reddit_analysis/tests/README.md

test_config_utils.py

• Functions under test
  • load_config(path) — reads settings from a YAML file.
  • get_secret(key) — retrieves a secret first from os.environ, then from streamlit.secrets, else raises.
• Patching & mocking
  • Environment variables via os.environ or monkeypatch.setenv() / monkeypatch.delenv().
  • reddit_analysis.config_utils.HAS_STREAMLIT toggled to simulate presence of Streamlit.
  • streamlit.secrets replaced with a MockSecrets object exposing a .get(key) method.
• Example inputs
  • A temporary config.yaml with keys like repo_id: test/repo, batch_size: 16, replicate_model: test/model.
  • Secret key "TEST_SECRET" set in os.environ or returned by MockSecrets.get().
  • Missing secret scenario triggers ValueError("Required secret TEST_SECRET not found…").

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test_scrape.py

• Methods under test
  • RedditScraper.get_posts(subreddit) — calls PRAW client’s .subreddit(...).top() and returns a DataFrame with columns post_id, title, text, score, subreddit, created_utc, url, num_comments.
  • RedditScraper.upload_to_hf(df, date) — downloads existing parquet via hf_hub_download, deduplicates by post_id, then calls hf_api.upload_file(...).
  • main(date) CLI — loads config, checks for Reddit credentials, raises if missing.
• Patching & mocking
  • A fake PRAW client (mock_reddit_client) whose .subreddit().top() yields two Mock submissions (ids post0, post1).
  • hf_hub_download patched to return a path for a “previous” parquet file containing prev_df.
  • mock_hf_api.upload_file to capture the uploaded parquet path.
  • Environment via monkeypatch and reddit_analysis.config_utils.HAS_STREAMLIT + streamlit.secrets.
• Example inputs
  • get_posts uses two submissions with id='post0', title='Test Post 0', etc., expecting a 2‑row DataFrame.
  • upload_to_hf combines prev_df (posts 0 & 1) with new_df (posts 1 & 2), resulting in only post1 & post2 uploaded.
  • CLI invoked with no Reddit env vars, raising ValueError("Missing required Reddit API credentials").

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test_summarize.py

• Methods under test
  • RedditSummarizer.summarize_date(date) — downloads scored parquet, groups by subreddit, and computes mean_sentiment, count, total_score, weighted_sentiment, plus date.
  • RedditSummarizer.update_summary(df) — appends to or creates summary_file, preserving chronological order.
  • CLI entrypoint in main(date) — validates date format or scored-file existence.
• Patching & mocking
  • hf_hub_download patched to return a temp parquet containing sample_scored_data (4 rows for two subreddits).
  • reddit_analysis.config_utils.HAS_STREAMLIT and streamlit.secrets.get(...) for missing-file tests.
• Example inputs & expectations
  • summarize_date:

    sample_scored_data = pd.DataFrame({
      'subreddit': ['test1','test1','test2','test2'],
      'sentiment': [0.8,0.6,0.4,0.2],
      'score': [10,20,30,40],
      …
    })
    

    – Expect two summary rows:
    • test1: mean_sentiment≈0.7, count=2, total_score=30, weighted_sentiment≈0.6667
    • test2: mean_sentiment≈0.3, count=2, total_score=70, weighted_sentiment≈0.2857
  • update_summary: merges an initial 2‑row file for 2025-04-19 with a new 2‑row file for 2025-04-20, ending with 4 total rows.
  • CLI invalid date: main('2025-04-20-invalid') → ValueError("Invalid date format").
  • Missing scored file: patched hf_hub_download raises → ValueError("Failed to download scored file…").

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test_score.py

• Class & functions under test
  • RedditScorer.score_date(date) — downloads input parquet, asserts required columns (text, score, post_id, subreddit), splits into batches, calls replicate_client.run(), injects sentiment & confidence, writes parquet, then calls hf_api.upload_file().
  • CLI main(date) — reads .env or streamlit.secrets, requires REPLICATE_API_TOKEN, else raises.
• Patching & mocking
  • hf_hub_download patched to return a temp parquet for the “input” DataFrame.
  • mock_hf_api supplying a stubbed upload_file method.
  • mock_replicate_client.run side‑effect that:

    texts = json.loads(input['texts'])
    sentiments = ['positive' if i%2==0 else 'negative' for i in range(len(texts))]
    confidences = [0.9 if i%2==0 else 0.8 for i in range(len(texts))]
    

  • reddit_analysis.config_utils.HAS_STREAMLIT + streamlit.secrets.get(...) for the CLI missing‑token test.
• Example inputs & expectations
  • test_score_date: input DataFrame with two rows ('Test text 1', 'Test text 2'), expects uploaded parquet to have sentiment=['positive','negative'], confidence=[0.9,0.8] and all six columns present.
  • test_score_date_missing_columns: input missing post_id/subreddit → ValueError("missing expected columns").
  • test_score_date_batch_processing: input of 5 texts, batch_size=2 → replicate_client.run called 3 times, final uploaded file contains all 5 rows.
  • test_cli_missing_token: no REPLICATE_API_TOKEN in env or secrets → ValueError("REPLICATE_API_TOKEN is required for scoring").