src/openalex_enricher

Phase 2a module for enriching publications with OpenAlex concepts, topics, and field classifications.

Functions

fetch_work_concepts(work_id: str, email: str, cache_dir: str) → dict

Fetch concept and topic data from the OpenAlex API for a single work.

Parameters:

Name	Type	Description
work_id	str	OpenAlex work ID (e.g., W2078536640)
email	str	Email for polite pool access
cache_dir	str	Directory for caching JSON responses

Returns: Dict with keys:

• concepts — List of {name, score} concept entries
• topics — List of topic classifications
• field — Primary field name (e.g., "Physics")

Side effects: Caches response to {cache_dir}/{work_id}.json.

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enrich_publications(publications: pl.DataFrame, cfg: dict) → pl.DataFrame

Batch-enrich publications DataFrame with OpenAlex data.

Parameters:

Name	Type	Description
publications	pl.DataFrame	Publications with openalex_work_id column
cfg	dict	Project configuration dict

Returns: Updated DataFrame with added columns:

• openalex_concepts — JSON string of concepts list
• openalex_topics — JSON string of topics list
• openalex_field — Primary field string

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run() → None

Execute the full Phase 2a pipeline:

1. Load publications.parquet
2. Fetch OpenAlex data for each paper
3. Add concept/topic/field columns
4. Overwrite publications.parquet