Scale(domain=interval.ref())),
color="variable",
)
).properties(width=600, height=300)
view = (
base.add_selection(interval)
.encode(color="variable")
.properties(
width=600,
height=50,
)
)
histogram = (
alt.Chart(data=data)
.mark_bar().encode(
alt.X("value:Q", bin=True),
y=alt.Y("count()"),
)
).transform_filter(
interval
)
return line_chart & view | histogram
if __name__ =="__main__":
chart = main()
# chart.show()
st.altair_chart(chart)
```
### Steps To Reproduce
0. Create the files `requirements.txt`, `webapp.py` and `altair_demo.py`
1. `pip install -r requirements.txt`
2. `python altair_demo.py` -> Displaying chart at http://localhost:45747/
3. `streamlit run webapp.py` -> http://localhost:8501
### Expected Behavior
Pictures speak volume.
Altair plot from the code below:
![image](https://user-images.githubusercontent.com/78359781/218152458-b1f90ed5-0905-4ecc-a374-9e1df51b07b7.png)
### Current Behavior
Streamlit equivalent of the same plot:
![image](https://user-images.githubusercontent.com/78359781/218152529-6bea20d7-14a4-46e3-984e-e47fc866da71.png)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18.0
- Python version: Python 3.8.10
- Operating System: Ubuntu 20.04 on Windows 11 WSL
- Browser: Firefox 109.0.1 (64-bit)
- Virtual environment: virtualenv
### Additional Information
I think the issue was already raised here first: https://discuss.streamlit.io/t/data-missing-from-altair-compound-chart/11527
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 2 | 2023-02-10T16:11:05 | 2023-02-12T11:54:56 | 2023-02-12T11:54:55 | COLLABORATOR | null | ## π Context
As mentioned in this PR, the default usage of Pandas Styler's `highlight_max` within an app used in dark mode will result in unreadable cells (https://github.com/streamlit/streamlit/issues/6060).
This PR adds a quick fix that uses our dark font color in case the cell background is set to yellow. Yellow is used as default in Pandas Styler in case the user does not specify any specific color. Thereby, the default `highlight_max` use works out of the box with any Streamlit theme.
- What kind of change does this PR introduce?
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Use a dark color in case the background is `yellow` (default in `highlight_max`).
**Revised:**
![image](https://user-images.githubusercontent.com/2852129/218139331-78e990a8-4217-459c-b5a9-8b4b1edae5b8.png)
**Current:**
![image](https://user-images.githubusercontent.com/2852129/218139300-360449a6-65ce-432c-afac-ce7efdaf38a0.png)
## π§ͺ Testing Done
- [x] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #6060
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
I am trying to build an app that will connect into the API of another running app on Windows through the com interface. This has been successfully done using Jupyter and win32com. No issues have been experienced connecting in and re-running the cell multiple times.
However, when attempting the same in Streamlit, I am able to get it working for about 30 secs. After that and when the app is updated or rerun it results in a com_error.
I have recreated the issue using Excel and the same behavior is experienced, which rules out the application I am trying to build this for.
The code I am using is an adapted version of this SO post:
[Python Multithreading COM Objects - Stack Overflow](https://stackoverflow.com/questions/51670530/python-multithreading-com-objects)
### Reproducible Code Example
```Python
import streamlit as st
import win32com.client
import pythoncom
st.header('Test')
com = win32com.client.Dispatch("Excel.Application")
com_id = win32com.client.pythoncom.CoMarshalInterThreadInterfaceInStream( win32com.client.pythoncom.IID_IDispatch, com)
pythoncom.CoInitialize()
api = win32com.client.Dispatch(pythoncom.CoGetInterfaceAndReleaseStream(com_id, pythoncom.IID_IDispatch))
add_wb = st.button('Add Workbook')
if add_wb :
api.Workbooks.Add()
```
### Steps To Reproduce
1. Run the above Streamlit App
2. Open Excel
3. Click the Add Workbook button and Excel will (should) create new instances/workbooks each time it is pressed
4. Try again after 30-60s and the com_error will appear
### Expected Behavior
No com_error to occur.
### Current Behavior
After 30-60s the following error appears:
com_error: (-2147221008, βCoInitialize has not been called.β, None, None)
File "C:\Users\Andy\AppData\Local\Programs\Python\Python39\lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 562, in _run_script
exec(code, module.__dict__)
File "C:\PythonProjects\streamlit_integration\test_app.py", line 7, in <module>
com = win32com.client.Dispatch("Excel.Application")
File "C:\Users\Andy\AppData\Roaming\Python\Python39\site-packages\win32com\client\__init__.py", line 117, in Dispatch
dispatch, userName = dynamic._GetGoodDispatchAndUserName(dispatch, userName, clsctx)
File "C:\Users\Andy\AppData\Roaming\Python\Python39\site-packages\win32com\client\dynamic.py", line 106, in _GetGoodDispatchAndUserName
return (_GetGoodDispatch(IDispatch, clsctx), userName)
File "C:\Users\Andy\AppData\Roaming\Python\Python39\site-packages\win32com\client\dynamic.py", line 88, in _GetGoodDispatch
IDispatch = pythoncom.CoCreateInstance(
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.13.0
- Python version: 3.9.13 64 Bit
- Operating System: Win 10
- Browser: Edge 108.0.1462.76
- Virtual environment: None
### Additional Information
Upgraded Streamlit to 1.18.0. The above code no longer generates a new Excel workbook, but the com_error still occurs after 30-60secs
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
St shows automatically a custom theme I dunno where to modify when opening on Safari, Google Chrome and Firefox. They don't follow the theme I made in .streamlit/config.toml . Is there a way to set the global theme?
### Reproducible Code Example
```Python
This is the theme it shows
[theme]
base="dark"
primaryColor="#29a2bb"
backgroundColor="#afc6d2"
secondaryBackgroundColor="#90d4de"
```
### Steps To Reproduce
_No response_
### Expected Behavior
I tried to put the light theme in my config.toml, but it still shows the old theme in custom theme.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:1.13.0
- Python version:3.82
- Operating System:Mac OS
- Browser:Safari, Google Chrome, Firefox
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 3 | 2023-02-10T10:31:58 | 2023-02-10T18:59:54 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Hi Team,
with the changes introduced in Rename endpoints #5534 you changed the websocket request path from `/stream` to `/_stcore/stream`.
We are running streamlit behind a load balancer with a specific configuration to upgrade requests that reach `/stream` to use Websocket. This is broken since the latest release and our Apps with the new streamlit version are not working anymore.
I am pretty sure, we are not the only organization running into this issue.
If it's possible, could you rollback this change?
Thanks,
Nicolas
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: streamlit-1.18.0
- Python version: python-3.8.15
- Operating System: macOS 13.1
- Browser: Version 109.0.5414.119 (Official Build) (x86_64)
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 0 | 2023-02-10T09:43:44 | 2023-02-10T18:43:03 | 2023-02-10T18:42:39 | COLLABORATOR | null | ## π Context
Streamlit 1.18.0 breaks on Safari due to [lack of support of Regex lookbehinds](https://caniuse.com/js-regexp-lookbehind) The best solution for now is to downgrade what caused the issue.
- What kind of change does this PR introduce?
- [x] Bugfix
## π§ Description of Changes
Downgrade `decamelize` to avoid lookbehinds. Safari does not support this feature. Downgrading required a downgrade in `humanize-string` This change reverts the specific piece from #5946 if you are curious that the revert returns these dependencies back to normal.
## π§ͺ Testing Done
We cannot test specifically on Safari, which stinks a lot, so manual testing and our current CI tests should be sufficient.
## π References
- **Issue**: Closes #6092
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
[Reported](https://discuss.streamlit.io/t/version-1-18-0/37501/3?u=snehankekre) by @marduk2 on our forum. The position of the `help` tooltip for `st.metric` has changed positions in v1.18.0 and appears under the metric label instead of to its right.
### Reproducible Code Example
```Python
import streamlit as st
st.title("'Help' tooltips in st.metric render in a weird position")
st.metric(
label="Example metric",
help="Something doesn't feel right...",
value=150.59,
delta="Very high",
)
```
### Steps To Reproduce
1. Run the app
### Expected Behavior
![image](https://user-images.githubusercontent.com/20672874/218045613-aa7e4a97-5f7f-418f-ad64-a795807a7d33.png)
### Current Behavior
![image](https://user-images.githubusercontent.com/20672874/218045435-bc389e06-c5ae-4bd9-bd0b-74b1c4860976.png)
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18.0
- Python version: 3.9
- Operating System: macOS
- Browser: Chrome
- Virtual environment: NA
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 4 | 2023-02-10T06:53:06 | 2023-02-10T23:05:10 | 2023-02-10T18:42:41 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
A simple st.write('Hello world') app fails in Safari 16.3 using streamlit 1.18.0 with this error
[Error] SyntaxError: Invalid regular expression: invalid group specifier name
(anonymous function) (main.223e9539.js:2)
The app works in Safari 16.3 with streamlit 1.17.0. The app also works in Firefox 109.0.1 and Chrome 110.0.5481.77 with streamlit 1.17.0 and 1.18.0
### Reproducible Code Example
```Python
import streamlit as st
st.write('''
# My first app
Hello *world!*
''')
```
### Steps To Reproduce
streamlit run sthelloworld.py
### Expected Behavior
Should see Hello world in a new Safari window
### Current Behavior
See a blank screen in Safari. The console shows the error
[Error] SyntaxError: Invalid regular expression: invalid group specifier name
(anonymous function) (main.223e9539.js:2)
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.18.0
- Python version: 3.11.2 and 3.10.10
- Operating System: macOS 13.2
- Browser: Safari 16.3 (18614.4.6.1.5)
- Virtual environment: vent
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 1 | 2023-02-10T02:43:36 | 2023-02-10T15:44:46 | 2023-02-10T15:44:46 | NONE | null | _(Note, you don't have to fill out every section here. They're just here for guidance. That said, nicely detailed feature requests are more likely to get eng attention sooner)_
### Problem
Is your feature request related to a problem? Please describe the problem here. Ex. I'm always frustrated when [...]
### Solution
**MVP:** What's the smallest possible solution that would get 80% of the problem out of the way?
**Possible additions:** What are other things that could be added to the MVP over time to make it better?
**Preferred solution:** If you don't like the MVP above, tell us why, and what you'd like done instead.
### Additional context
Add any other context or screenshots about the feature request here. For example, did this FR come from https://discuss.streamlit.io or another site? Link the original source here!
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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The st.date_input() is not taken into account the time in the widget. We can only select : day, month, year.
In order to bypass this limitation, Iβm using st.text_input, next I convert it into full datetime format (I donβt want to use st.slider(), Itβ s ugly).
![image](https://user-images.githubusercontent.com/97457066/217923408-1b80609f-e829-48d2-90a5-03c37e9c8d9e.png)
### Solution
The purpose is to add time selection in the widget like this :
![image](https://user-images.githubusercontent.com/97457066/217924007-b441d90b-6234-483c-8fc6-1a4cf6947500.png)
--------------------------------------------
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.
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} | [] | open | false | null | [] | null | 0 | 2023-02-09T19:38:09 | 2023-02-09T19:38:09 | null | NONE | null | Without this, new users get cryptic encoding errors. Fixes: https://github.com/streamlit/streamlit/issues/2284
## π Context
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Added a condition to only show emoji when the encoding is utf-8.
- There may be other terminal encodings that also work, but utf-8 is the de facto standard.
- It's unclear whether the remaining condition about Windows terminals is needed; it's not easy for me to test that. So I've left in that condition to be conservative.
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
## π§ͺ Testing Done
To test:
1. Remove streamlit config (so it prints the greeting)
2. Run `env PYTHONIOENCODING=latin-1 streamlit hello`
3. It shouldn't crash (but it won't print the emoji greeting).
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Streamlit apps that are embedded through iframe do not appear when we use Chrome (or Chrome-based browsers) with third party cookie blocking setting.
For example, see the sample embedded in the official document below.
https://docs.streamlit.io/library/api-reference/write-magic/st.write
Without the cookie-blocking setting, it works as below.
<img width="1480" alt="CleanShot 2023-02-09 at 19 52 08@2x" src="https://user-images.githubusercontent.com/3135397/217792545-17dd1fd0-acaa-425f-9e9a-897b0d5d405b.png">
However, if we enable the settings as below,
<img width="765" alt="CleanShot 2023-02-09 at 19 53 08@2x" src="https://user-images.githubusercontent.com/3135397/217792764-03020f74-1129-47e7-a2cc-394de0d27dea.png">
the embedded app does not appear.
![CleanShot 2023-02-09 at 19 52 30@2x](https://user-images.githubusercontent.com/3135397/217792688-9ea12e70-0057-4716-8eae-ca3ae174b309.png)
FYI: According to [this Chromium document](https://www.chromium.org/for-testers/bug-reporting-guidelines/uncaught-securityerror-failed-to-read-the-localstorage-property-from-window-access-is-denied-for-this-document/), it might be an intended security behavior.
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
Embedding apps through iframe is officially expected usage, so it should work even in this setting (maybe ignoring the errors at localStorage access and fallback to some default values?)
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: (Official sample on the Cloud)
- Python version: (Official sample on the Cloud)
- Operating System: macOS Ventura 13.1 (22C65)
- Browser: Version: Chrome Version 110.0.5481.77 (Official Build) (arm64), SideKick Version 108.36.1.29778 (Official Build) (arm64)
- Virtual environment: (Official sample on the Cloud)
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 2 | 2023-02-08T22:52:22 | 2023-02-09T15:02:51 | null | COLLABORATOR | null | ### Problem
Sometimes the border around forms doesn't look good visually.
### Solution
Add a parameter to remove it.
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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Colored text and other markdown elements work in the label of `st.radio` but not in the texts of the radio elements. This is a bit weird since we do support it in the texts of checkboxes (where the text next to the checkbox is the label).
### Solution
Allow markdown in the options of `st.radio`.
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | open | false | null | [] | null | 1 | 2023-02-08T21:40:08 | 2023-02-13T20:31:25 | null | COLLABORATOR | null | ## π Context
Tech Debt: Refactor `Radio.tsx` in `shared/Radio` & `widgets/Radio`
- What kind of change does this PR introduce?
- [x] Refactoring
## π§ Description of Changes
- Refactored both `Radio.tsx` files into functional components w/ hooks
- Refactored both `Radio.test.tsx` files to use `react-testing-library` instead of enzyme
## π§ͺ Testing Done
- [x] Added/Updated unit tests | {
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## π Context
https://github.com/streamlit/streamlit/issues/5694
_Please describe the project or issue background here_
Fullscreen button can't be found because the overflow is hidden so just setting the parent div to overflow: visible will solve this.
Solution was found by: @LukasMasuch
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
![Screenshot 2023-02-08 at 11 07 47 AM](https://user-images.githubusercontent.com/16749069/217629584-a6ce8b9e-ec64-4dab-b338-97b513c9af69.png)
**Current:**
![Screenshot 2023-02-08 at 11 16 51 AM](https://user-images.githubusercontent.com/16749069/217629763-439d27a2-2548-4d30-8540-6ee4ffea632f.png)
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [x] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #5694
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | null | 3 | 2023-02-08T17:09:49 | 2023-02-09T01:08:35 | 2023-02-09T00:49:40 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Incorrect display of the graph streamlit (figure 1). A similar graph is displayed correctly in jupiter notebook figure (2). Code to reproduce the problem.
![1](https://user-images.githubusercontent.com/74976567/217598114-a5a2aba9-b16a-46c9-8d0f-2d0ad5530465.png)
![2](https://user-images.githubusercontent.com/74976567/217598146-0e08f629-5513-4d82-b83e-1f9b6bf1c6cd.png)
### Reproducible Code Example
```Python
#jupyter
import pandas as pd
import plotly.express as px
df1=pd.DataFrame([[403, 'April', 686],
[403, 'August', 958],
[403, 'December', 653],
[403, 'February', 645],
[403, 'January', 552],
[403, 'July', 901],
[403, 'June', 818],
[403, 'March', 587],
[403, 'May', 719],
[403, 'November', 850],
[403, 'October', 851],
[403, 'September', 933],
[601, 'April', 28],
[601, 'August', 35],
[601, 'December', 14],
[601, 'February', 13],
[601, 'January', 17],
[601, 'July', 32],
[601, 'June', 27],
[601, 'March', 18],
[601, 'May', 15],
[601, 'November', 14],
[601, 'October', 24],
[601, 'September', 21],
[602, 'April', 49],
[602, 'August', 169],
[602, 'December', 123],
[602, 'February', 64],
[602, 'January', 64],
[602, 'July', 132],
[602, 'June', 146],
[602, 'March', 77],
[602, 'May', 65],
[602, 'November', 106],
[602, 'October', 225],
[602, 'September', 159],
[603, 'April', 10],
[603, 'August', 5],
[603, 'December', 8],
[603, 'February', 18],
[603, 'January', 15],
[603, 'July', 5],
[603, 'June', 2],
[603, 'March', 7],
[603, 'May', 18],
[603, 'November', 14],
[603, 'October', 18],
[603, 'September', 6],
[701, 'April', 5],
[701, 'August', 7],
[701, 'December', 2],
[701, 'February', 1],
[701, 'January', 2],
[701, 'July', 6],
[701, 'June', 7],
[701, 'March', 5],
[701, 'May', 10],
[701, 'November', 2],
[701, 'October', 2],
[701, 'September', 3],
[801, 'April', 1],
[801, 'August', 12],
[801, 'December', 16],
[801, 'February', 1],
[801, 'January', 1],
[801, 'July', 9],
[801, 'June', 5],
[801, 'March', 1],
[801, 'May', 1],
[801, 'November', 16],
[801, 'October', 16],
[801, 'September', 16],
['H99', 'April', 18],
['H99', 'August', 3],
['H99', 'December', 1],
['H99', 'February', 13],
['H99', 'January', 12],
['H99', 'July', 7],
['H99', 'June', 2],
['H99', 'March', 17],
['H99', 'May', 21],
['H99', 'November', 5],
['H99', 'October', 3],
['H99', 'September', 2],
['H99', 'December', 2],
['H99', 'May', 2],
['H99', 'November', 2]], columns=['PP', 'Month', 'Count'])
df1["PP"] = df1["PP"].astype(str)
months=['January', 'February', 'March', 'April', 'May','June', 'July', 'August', 'September', 'October', 'November', 'December']
PP=["H99", "403", "601", "602", "603", "701", "801"]
fig1 = px.histogram(
df1,
x="PP",
y="Count",
color="Month",
barmode="group",
height=550,
category_orders={
"PP": PP,
"Month": months,
},
text_auto=True,
)
fig1.update_layout(title_text="P", title_x=0.5)
fig1.update_xaxes(
title_text="<b>PP</b>",
)
fig1.update_yaxes(
title_text="<b>Count</b>",
secondary_y=False,
)
fig1.update_layout(hovermode="x unified")
fig1.update_traces(
hovertemplate="<b>Count</b>: %{y:r}",
textposition="auto",
textangle=0,
)
fig1.show()
#streamlit
import pandas as pd
import plotly.express as px
import streamlit as st
df1=pd.DataFrame([[403, 'April', 686],
[403, 'August', 958],
[403, 'December', 653],
[403, 'February', 645],
[403, 'January', 552],
[403, 'July', 901],
[403, 'June', 818],
[403, 'March', 587],
[403, 'May', 719],
[403, 'November', 850],
[403, 'October', 851],
[403, 'September', 933],
[601, 'April', 28],
[601, 'August', 35],
[601, 'December', 14],
[601, 'February', 13],
[601, 'January', 17],
[601, 'July', 32],
[601, 'June', 27],
[601, 'March', 18],
[601, 'May', 15],
[601, 'November', 14],
[601, 'October', 24],
[601, 'September', 21],
[602, 'April', 49],
[602, 'August', 169],
[602, 'December', 123],
[602, 'February', 64],
[602, 'January', 64],
[602, 'July', 132],
[602, 'June', 146],
[602, 'March', 77],
[602, 'May', 65],
[602, 'November', 106],
[602, 'October', 225],
[602, 'September', 159],
[603, 'April', 10],
[603, 'August', 5],
[603, 'December', 8],
[603, 'February', 18],
[603, 'January', 15],
[603, 'July', 5],
[603, 'June', 2],
[603, 'March', 7],
[603, 'May', 18],
[603, 'November', 14],
[603, 'October', 18],
[603, 'September', 6],
[701, 'April', 5],
[701, 'August', 7],
[701, 'December', 2],
[701, 'February', 1],
[701, 'January', 2],
[701, 'July', 6],
[701, 'June', 7],
[701, 'March', 5],
[701, 'May', 10],
[701, 'November', 2],
[701, 'October', 2],
[701, 'September', 3],
[801, 'April', 1],
[801, 'August', 12],
[801, 'December', 16],
[801, 'February', 1],
[801, 'January', 1],
[801, 'July', 9],
[801, 'June', 5],
[801, 'March', 1],
[801, 'May', 1],
[801, 'November', 16],
[801, 'October', 16],
[801, 'September', 16],
['H99', 'April', 18],
['H99', 'August', 3],
['H99', 'December', 1],
['H99', 'February', 13],
['H99', 'January', 12],
['H99', 'July', 7],
['H99', 'June', 2],
['H99', 'March', 17],
['H99', 'May', 21],
['H99', 'November', 5],
['H99', 'October', 3],
['H99', 'September', 2],
['H99', 'December', 2],
['H99', 'May', 2],
['H99', 'November', 2]], columns=['PP', 'Month', 'Count'])
df1["PP"] = df1["PP"].astype(str)
months=['January', 'February', 'March', 'April', 'May','June', 'July', 'August', 'September', 'October', 'November', 'December']
PP=["H99", "403", "601", "602", "603", "701", "801"]
fig1 = px.histogram(
df1,
x="PP",
y="Count",
color="Month",
barmode="group",
height=550,
category_orders={
"PP": PP,
"Month": months,
},
text_auto=True,
)
fig1.update_layout(title_text="P", title_x=0.5)
fig1.update_xaxes(
title_text="<b>PP</b>",
)
fig1.update_yaxes(
title_text="<b>Count</b>",
secondary_y=False,
)
fig1.update_layout(hovermode="x unified")
fig1.update_traces(
hovertemplate="<b>Count</b>: %{y:r}",
textposition="auto",
textangle=0,
)
st.plotly_chart(fig1, use_container_width=True, config={"displaylogo": False})
```
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0
- Python version: 3.10.7
- Operating System: win 10
- Browser: google chrome 109.0
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | null | 1 | 2023-02-08T16:54:25 | 2023-02-10T17:51:11 | null | NONE | null | β¦fies a custom URL.
<!--
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4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
This PR implements the hamburger menu items cleanup, according to the according to the "Clean up the hamburger menu" [Product spec](https://www.notion.so/streamlit/Product-spec-fa80e423ee5e4863963f5d0f4c873c7c).
- What kind of change does this PR introduce?
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
* π§Β Report a bug β Remove by default. BUT: We have a parameter `menu_items` in `st.set_page_config` that lets the developer manually set a link for this option (see [[here](https://docs.streamlit.io/library/api-reference/utilities/st.set_page_config)](https://docs.streamlit.io/library/api-reference/utilities/st.set_page_config)). If that is set (to something different than `None`), the item should still show up.
(see below). No matter what, we should just use the name βReport a bugβ going forward.
* π§Β Get help β Remove by default. BUT: We have a parameter `menu_items` in `st.set_page_config` that lets the developer manually set a link for this option (see [[here](https://docs.streamlit.io/library/api-reference/utilities/st.set_page_config)](https://docs.streamlit.io/library/api-reference/utilities/st.set_page_config)). If that is set (to something different than `None`), the item should still show up.
* βΒ Streamlit Cloud β Remove. This is pretty redundant with βDeploy this appβ. 0.4% of all clicks.
* βΒ Report a Streamlit bug β Remove. Hardly gets clicks (0.0%).
* βΒ Visit Streamlit docs β Remove. Hardly gets clicks (0.3%).
* βΒ Visit Streamlit forums β Remove. Hardly gets clicks (0.1%).
Changes:
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
No custom menu items:
![Screenshot 2023-02-09 at 22 33 40](https://user-images.githubusercontent.com/119880369/217944501-db2bee82-d146-4144-b2aa-8eac4cf36601.png)
Deploy option available:
![Screenshot 2023-02-09 at 22 34 14](https://user-images.githubusercontent.com/119880369/217944530-75020c02-35d6-41b6-b7a6-ad86be4e19dc.png)
Custom menu items added using the following code
```
menu_items: MenuItems = {
"Get help": "https://google.com", # must be a valid URL
"Report a bug": "https://google.com", # must be a valid URL
"About": "This is a custom about text set with st.set_page_config" # can be any text
}
st.set_page_config(
page_title="This is custom page title",
menu_items=menu_items
)
```
![Screenshot 2023-02-09 at 22 35 01](https://user-images.githubusercontent.com/119880369/217944555-6c41cdeb-e983-4ed9-9741-4fdb82053ae3.png)
**Current:**
_Insert screenshot of existing UI/code here_
<img width="222" alt="Screenshot 2023-02-07 at 10 31 20" src="https://user-images.githubusercontent.com/119880369/217660184-998ab1d5-ba4f-4c3c-89cb-c6d079d0ab89.png">
## π§ͺ Testing Done
- [x] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: [STREAMLIT-2113](https://snowflakecomputing.atlassian.net/browse/STREAMLIT-2113)
- **PR in s4t repo**: https://github.com/streamlit/s4t/pull/5087
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 7 | 2023-02-08T16:48:30 | 2023-02-13T09:00:29 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
**Summary:**
When the multiselect widget is changed, the Streamlit page reloads from top to bottom, however the `session_state` receiving the output from the multiselect box [I.e. `session_state["myvar"] = st.multiselect(...)`] does not actually change (persistently) until the page reloads a _second_ time.
**Details:**
I don't know if this is actually a bug, a change request, or simply something that can't be done the way I'm coding it.
When using a widget that passes it's results to session_state [I.e. `session_state["myvar"] = st.multiselect(...)`] **the page reloads from top to bottom _as soon_ as a selection is made, however the `session_state` does not actually change until the page is reloaded a _second_ time**.
We discovered this using the `streamlit.sidebar` (however it behaves the same in any streamlit page.) We are using multiple pages in a dashboard (I.e. all our streamlit pages are in `streamlit_root/pages`) however we use a common sidebar to select what data is processed on the page.
Previously, **if a user went to a new page, all selections on the sidebar were lost** - because the sidebar reloads from scratch. So we are attempting to use `session_state` to capture those selections, so they persist amongst all the pages. We did this by using the saved parameters within `session_state`, and then using the `session_state` to set the "default" parameter in the multiselect box (see code below.)
However, this resulted in unpredictable behavior (see image.) I was able to work around, by using `experimental_rerun()` to force a second page reload anytime the multiselect was changed - but it causes a lot of slowdown and is fragile.
**_Is it possible for the `session_state`` to be immediately updated after selecting from a multiselect box with a single page reload?_**
![Streamlit bug report](https://user-images.githubusercontent.com/6683102/217595291-e6442c9c-56ac-4b12-a8e6-dd9be25c7496.png)
### Reproducible Code Example
```Python
import streamlit as st
options = ["Apple", "Orange", "Pear"]
# Initialize (check if session_state var exists and, if not, create it)
try: garbage = st.session_state["multiselect_selections"]
except KeyError:
st.session_state["multiselect_selections"] = []
st.write('(BEFORE) st.session_state["multiselect_selections"]: ', st.session_state["multiselect_selections"])
st.session_state["multiselect_selections"] = st.multiselect("Multiselect",
options,
default = st.session_state["multiselect_selections"])
st.write('(AFTER) st.session_state["multiselect_selections"]: ', st.session_state["multiselect_selections"])
```
### Steps To Reproduce
1. streamlit run code.py
2. Select from the multiselect box. Now the "Before" and "After" state of the session_state variable
3. Select another options fro the multiselect box.
4. Not the selected option disappears, but the session_state variable is finally updated after this second page reload.
### Expected Behavior
That session_state would be immediately (persistently) updated after the single page reload triggered by making a selection from the multiselect box.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: Streamlit, version 1.16.0
- Python version: 3.11
- Operating System: Windows 10 Enterprise
- Browser: Chrome
- Virtual environment: Na
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 2 | 2023-02-08T09:50:03 | 2023-02-14T07:44:01 | null | NONE | null | ### Problem
The problem is, that when doing a multi-upload using the file uploader widget, some files can fail sometimes (even though they are below the file size limit), see screenshot:
![image](https://user-images.githubusercontent.com/37546799/217493257-8acbac83-5e04-478a-8b6f-ef20ec221a51.png)
I tried uploading 13 files with ~12MB each. 7 failed and 6 succeeded. While errors don't happen regularly, it can happen. And the problem is, that the user cannot be informed about this, because I have no way to compare how many files the user intended to upload vs. how many actually uploaded.
### Solution
**MVP:** What's the smallest possible solution that would get 80% of the problem out of the way?
The obvious solution would be if the st.file_uploader object does not only create a list with the **successful** uploads, but also return an integer number how many files the user intended to upload in total. Then we can compare this with len of the list and decide whether any files failed or not.
**Possible additions:** What are other things that could be added to the MVP over time to make it better?
Even better would be of course to know, _which_ of the files failed (although not needed for me personally because I would just inform the user to redo the whole multi-upload). E.g. return a list object of the intended filenames that were supposed to upload.
### Additional context
Code used:
```
uploaded_files = st.file_uploader("**.psdata** files", type=["psdata"], accept_multiple_files=True)
for uploaded_file in uploaded_files:
bytes_data = uploaded_file.read()
st.write("filename:", uploaded_file.name, f"Bytes Len: {len(bytes_data)}")
```
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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This helps make sure:
1. Two people aren't working on the same thing
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More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
https://github.com/streamlit/streamlit/issues/5694
_Please describe the project or issue background here_
The issue is that the padding for the expander is too little and thus it doesn't show the full screen button. There are some solutions that I investigated such as passing in some props for `inExpander` and then modifying the fullScreenButton based on that prop but it didn't seem worth it to do all of the work to do that just so that we can see the button. I also updated the form because theyre similar elements / containers but form doesn't have the same problem.
Note: this affects all the widgets / elements with full screen button that can go into the expander aka charts, dataframe, etc.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
Changing the padding
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
EXPANDER:
![Screenshot 2023-02-07 at 6 04 07 PM](https://user-images.githubusercontent.com/16749069/217409983-86863a94-56db-432c-8d2f-39a08fd29961.png)
FORM:
![Screenshot 2023-02-07 at 6 07 44 PM](https://user-images.githubusercontent.com/16749069/217410546-9627c0e1-b2f6-4366-aac1-261d3af6939f.png)
_Insert screenshot of your updated UI/code here_
**Current:**
EXPANDER:
![Screenshot 2023-02-07 at 6 05 19 PM](https://user-images.githubusercontent.com/16749069/217410140-90090675-4582-4340-af43-d1844a2573a2.png)
FORM:
![Screenshot 2023-02-07 at 6 07 56 PM](https://user-images.githubusercontent.com/16749069/217410528-3479e09f-c000-4112-bf8d-58145bf57d32.png)
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [x] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #5694
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 2 | 2023-02-07T20:54:18 | 2023-02-09T19:26:55 | 2023-02-09T19:26:54 | COLLABORATOR | null | ## π Context
Avoid rogue print statements in our code by adding pre-commit step to check for & error out if a print statement exists
- What kind of change does this PR introduce?
- [x] Other, please describe: Tech Debt/Update Pre-Commit Checks
## π§ Description of Changes
- Added step to `.pre-commit-config.yaml` to check for print statements | {
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] | closed | false | null | [] | null | 0 | 2023-02-07T20:32:45 | 2023-02-07T22:57:49 | 2023-02-07T22:57:45 | COLLABORATOR | null | Minor `streamlit.runtime.state` refactor:
- There are a number of functions and types declared in `session_state.py` and shared between `session_state.py` and `widgets.py`. These are now moved to a new `common.py` module, so that we can avoid sibling modules importing from each other.
- This also means that all functions that create, inspect, and validate widget_id values are now in the same source file. (This was the original motivation for the refactor.)
- Renamed our `cull_nonexistent` functions, for removing stale widgets, to `remove_stale_widgets`
- Renamed `get_widget_id` -> `compute_widget_id`
- Renamed `GENERATED_WIDGET_KEY_PREFIX` -> `GENERATED_WIDGET_ID_PREFIX`, for consistency | {
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] | open | false | null | [] | null | 4 | 2023-02-07T16:24:43 | 2023-02-15T10:48:18 | null | NONE | null | π I work on developer experience for Streamlit and wanted to get some feedback on this recurring issue.
**TL;DR: Take a look at the [example app](https://keyed-widget-state-issue.streamlit.app/) and let us know how it impacts you, and what you think about how to fix this issue!**
**Discussion on the forums [here](https://discuss.streamlit.io/t/keyed-widget-state-persistence-discussion-possible-fixes/37359)**
One of the current Streamlit behaviors that causes confusion for many of us is how widgets with `key='foo'` lose their session_state value when they are not rendered in a given run. It seems to come up most often with multipage apps that have some state dependency between pages, but also possible in a single page app with conditional rendering. A minimal example:
```
view = st.radio("View", ["view1", "view2"])
if view == "view1":
st.text_input("Text1", key="text1")
"βοΈ Enter some text, then click on view2 above"
elif view == "view2":
"βοΈ Now go back to view1 and see if your text is still there"
```
I'm working with @tconkling on whether / how to update this behavior so it's more intuitive, or at least possible to get the intuitive behavior easily.
I put together a simple example app showing the behavior and linking some of the prior issues about it:
[https://keyed-widget-state-issue.streamlit.app/](https://keyed-widget-state-issue.streamlit.app/)
### Questions
- Do you have a full working public app where you had to hack around this (such as duplicating or using "shadow keys")? Please share with us!
- Do you have an app or use case where you rely on the current behavior (widget has `key` set but needs value to reset after not rendering), that will break if we change this? We **really** want to hear about these! Please share!
### Possible fixes
It seems like most developers we hear from find the current behavior very unintuitive, and we see a lot more use cases that have to work around this rather than benefit from it.
- Given that, should we just do a breaking change to the default behavior to persist, like most of us seem to expect?
- If so: We should still provide a path to clear keyed widget state when needed. Need to figure out how to best do this.
If not a breaking change: most proposals seem to prefer something like a `persist=` key. For example, both @whitphx and @mathcatsand propose something like this in [#4458](https://github.com/streamlit/streamlit/issues/4458). Thoughts on this approach, or other ideas?
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | open | false | null | [] | null | 2 | 2023-02-07T10:43:55 | 2023-02-09T07:56:55 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
type_util.py line 643 triggers a pandas SettingWithCopyWarning under certain condition.
### Reproducible Code Example
[![Open in Streamlit Cloud](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://issues.streamlitapp.com/?issue=gh-6073)
```Python
import pandas as pd
import streamlit as st
df = pd.DataFrame({'a': [1, 2], 'b': [11, 22]})
print('okay with full df')
st.dataframe(df)
print('add a new column')
df['value'] = [[1, 1.1], 2]
print('problem with a small portion of df that includes the new column')
st.dataframe(df[['a', 'value']])
print('no problem with the new full df')
st.dataframe(df)
if st.button('rerun'):
print('---try experiment again---')
st.experimental_rerun()
```
### Steps To Reproduce
Run the above code and see printouts for problem. Click button to rerun if desired.
### Expected Behavior
There should not be any pandas SettingWithCopyWarning.
### Current Behavior
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].astype(str)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.16.0
- Python version: 3.9.6
- Operating System: Windows
- Browser: Edge
- Virtual environment: virtualenv
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 1 | 2023-02-06T22:19:08 | 2023-02-08T20:47:51 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
When selecting multiple dates in dark mode, the range selector colors are very difficult to read.
### Reproducible Code Example
```Python
import datetime
import streamlit as st
st.date_input("The date is", value=(datetime.datetime.now() - datetime.timedelta(days=30), datetime.datetime.now()))
```
### Steps To Reproduce
1. Run the code above
2. Change the mode to `Dark Mode` while the app is running
3. Adjust the dates and see that the text in the dates is difficult to see.
### Expected Behavior
1. Run the code above
2. Change the mode to `Dark Mode` while the app is running
3. Adjust the dates and see that the text in the dates is black rather than white.
### Current Behavior
The calendar dates are really hard to see.
![image](https://user-images.githubusercontent.com/116604801/217099878-6abcbc45-55cc-492e-b80d-8456f9482f98.png)
### Is this a regression?
- [x] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0
- Python version: 3.10.9
- Operating System: MacOS 13.2
- Browser: Chrome
- Virtual environment: Pipenv
### Additional Information
_No response_
### Are you willing to submit a PR?
- [X] Yes, I am willing to submit a PR! | {
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] | null | 1 | 2023-02-06T20:51:13 | 2023-02-15T00:38:31 | null | CONTRIBUTOR | null | <!--
Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
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2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
This PR adds `step` parameter to `st.time_input` as a keyword only optional param.
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
This PR implements the hamburger menu items cleanup, according to the according to the "Clean up the hamburger menu" [Product spec](https://www.notion.so/streamlit/Product-spec-fa80e423ee5e4863963f5d0f4c873c7c).
- What kind of change does this PR introduce?
- [ ] Bugfix
- [x] Feature
- [x] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
* Renamed "About" to "About & help" menu item.
* Moved "Report a bug" item from menu to the "About" modal
* Moved "Get help" item from menu to the "About" modal
* Removed the following menu items from "Developer options" section:
* Streamlit could
* Report a Streamlit bug
* Visit Streamlit docs (link to documentation is now in the "About" modal)
* Visit Streamlit forums (link to documentation is now in the "About" modal)
* The "Promote this app" and "Report a bug with this app" menu items are added by the s4t project and removed in a [dedicated PR](https://github.com/streamlit/s4t/pull/5087)
* Visual changes to the "About modal":
* Information about Streamlit version and Streamlit-related urls are separated into a dedicated component
* URLs are blue not red
* Horizontal line separates user-added markdown from the core streamlit into
Changes:
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
*Simplified hamburger menu in the local environment:
<img width="206" alt="Screenshot 2023-02-07 at 10 24 50" src="https://user-images.githubusercontent.com/119880369/217205261-d04ea783-f4bb-459e-8489-fae184a7487b.png">
* "About" modal with custom markdown message specified by the user:
<img width="513" alt="Screenshot 2023-02-07 at 14 18 46" src="https://user-images.githubusercontent.com/119880369/217255777-188a2224-ca43-4912-a9c7-af21a130c162.png">
* "About" modal default view:
<img width="520" alt="Screenshot 2023-02-07 at 10 26 02" src="https://user-images.githubusercontent.com/119880369/217205583-2434827a-4236-4f48-8814-6a814e72eb41.png">
**Current:**
_Insert screenshot of existing UI/code here_
* Original hamburger menu in the local environment:
<img width="222" alt="Screenshot 2023-02-07 at 10 31 20" src="https://user-images.githubusercontent.com/119880369/217206679-f12498cd-7d48-47c0-9c07-19f260e53ee2.png">
* Original "About" modal with custom markdown message specified by the user:
<img width="513" alt="Screenshot 2023-02-07 at 10 32 10" src="https://user-images.githubusercontent.com/119880369/217206759-c5796dd9-c3e1-4092-9ced-5678b0d9ee73.png">
* Original "About" modal default view:
<img width="510" alt="Screenshot 2023-02-07 at 10 31 35" src="https://user-images.githubusercontent.com/119880369/217206799-6e155917-b1a8-4c39-8757-e449199657e6.png">
## π§ͺ Testing Done
- [x] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: [STREAMLIT-2113](https://snowflakecomputing.atlassian.net/browse/STREAMLIT-2113)
- **PR in s4t repo**: https://github.com/streamlit/s4t/pull/5087
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 1 | 2023-02-06T16:43:48 | 2023-02-10T20:15:31 | null | NONE | null | I know there have been "official workarounds" in the past but it seems like none of them exist or work anymore.
This feature has already been requested:
Here: https://discuss.streamlit.io/t/feature-suggestion-image-carousel/1189
and here: https://github.com/streamlit/streamlit/issues/780
it seems like people have used image carousels written in react to make this work but there's no official streamlit solution. | {
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## π Context
Close: https://github.com/streamlit/streamlit/issues/3527
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [X] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [X] Added/Updated unit tests
- [X] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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https://api.github.com/repos/streamlit/streamlit/issues/6066 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6066/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6066/comments | https://api.github.com/repos/streamlit/streamlit/issues/6066/events | https://github.com/streamlit/streamlit/issues/6066 | 1,571,983,885 | I_kwDODCoeTs5dspIN | 6,066 | Streamlit startup time could be reduced from 1s to 400ms | {
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] | open | false | null | [] | null | 3 | 2023-02-06T06:15:36 | 2023-02-07T17:27:25 | null | CONTRIBUTOR | null | ### Problem
The time between `streamlit run foo.py` and having a blank app load in the browser feels a bit slow nowadays!
Based on a quick analysis, a simple way to cut startup time by 60% would be to lazy-load certain imports.
### Methodology
1. On a new environment, install Streamlit
2. Call `python -X importtime -c 'import streamlit' 2> latency.log`
3. Look at latency.log by hand or with [Tuna](https://github.com/nschloe/tuna).
Interestingly, even if you run this multiple times, there's no real change in the numbers.
Machine: M2 Macbook Pro
### Results
The result of step 2 above is attached as [latency.log](https://github.com/streamlit/streamlit/files/10660238/latency.log).
Also, here's a pretty chart:
<img width="2105" alt="Screenshot 2023-02-05 at 22 01 09" src="https://user-images.githubusercontent.com/103002884/216897272-6af739cd-b24d-4ebb-aadd-c2719a6760b8.png">
### Findings
Streamlit takes 1s to initialize:
```
import time: 641 | 1011102 | streamlit
```
Major culprits:
- Importing pandas inside type_util: 240ms
```
import time: 2062 | 240916 | pandas
import time: 927 | 281330 | streamlit.type_util
import time: 2104 | 440877 | streamlit.runtime.state.session_state
import time: 320 | 441196 | streamlit.runtime.state.safe_session_state
import time: 175 | 442065 | streamlit.runtime.state
import time: 11 | 442076 | streamlit.runtime.state.session_state
import time: 444 | 465120 | streamlit.runtime.app_session
import time: 785 | 506798 | streamlit.runtime.runtime
import time: 146 | 506944 | streamlit.runtime
import time: 11 | 506954 | streamlit.runtime.scriptrunner
import time: 193 | 507147 | streamlit.cursor
```
- Importing pandas.style in st.arrow: 209ms
```
import time: 957 | 209657 | pandas.io.formats.style
import time: 278 | 209934 | streamlit.elements.arrow
```
- Setting up the plotly theme: 49ms
```
import time: 46609 | 49771 | streamlit.elements.lib.streamlit_plotly_theme
import time: 2810 | 54590 | streamlit.elements.plotly_chart
```
- Importing altair inside of arrow_altair (mostly to set up theme): 48ms
```
import time: 345 | 48145 | altair
import time: 124 | 124 | streamlit.elements.lib
import time: 264 | 388 | streamlit.elements.lib.dicttools
import time: 293 | 680 | streamlit.elements.arrow_vega_lite
import time: 300 | 300 | streamlit.elements.form
import time: 197 | 497 | streamlit.elements.utils
import time: 462 | 49782 | streamlit.elements.arrow_altair
```
- Loading the validators library: 40ms
```
import time: 309 | 40592 | validators
import time: 413 | 41005 | streamlit.elements.media
```
- Importing requests inside streamlit.version: 52ms
```
import time: 364 | 51844 | requests
import time: 1632 | 59739 | streamlit.version
```
- String util is slow to import probably due to emoji computation: 27ms
```
import time: 26409 | 27205 | streamlit.string_util
import time: 168 | 27587 | streamlit.file_util
import time: 729 | 58916 | streamlit.config
```
### Proposal
1. For some of the culprits above, we can just move the offending `import` out of the file's root scope and into the actual scope where it's used.
2. For the files where we import modules to set up Altair and Plotly theming, stop setting up the themes globally at import time and, instead, change the Altair and Plotly figures to use our theme before marshalling them.
3. For the emoji computation: move `EMOJI_EXTRACTION_REGEX` into a `functools.cache`'d function.
4. Consider no longer checking the Streamlit version upstream to prompt people to upgrade. We do this with 10% probability on every run, and requires `requests` (52ms) -- but it's unclear whether this actually causes a nontrivial number of people to actually upgrade.
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | closed | false | null | [] | null | 1 | 2023-02-05T20:05:44 | 2023-02-06T07:45:54 | 2023-02-06T07:45:02 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
The st.bar_chart does not handle pd.Series
I have tried :
- st.bar_chart(data = temp, x = temp.index, y = temp.values)
- st.bar_chart(x = temp.index, y = temp.values)
ValueError: The truth value of a Index is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
### Reproducible Code Example
```Python
import streamlit as st
import pandas as pd
s = pd.Series([1, 3, 5, 6, 8], index = ['a', 'b', 'c', 'd', 'e'])
st.bar_chart(data = s, x = s.index, y = s.values)
```
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: latest
- Python version: 3.10
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 2 | 2023-02-05T12:26:53 | 2023-02-13T21:09:55 | null | NONE | null | If you plot a plotly chart, it follows the default `streamlit` theme: color background, color title, etc. But the fill is still blue (the default from pyplot).
As far as i know, this now has to be done plot by ploy.
'Cause if you enter [the pyplot theme](https://matplotlib.org/stable/tutorials/introductory/customizing.html) this is overwritten by streamlit
```py
mpl.rcParams['axes.prop_cycle'] = cycler(color=['r', 'g', 'b', 'y'])
plt.plot(data) # first color is red
```
I would like to be able to setup the fill color or colors (scale option would be even nicer) only using the `.streamlit/config.toml` file.
My particular usecase, is to use streamlit's primary color as the fill color in the charts. | {
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] | open | false | null | [] | null | 0 | 2023-02-04T11:38:54 | 2023-02-04T11:38:54 | null | CONTRIBUTOR | null | ### Problem
Having app elements linger (grayed out and disabled) on screen while the app re-runs is most often useful from a UX perspective. Other times it is fundamentally undesirable, leads to both user and developer confusion, and results in a general unprofessional product feel. The desired behaviour in these cases would be to clear the offending elements before re-render. I refer to this effect as **clean-slate rendering**.
**Q: When is it undesirable to keep elements on screen?**
**A:** When we know up front that the element won't return on next re-render. In other words, in cases of smaller or lager state-changes within the app.
**Q: How can this lead to developer confusion?**
**A:** As example of developer confusion, see these issues, both directly tied with this behaviour.
- https://github.com/streamlit/streamlit/issues/2820
- https://github.com/streamlit/streamlit/issues/3768
### Solution
One solution could be to enable explicit control of re-rendering behaviour, though some simple API. I demo the effect this could have in this [app](https://clean-slate-rendering.streamlit.app/).
**MVP:** Technically speaking, there are ways of achieving clean-slate rendering today, as can be seen in my demo app. But, if you have a look at [the code](https://github.com/harahu/st-clean-slate-rendering/blob/main/__main__.py) used to achieve the result, it smells of dark magic, and might be somewhat brittle.
**Preferred solution:** I'd love to see the control of re-rendering behaviour made explicit though some neat and tidy API. Perhaps this can be configured dynamically on each container? Something like this:
```py
FOO: Final = "foo"
BAR: Final = "bar"
to_be_displayed = st.session_state.set_default("to_be_displayed", FOO)
(cont := st.container()).text(to_be_displayed)
if st.button(label="Display something else"):
st.session_state.to_be_displayed = BAR if to_be_displayed == FOO else FOO
# Use the fact that we know the content of cont will change to tell frontend to wipe it early
cont.experimental_clear_on_rerender()
else:
# Re-enable standard behaviour when we know nothing will change on re-run
cont.experimental_keep_on_rerender()
```
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | open | false | null | [] | null | 4 | 2023-02-04T09:46:14 | 2023-02-10T20:27:36 | null | NONE | null | ### Problem
The name of the config option `server.enableCORS` is confusing. As mentioned by @snehankekre in this forum [post](https://discuss.streamlit.io/t/when-to-use-enablecors-and-enablexsrfprotection-parameters/32075/5), the real behavior of this option makes it so that a better name would be `server.enableCORSProtection`.
### Solution
Rename config option `server.enableCORS` to `server.enableCORSProtection` (and remember to update API Reference docs).
### Additional context
This is even marked as "TODO" in the [source code](https://github.com/streamlit/streamlit/blob/develop/lib/streamlit/config.py#L644), but didn't have a GitHub issue opened until now π
.
---
Community voting on feature requests enables the Streamlit team to understand which features are most important to our users.
**If you'd like the Streamlit team to prioritize this feature request, please use the π (thumbs up emoji) reaction in response to the initial post.**
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] | closed | false | null | [] | null | 1 | 2023-02-03T21:17:09 | 2023-02-03T21:22:05 | 2023-02-03T21:21:44 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Your application crashes after a question :
ΠΡΠ°ΡΠΈΠΊ ΡΠΎΡΡΠ° ΠΌΠ°ΡΡΡ ΡΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΡΠΈΠΊΠ° Π΄ΠΈΠ°ΠΌΠ΅ΡΡΠΎΠΌ 30 ΠΌΠΌ ΠΏΡΠΈ Π½Π°ΡΠ°ΡΠΈΠ²Π°Π½ΠΈΠΈ ΡΠΊΠΎΡΠΎΡΡΠΈ Ρ 0 Π΄ΠΎ 1\2 ΡΠΊΠΎΡΠΎΡΡΠΈ ΡΠ²Π΅ΡΠ°.
:)
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [X] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 3 | 2023-02-03T14:24:34 | 2023-02-12T11:54:57 | 2023-02-12T11:54:56 | CONTRIBUTOR | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
The background color of the highlighted cells in `st.dataframe()` table is kept as yellow even in dark mode, while the text color changes to white.
As a result, in dark mode, the highlighted cells are very hard to read.
<img width="755" alt="CleanShot 2023-02-03 at 23 19 03@2x" src="https://user-images.githubusercontent.com/3135397/216626158-b3e0a3e9-08c3-4f41-b879-d85b3be48644.png">
### Reproducible Code Example
[![Open in Streamlit Cloud](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://issues.streamlitapp.com/?issue=gh-6060)
```Python
import streamlit as st
import pandas as pd
import numpy as np
df = pd.DataFrame(
np.random.randn(10, 20),
columns=('col %d' % i for i in range(20)))
st.dataframe(df.style.highlight_max(axis=0))
```
### Steps To Reproduce
_No response_
### Expected Behavior
The background color should also be nicely selected by default in combination with the text color.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0
- Python version: `Python 3.10.6`
- Operating System: macOS 13.1
- Browser: Sidekick (chrome-based) Version 108.35.1.29385 (Official Build) (arm64)
- Virtual environment:
### Additional Information
`color='red'` for example provide a visible color combination like `st.dataframe(df.style.highlight_max(axis=0, color='red'))`.
<img width="815" alt="CleanShot 2023-02-03 at 23 23 17@2x" src="https://user-images.githubusercontent.com/3135397/216627084-4e3b1e18-6c61-4e7a-87ee-3c08ec01768c.png">
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | open | false | null | [] | null | 0 | 2023-02-03T13:35:50 | 2023-02-06T17:55:33 | null | NONE | null | <!--
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## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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} | [] | closed | false | null | [] | null | 1 | 2023-02-03T06:44:10 | 2023-02-03T18:18:20 | 2023-02-03T18:18:20 | COLLABORATOR | null | ## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests | {
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] | open | false | null | [] | null | 1 | 2023-02-02T22:04:58 | 2023-02-02T22:05:56 | null | COLLABORATOR | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
When adding the query parameter `?embed=true` to an app URL, Streamlit removes the colored line at the top. This works as intended but if the app is moving the sidebar, there's now a small 2px wide white gap above the sidebar. This should not appear but the sidebar should always go to the very top.
### Reproducible Code Example
```Python
import streamlit as st
st.sidebar.write("foo")
```
### Steps To Reproduce
Run this app, then add `?embed=true` to its URL.
### Expected Behavior
No gap above the sidebar.
### Current Behavior
See the gap at the top:
![CleanShot 2023-02-02 at 23 04 04](https://user-images.githubusercontent.com/5103165/216459755-956ebafb-1521-4189-9e48-c41d4ff694a2.png)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0
- Python version: 3.10
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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https://api.github.com/repos/streamlit/streamlit/issues/6056 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6056/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6056/comments | https://api.github.com/repos/streamlit/streamlit/issues/6056/events | https://github.com/streamlit/streamlit/pull/6056 | 1,568,701,704 | PR_kwDODCoeTs5JJPtr | 6,056 | Bump min tornado version to 6.0.3 | {
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] | closed | false | null | [] | null | 0 | 2023-02-02T20:00:29 | 2023-02-02T20:41:04 | 2023-02-02T20:41:00 | COLLABORATOR | null | We claim to support Tornado 5.0, but it's an ancient version (March 2018) and we don't actually test against it.
This PR bumps our Tornado dependency to `>=6.0.3`. 6.0.3 was the current version of Tornado when Python 3.8 was released. | {
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https://api.github.com/repos/streamlit/streamlit/issues/6055 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6055/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6055/comments | https://api.github.com/repos/streamlit/streamlit/issues/6055/events | https://github.com/streamlit/streamlit/pull/6055 | 1,568,561,588 | PR_kwDODCoeTs5JIxZ- | 6,055 | Add ability to update layout for title | {
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] | closed | false | null | [] | null | 6 | 2023-02-02T18:28:09 | 2023-02-03T19:43:24 | 2023-02-03T19:43:24 | CONTRIBUTOR | null | <!--
Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
Looks like you can't update the title attributes because we are overriding it. I found this bug through this discussion forum post (https://discuss.streamlit.io/t/overriding-new-streamlit-theme-how-to-modify-plotly-title-and-axis-labels/36678/10) and the bug issue is here: https://github.com/streamlit/streamlit/issues/6046.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
<img width="730" alt="Screenshot 2023-02-02 at 10 27 06 AM" src="https://user-images.githubusercontent.com/103006371/216415560-d61b5539-2e44-437c-bfcb-5063202f7b9c.png">
_Insert screenshot of your updated UI/code here_
**Current:**
<img width="722" alt="Screenshot 2023-02-02 at 10 27 41 AM" src="https://user-images.githubusercontent.com/103006371/216415764-dc772169-9642-4754-b0cf-e5740ff1949e.png">
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [x] Screenshots included
- [ ] Added/Updated unit tests
- [x] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #6046
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
| {
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] | open | false | null | [] | null | 1 | 2023-02-02T18:19:47 | 2023-02-03T13:50:04 | null | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Label doesn't show if it starts with a number and is followed by a dot.
Also fails if followed by a space and additional text
### Reproducible Code Example
```Python
import streamlit as st
if st.button('1.'): #no label shown
st.write('test 1')
if st.button('123. test'): #no label shown
st.write('test 2')
if st.button('123.test'): #as expected
st.write('test 3')
```
### Steps To Reproduce
1. Just run the example
### Expected Behavior
Labels should be shown
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17
- Python version: 3.09
- Operating System: Win 11
- Browser: Firefox 109 / latest Edge
- Virtual environment: no
![Screenshot 2023-02-02 191918](https://user-images.githubusercontent.com/93788994/216412179-8edfd72e-9987-4272-9f56-d9e86cfede53.png)
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 0 | 2023-02-02T17:43:30 | 2023-02-08T05:37:46 | 2023-02-08T05:37:42 | COLLABORATOR | null | ## π Context
Recently released dependency updates, cleanup & resolve new High Severity security vulnerability [#135](https://github.com/streamlit/streamlit/security/dependabot/135)
- What kind of change does this PR introduce?
- [x] Other, please describe: **dependency updates**
## π§ Description of Changes
**Major Updates:**
- apache-arrow to **11.0.0**
- minimatch to **6.1.6**
**Minor Updates:**
- @types/katex to **0.16.0**
- @typescript-eslint/eslint-plugin to **5.51.0**
- @typescript-eslint/parser to **5.51.0**
- remark-emoji to **3.1.0**
- sass to **1.58.0**
- shell-quote to **1.8.0**
- protobufjs to **7.2.0**
- protobufjs-cli to **1.1.0** -> Addresses High Severity [#135](https://github.com/streamlit/streamlit/security/dependabot/135), removes taffydb as dependency
**Patch Updates:**
- browserslist to **4.21.5**
- color2k to **2.0.2**
- eslint-plugin-react to **7.32.2**
- iframe-resizer to **4.3.3**
- immer to **9.0.19**
- start-server-and-test to **1.15.3**
- terser to **5.16.2**
- typescript to **4.9.5**
- unist-util-visit to **4.1.2**
- immutable to **4.2.3**
- plotly to **2.18.1** | {
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Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 1 | 2023-02-02T16:36:57 | 2023-02-06T12:27:33 | 2023-02-06T12:27:33 | CONTRIBUTOR | null | <!--
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## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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https://api.github.com/repos/streamlit/streamlit/issues/6050 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6050/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6050/comments | https://api.github.com/repos/streamlit/streamlit/issues/6050/events | https://github.com/streamlit/streamlit/pull/6050 | 1,568,174,097 | PR_kwDODCoeTs5JHdMz | 6,050 | Update MPA expand/collapse functionality | {
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This PR addresses some issues reported by @jrieke and other users [here](https://www.notion.so/streamlit/Papercut-multipage-handle-b09cfe603cba4c15a307edef15a9d4a6) regarding our existing mechanism to expand/collapse the sidebar navigation.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- Removed the up and down carets, and replaced that with a more clear wording;
- Removed the overflow behavior, and instead sliced the number of apps shown when the menu is collapsed;
- Check whether the active page has sidebar widgets on it, and update the collapse/expand state based on that (we want the menu to take up as much space as possible when no widgets are below it);
- Store the expand/collapse preference in `localStorage` so it persists when you refresh the page.
- [ ] This is a breaking API change
- [x] This is a visible (user-facing) change
**Revised:**
https://user-images.githubusercontent.com/103376966/216356134-b828325e-aada-4af3-ae52-f4971705d29f.mp4
**Current:**
https://user-images.githubusercontent.com/103376966/216356614-c8c64e90-1f2c-4d6a-81f1-6608d31ebc70.mp4
## π§ͺ Testing Done
- [x] Screenshots included
- [x] Added/Updated unit tests
- [x] Added/Updated e2e tests
## π References
- https://www.notion.so/streamlit/Papercut-multipage-handle-b09cfe603cba4c15a307edef15a9d4a6
- https://www.notion.so/streamlit/Post-launch-feedback-multipage-apps-78795ad17e7e40e49dbfcfcbad47cb4f
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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https://api.github.com/repos/streamlit/streamlit/issues/6049 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/6049/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/6049/comments | https://api.github.com/repos/streamlit/streamlit/issues/6049/events | https://github.com/streamlit/streamlit/pull/6049 | 1,567,025,065 | PR_kwDODCoeTs5JDl1K | 6,049 | Add File connection and more convenience methods in Snowpark connection | {
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* Merge File connection from Zachary's standalone version
* Add convenience support in the factory function for gcs and s3
* Add snowsql config file lookup option for Snowpark init
* Add read_sql() convenience method for Snowpark
Working in a local app:
![image](https://user-images.githubusercontent.com/116604821/216196911-ffcfe30f-7f1d-4493-b2a2-d239427e876d.png)
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] | closed | false | null | [] | null | 7 | 2023-02-01T23:33:16 | 2023-02-09T15:04:07 | 2023-02-08T09:17:21 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
It seems that version 1.17.0 introduced some braking changes in padding of header paragraphs?
Version 1.15.1:
![1 15 1](https://user-images.githubusercontent.com/115263325/216190774-65961657-a77e-462f-b82a-f637f292a4b6.jpg)
Version 1.17.0
![1 17 0](https://user-images.githubusercontent.com/115263325/216190801-7f1ff8ed-a4af-43d4-b43e-77756e8cb058.jpg)
Tested on streamlit community cloud with different requriements. My github repo: https://github.com/TomJohnH/streamlit-dungeon
### Reproducible Code Example
```Python
import streamlit as st
tab1, tab2 = st.tabs(["intro", "start game"])
# ----------------- game start --------
with tab1:
st.subheader("| Intro")
col1, col2 = st.columns(2, gap="small")
with col1:
# main_image
st.image("graphics/other/dungeon_crawler.png")
st.caption(
"The Dungeon: a streamlit dungeon crawler game", unsafe_allow_html=True
)
with col2:
intro_text = """
Explore the depths of an ancient dungeon in the first streamlit-based dungeon crawler game!
Navigate through dangerous traps, defeat fearsome monsters and uncover the secrets of the DuNgeOn.
With intuitive controls and beautiful graphics, this game will keep you entertained for hours.
Experience the thrill of adventure as you progress through levels and uncover powerful treasures.
Join the adventure today and become the hero of the dungeon!
"""
st.write(f'<p style="color:#9c9d9f">{intro_text}</p>', unsafe_allow_html=True)
audio_file = open("audio/intro.mp3", "rb")
audio_bytes = audio_file.read()
st.audio(audio_bytes, format="audio/mp3")
st.subheader("| Game start")
st.write(
'<p style="color:#9c9d9f">To start the game go to the "start game" tab.</p>',
unsafe_allow_html=True,
)
st.subheader("| Controls")
st.write(
'<p style="color:#9c9d9f">Desktop: please use keyboard arrows | Mobile: please use on-screen buttons | iOS: scrolling JS does not work yet.</p><br>',
unsafe_allow_html=True,
)
with tab2:
st.write("...")
```
### Steps To Reproduce
_No response_
### Expected Behavior
Headers paragraphs spacing is the same as in 1.15.1
### Current Behavior
Visible on screenshots.
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.17.0 vs 1.15.1
- Python version: deployed on streamlit community cloud
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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} | [] | open | false | null | [] | null | 7 | 2023-02-01T22:37:08 | 2023-02-14T17:28:02 | null | CONTRIBUTOR | null | ## π Context
Customers want to be able to add formatting to their number input boxes, just like you can add formatting to st.slider instances today. This change enables customers to specify formatting strings with a single numeric specifier. The customer is then required to match the format string when putting a number in the number input. For example: if the format string is "$%dk" the user input string must have a '$' prefix and a 'k' postfix that surround an integer value. See below for additional examples.
- What kind of change does this PR introduce?
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [X] This is a visible (user-facing) change
**Revised:**
![Screenshot 2023-02-01 at 2 35 11 PM](https://user-images.githubusercontent.com/119367037/216179574-cca908cd-42b7-44e3-9967-f6631eec92a2.png)
![Screenshot 2023-02-01 at 2 35 41 PM](https://user-images.githubusercontent.com/119367037/216179655-f2494abb-1fbc-470d-8dbd-0a8a371fe78b.png)
**Current:**
You are unable to apply formatting to a number input as below.
![Screenshot 2023-02-01 at 2 30 20 PM](https://user-images.githubusercontent.com/119367037/216178573-94ae0689-d54e-4696-b37d-d334573b05a7.png)
## π§ͺ Testing Done
- [X] Screenshots included
- [X] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Using st.plotly_chart and the new streamlit theme - it is now impossible to adjust any of the title or axis labels, in terms of size, colour, position, etc.
Discussed in [this forum post](https://discuss.streamlit.io/t/overriding-new-streamlit-theme-how-to-modify-plotly-title-and-axis-labels/36678)
### Reproducible Code Example
From forum post: https://discuss.streamlit.io/t/overriding-new-streamlit-theme-how-to-modify-plotly-title-and-axis-labels/36678
# doing any of these commands does not adjust any of the title or axes.
fig.update_layout(title=dict(font=dict(size=40)))
fig.update_layout(title_font_size=40)
fig.update_layout(
title={
'text': "Plot Title",
'y':0.9,
'x':0.9,
'xanchor': 'right',
'yanchor': 'top'})
fig.update_layout(
title="Plot Title",
xaxis_title="X Axis Title",
yaxis_title="Y Axis Title",
legend_title="Legend Title",
font=dict(
family="Courier New, monospace",
size=18,
color="RebeccaPurple"
)
)
fig.update_layout(
title=dict(
text='<b>Life Expectancy - Our World in Data</b>',
x=0.5,
y=0.95,
font=dict(
family="Arial",
size=20,
color='#000000'
)
))
fig.update_layout(font={'size': 30})
Copy and paste example:
```Python
import numpy as np
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import streamlit as st
df = pd.read_csv(
"https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv"
)
fig = px.line(
df, x="Date", y="AAPL.High", title="Time Series with Range Slider and Selectors"
)
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list(
[
dict(count=1, label="1m", step="month", stepmode="backward"),
dict(count=6, label="6m", step="month", stepmode="backward"),
dict(count=1, label="YTD", step="year", stepmode="todate"),
dict(count=1, label="1y", step="year", stepmode="backward"),
dict(step="all"),
]
)
),
)
fig.update_layout(height=300, width=600)
fig.update_layout(
font_family="Courier New",
font_color="blue",
title_font_family="Times New Roman",
title_font_color="red",
legend_title_font_color="green"
title_font_size=40,
)
st.plotly_chart(fig, theme="streamlit")
```
### Steps To Reproduce
1. use st.plotly_chart
2. try to override the title or axis labels using the normal fig.update_traces commands
### Expected Behavior
I expect that the plot title and axis labels can be adjusted like they used to be.
### Current Behavior
The title and axis labels do not change.
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
Streamlit version: 1.17.0
Python version: 3.8.13
Conda
OS version: Mac
Browser version: Chrome/safari
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | closed | false | null | [] | null | 1 | 2023-02-01T19:51:54 | 2023-02-01T22:23:45 | 2023-02-01T22:22:53 | COLLABORATOR | null | ## π Context
Continuing the gradual adoption of `from __future__ import annotations`
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [x] Refactoring
- [ ] Other, please describe:
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] | closed | false | null | [] | null | 2 | 2023-02-01T16:57:25 | 2023-02-03T19:18:47 | 2023-02-03T19:18:28 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
![image](https://user-images.githubusercontent.com/16603602/216108368-464350aa-5f78-41bf-9500-14b14c1d0d66.png)
in chrome
### Reproducible Code Example
```Python
from threading import Thread
from streamlit.runtime.scriptrunner import add_script_run_ctx
import time
import streamlit as st
import datetime
def writesome(x):
time.sleep(1)
st.write(x)
ts = []
st.write("start threading ")
st.write(datetime.datetime.now())
for j in range(0,4):
t = Thread(target=writesome,args=("sssss",))
ctx = add_script_run_ctx(t)
ctx.start()
ts.append(ctx)
for i in range(0,len(ts)):
ts[i].join()
st.write(datetime.datetime.now())
st.write("done")
```
### Steps To Reproduce
streamlit run test.py
### Expected Behavior
_No response_
### Current Behavior
![image](https://user-images.githubusercontent.com/16603602/216109779-4a91b489-0d44-46e1-9785-fcbc2f8e9b55.png)
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:1.17.0
- Python version: 3.10.9
- Operating System:windows
- Browser:chrome
- Virtual environment: anaconder
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | null | 2 | 2023-02-01T13:16:45 | 2023-02-07T22:11:16 | null | CONTRIBUTOR | null | <!--
Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
This PR introduces support for tooltips on text elements in the following widgets:
* st.markdown
* st.title
* st.header
* st.subheader
* st.caption
* st.text
* st.latex
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | open | false | null | [] | null | 3 | 2023-02-01T12:26:13 | 2023-02-10T16:38:46 | null | CONTRIBUTOR | null | <!--
Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
Close: https://github.com/streamlit/streamlit/issues/5756
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
- [ ] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
Trying to generate the full report, the webpage would crash
### Reproducible Code Example
_No response_
### Steps To Reproduce
_No response_
### Expected Behavior
_No response_
### Current Behavior
_No response_
### Is this a regression?
- [X] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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] | null | 1 | 2023-01-31T14:33:25 | 2023-02-09T10:09:21 | 2023-02-09T10:09:20 | CONTRIBUTOR | null | <!--
Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
This PR adds "How to embed this app?" option to Hamburger menu with detailed instructions about Streamlit app embedding.
- [ ] Bugfix
- [x] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [x] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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Before contributing (PLEASE READ!)
β οΈ If your contribution is more than a few lines of code, then prior to starting to code on it please post in the issue saying you want to volunteer, then wait for a positive response. And if there is no issue for it yet, create it first.
This helps make sure:
1. Two people aren't working on the same thing
2. This is something Streamlit's maintainers believe should be implemented/fixed
3. Any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers
4. Your time is well spent!
More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing
-->
## π Context
_Please describe the project or issue background here_
- What kind of change does this PR introduce?
Sometimes hamburger menu gets printed when using recently introduced **Print** option, this PR adds "display: none" to hamburger menu, so it's not printed.
- [x] Bugfix
- [ ] Feature
- [ ] Refactoring
- [ ] Other, please describe:
## π§ Description of Changes
- _Add bullet points summarizing your changes here_
- [ ] This is a breaking API change
- [ ] This is a visible (user-facing) change
**Revised:**
_Insert screenshot of your updated UI/code here_
**Current:**
_Insert screenshot of existing UI/code here_
## π§ͺ Testing Done
- [ ] Screenshots included
- [ ] Added/Updated unit tests
- [ ] Added/Updated e2e tests
## π References
_Does this depend on other work, documents, or tickets?_
- **Issue**: Closes #XXXX
---
**Contribution License Agreement**
By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.
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] | closed | false | null | [] | null | 1 | 2023-01-31T00:31:51 | 2023-01-31T21:26:59 | 2023-01-31T21:26:59 | NONE | null | For example, the basic app functionality is free, while additional features will be available starting from a certain plan. I think this is a good way for both earning money by app authors and monetizing the Streamlit project.
To prepare plans, I imagine it will be needed a visual builder inside the app developer's account in Streamlit/Snowflake. The `pricing` parameter should have default value `False`. The non-default value should be the name of the plan starting from which the user gets access to the element. If, for instance, `st.radio` has a `pricing` value other than `False`, only the variant corresponding to `index` will be available to free users or subscribers of lower plans. For a paid subscription, the user will need to register in Streamlit/Snowflake (ideally via popular social networks and email services). Most of the money will go to the app developer, while Snowflake company will take a certain percentage.
Drawback: if we are talking about the implementation of the `pricing` parameter for locally running applications, a significant disadvantage would be the requirement for an Internet connection when using the app. | {
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] | closed | false | null | [] | null | 1 | 2023-01-30T23:54:52 | 2023-01-31T21:29:15 | 2023-01-31T21:29:03 | NONE | null | ### Checklist
- [X] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [X] I added a very descriptive title to this issue.
- [X] I have provided sufficient information below to help reproduce this issue.
### Summary
When I try to visit snowloader.streamlit.app I receive a "Please Wait" message that will not load a new page or allow me to do anything. No matter how long I sit on the page "Please Wait" will not change.
### Reproducible Code Example
_No response_
### Steps To Reproduce
1. Go to "https://snowloader.streamlit.app"
2. "Please wait" should appear in the center screen
### Expected Behavior
There would be a SnowFlake sign in page for me to sign in and load a CSV file.
### Current Behavior
_No response_
### Is this a regression?
- [ ] Yes, this used to work in a previous version.
### Debug info
- Streamlit version:
- Python version:
- Operating System:
- Browser:
- Virtual environment:
### Additional Information
_No response_
### Are you willing to submit a PR?
- [ ] Yes, I am willing to submit a PR! | {
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