Delete rpst/rpst.py

rpst/rpst.py

@@ -1,131 +0,0 @@
-import argparse
-from datetime import datetime
-
-import requests
-from glyphoji import glyph
-from rich import print
-from rich.tree import Tree
-
-from .utils import convert_timestamp_to_datetime, write_post_data
-
-
-def create_post_branch(post: dict, keyword: str, tree: Tree, args: argparse) -> Tree:
-    """
-    This function extracts relevant data from a Reddit post and adds it in a tree branch structure,
-    followed by the post's selftext.
-
-    :param post: A dictionary containing the data of a Reddit post.
-    :param keyword: The keyword that is used to find posts, in his case gets uses as the filename.
-    :param tree: Tree where the post branch will be added.
-    :param args: A namespace object from argparse.
-    :returns: The main tree with added post branches.
-    """
-    # Define the data to extract from the post.
-    post_data = {
-        # "Author": post["data"]["author"],
-        f"{glyph.id_button} ID": post["data"]["id"],
-        f"{glyph.people_hugging} Subreddit": post["data"]["subreddit_name_prefixed"],
-        f"{glyph.face_with_peeking_eye} Visibility": post["data"]["subreddit_type"],
-        f"{glyph.framed_picture} Thumbnail": post["data"]["thumbnail"],
-        f"{glyph.white_question_mark} Gilded": post["data"]["gilded"],
-        f"{glyph.up_arrow} Upvotes": post["data"]["ups"],
-        f"{glyph.chart_increasing} Upvote ratio": post["data"]["upvote_ratio"],
-        f"{glyph.down_arrow} Downvotes": post["data"]["downs"],
-        f"{glyph.trophy} Awards": post["data"]["total_awards_received"],
-        f"{glyph.trophy} Top award": post["data"]["top_awarded_type"],
-        f"{glyph.no_one_under_eighteen} Is NSFW?": post["data"]["over_18"],
-        f"{glyph.left_arrow_curving_right} Is crosspostable?": post["data"][
-            "is_crosspostable"
-        ],
-        f"{glyph.bar_chart} Score": post["data"]["score"],
-        f"{glyph.card_file_box} Category": post["data"]["category"],
-        f"{glyph.globe_with_meridians} Domain": post["data"]["domain"],
-        f"{glyph.calendar} Posted on": convert_timestamp_to_datetime(
-            post["data"]["created"]
-        ),
-        f"{glyph.calendar} Approved at": post["data"]["approved_at_utc"],
-        f"{glyph.bust_in_silhouette} Approved by": post["data"]["approved_by"],
-    }
-
-    # Add the post's branch to the main tree.
-    post_branch = tree.add(f"{glyph.page_with_curl} {post['data']['title']}")
-
-    # Add each piece of extracted data as a branch of the post_branch.
-    for post_key, post_value in post_data.items():
-        post_branch.add(f"{post_key}: {post_value}", style="dim")
-
-    # This ensures that the post's selftext is also added to the written json/csv file.
-    post_data[f"{glyph.clipboard} Text"] = post["data"]["selftext"]
-    write_post_data(
-        filename=keyword, post_data=post_data, tree_branch=post_branch, args=args
-    )
-    post_branch.add(post["data"]["selftext"], style="italic")
-
-    return tree
-
-
-def get_posts(args: argparse):
-    """
-    Scrapes a given subreddit for posts that contain a specified keyword.
-    The search is limited by the number of posts and timeframe specified.
-
-    :param args: Namespace object from argparse.
-
-    Expected Object Attributes
-    --------------------------
-        - keyword: The keyword to search for in the posts.
-        - subreddit: The subreddit to scrape.
-        - listing: The type of posts to scrape. This could be 'hot', 'new', etc.
-        - timeframe: The timeframe from which to scrape posts. This could be 'day', 'week', etc.
-        - limit: The maximum number of posts to scrape.
-        - json: If specified, all found posts will be written to a json file.
-    """
-    keyword = args.keyword
-    subreddit = args.subreddit
-    listing = args.listing
-    timeframe = args.timeframe
-    limit = args.limit
-
-    # Create main result tree.
-    main_tree = Tree(
-        f"[bold]{glyph.calendar} {datetime.now()}[/]", guide_style="bold bright_blue"
-    )
-
-    # Start a new session
-    session = requests.session()
-    # Set the User-Agent to mimic a Safari browser on a Mac.
-    session.headers = {
-        "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, "
-        "like Gecko) Version/14.1.1 Safari/605.1.15"
-    }
-
-    # Send a GET request to the specified subreddit and listing,
-    # limiting the response by the specified limit and timeframe.
-    response = session.get(
-        f"https://www.reddit.com/r/{subreddit}/{listing}"
-        f".json?limit={limit}&t={timeframe}"
-    ).json()
-
-    # Initialize a counter for the number of posts found that contain the keyword.
-    found_posts = 0
-
-    # Loop through each post in the response
-    for post_index, post in enumerate(response["data"]["children"], start=1):
-        # If the keyword is found in the post's selftext or title, increment the counter and process the post.
-        if (
-            keyword.lower() in post["data"]["selftext"]
-            or keyword.lower() in post["data"]["title"]
-        ):
-            # Create a branch for found post(s) and show post index and post author as the title
-            found_tree = main_tree.add(
-                f"{glyph.bust_in_silhouette} #{post_index} by [bold]@{post['data']['author']}[/]"
-            )
-            found_posts += 1
-            create_post_branch(post=post, keyword=keyword, tree=found_tree, args=args)
-
-    # Log the number of posts in which the keyword was found
-    main_tree.add(
-        f"{glyph.check_mark_button} Keyword ('{keyword}') was found in "
-        f"{found_posts}/{len(response['data']['children'])} {listing} posts from r/{subreddit}."
-    )
-    print(main_tree)