import os
from datetime import datetime
from pathlib import Path
from shutil import rmtree

import pytz
from huggingface_hub import HfApi, Repository

frequency = os.environ.get("FREQUENCY", '').lower()
GENERATED_BELOW_MARKER = "--- Generated Part of README Below ---"
username = os.environ["USERNAME"]
hf_token = os.environ["HF_TOKEN"]
local_repo_path = "./readme_repo"


def update_dataset_readme(dataset_name: str, subreddit: str, new_rows: int) -> None:
    """
    Update the README file of a specified dataset repository with new information.

    Args:
    dataset_name (str): Name of the dataset repository.
    subreddit (str): Name of the subreddit being used for dataset creation.
    new_rows (int): Number of new rows added in the latest update.
    hf_token (str): Hugging Face authentication token.
    local_repo_path (str): Local path to clone the repository.
    """
    # Initialize HfApi
    api = HfApi()

    # Download README file
    readme_path = api.hf_hub_download(repo_id=dataset_name, repo_type="dataset", filename="README.md")

    # Read it
    with open(readme_path, "r") as file:
        old_readme = file.read()

    # Modify it
    new_readme = append_to_readme(subreddit=subreddit, new_rows=new_rows, old_readme=old_readme)

    # Commit modifications
    api.upload_file(
        path_or_fileobj=new_readme.encode(),
        path_in_repo="README.md",
        repo_id=dataset_name,
        repo_type="dataset",
        commit_message=f'Pushing {new_rows} new rows'
    )


def append_to_readme(subreddit: str, new_rows: int, old_readme: str) -> str:
    """
    Append new information to the existing README content.

    Args:
    subreddit (str): Name of the subreddit.
    new_rows (int): Number of new rows added.
    old_readme (str): Existing README content.

    Returns:
    str: Updated README content.
    """
    latest_hour = datetime.now(pytz.utc).replace(minute=0, second=0, microsecond=0)
    latest_hour_str = latest_hour.strftime('%Y-%m-%d %H:00:00 %Z%z')

    readme_text = f"""
## Dataset Overview
The goal is to have an open dataset of [r/{subreddit}](https://www.reddit.com/r/{subreddit}/) submissions. I'm leveraging PRAW and the Reddit API to get downloads.

There is a limit of 1000 in an API call and limited search functionality, so this is run {frequency} to get new submissions.

## Creation Details
This dataset was created by [{username}/dataset-creator-reddit-{subreddit}](https://huggingface.co/spaces/{username}/dataset-creator-reddit-{subreddit})

## Update Frequency
The dataset is updated {frequency} with the most recent update being `{latest_hour_str}` where we added **{new_rows} new rows**.

## Licensing 
[Reddit Licensing terms](https://www.redditinc.com/policies/data-api-terms) as accessed on October 25:
[License information]

## Opt-out
To opt-out of this dataset please make a pull request with your justification and add your ids in filter_ids.json

1. Go to [filter_ids.json](https://huggingface.co/spaces/reddit-tools-HF/dataset-creator-reddit-bestofredditorupdates/blob/main/filter_ids.json)
2. Click Edit
3. Add your ids, 1 per row
4. Comment with your justification
"""

    if GENERATED_BELOW_MARKER in old_readme:
        index = old_readme.index(GENERATED_BELOW_MARKER) + len(GENERATED_BELOW_MARKER)
        new_readme = old_readme[:index] + "\n\n" + readme_text
    else:
        new_readme = old_readme + "\n\n" + GENERATED_BELOW_MARKER + "\n\n" + readme_text + "\n"

    return new_readme