feat: adding the scaffolding to match the author links

README.md

@@ -67,7 +67,7 @@ There is maintained work item list [here](task_backlog.md) that you can pick up
 
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-# How to setup the environment ?
+## How to setup the environment ?
 
 ```
 ./setup.sh

src/populate_csv_files/get_article_content/get_websites_from_articles.py

@@ -1,6 +1,9 @@
 import pandas as pd
-import os
 import re
+from re import Pattern
+from typing import Dict, List
+from abc import ABC, abstractmethod
+
 
 from src.populate_csv_files.parse_new_data import url_patterns
 from src.utils import root_directory
@@ -43,10 +46,58 @@ def match_website_base(article_url, url_patterns):
  return f"Error: {e}"
  return ", ".join(base_urls) # Join unique base URLs with comma separator
 
+
+class Url:
+
+ def __init__(self, value: str):
+ self.value = value
+
+class ArticleMatcher(ABC):
+
+ @abstractmethod
+ def matches(self, url: Url) -> bool:
+ pass
+
+ @abstractmethod
+ def get_author_link(self, url: Url) -> Url:
+ pass
+
+class MatchNotFoundException(Exception):
+ pass
+
+class AuthorUrlExtractor:
+ article_matchers: List[ArticleMatcher]
+
+ def __init__(self, website_matchers):
+ self.article_matchers: List[ArticleMatcher] = website_matchers
+
+ def extract_url(self, url: Url) -> Url:
+ match_count = sum(matcher.matches(url) for matcher in self.article_matchers)
+ if match_count > 1:
+ raise Exception(f"More than one matcher: ({match_count}) matched for url: {url}")
+ if match_count == 0:
+ raise MatchNotFoundException()
+ for matcher in self.article_matchers:
+ if matcher.matches(url):
+ return matcher.get_author_link(url)
+
+
+class UrlPatternsMatcher(ArticleMatcher):
+
+ def __init__(self, url_patterns: Dict[str, str]):
+ self.url_patterns = url_patterns
+ self.matchers: Dict[Pattern[str]] = dict()
+
+ def matches(self, url: Url) -> bool:
+ return 
+
+
 def main():
  input_filepath = f"{root_directory()}/data/links/articles_updated.csv"
- articles_df = pd.read_csv(input_filepath)
-
+ articles = pd.read_csv(input_filepath)
+ for url in articles.article:
+ print(url)
+ return 
  # Iterate through each article URL, find its website match, and get the equivalent URL
  for _, row in articles_df.iterrows():
  try: