KEGG Pathways, Genes & Compounds Scraper

Turn the KEGG database (Kyoto Encyclopedia of Genes and Genomes) into clean, structured JSON. This Apify Actor talks to the free KEGG REST API and parses its plain-text and flat-file responses into ready-to-use records for metabolic modelling, pathway analysis, drug research and bioinformatics pipelines.

Roughly ~$0.50 per 1,000 records on the Apify platform — no KEGG API key required.

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⚠️ Licensing — please read (this matters)

KEGG is free for academic and non-commercial use only. The KEGG REST API (https://rest.kegg.jp) may be used by academic users for non-commercial purposes. Commercial use, redistribution of KEGG data, and bulk downloads for commercial products require a paid license from Pathway Solutions / the KEGG FTP subscription. This Actor is a thin, rate-limited client over the public REST endpoint — it does not grant you any rights to KEGG data. You are responsible for using it within KEGG's terms:

• Non-commercial / academic research: generally fine via the REST API.
• Commercial use or redistribution: obtain a KEGG license first.
• Always cite KEGG (Kanehisa et al.) in academic work.

See https://www.kegg.jp/kegg/legal.html and https://www.pathway.jp/ for the authoritative terms. When in doubt, contact KEGG. We keep request rates modest and honest to respect their servers.

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What makes this different from our other biology scrapers

This Actor covers KEGG specifically — its pathway maps, KEGG gene ids, KEGG compound (C…) / drug (D…) / disease (H…) / module (M…) ids, and KEGG's own cross-links. If you need a different database, use the matching Actor from the same account instead:

Need	Use
Reactome pathways & reactions	reactome-pathways-scraper
UniProt protein records	uniprot-scraper
ChEMBL bioactivity & compounds	chembl-scraper
STRING protein–protein interactions	string-interactions-scraper
KEGG pathways / genes / compounds	this Actor

KEGG vs Reactome specifically: both are pathway databases, but they are not interchangeable. KEGG is manually drawn "KEGG PATHWAY maps" with its own gene and compound identifiers and a strong metabolic-pathway focus; it is licensed non-commercially. Reactome is an open-source (CC-BY) reaction-level pathway knowledgebase using Reactome stable ids and UniProt/ChEBI references. If you need reaction-level detail with an open licence, use the Reactome Actor; if you need KEGG pathway maps, KO/EC annotations and KEGG compound ids, use this one.

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Modes

Mode	What it does	Key inputs
list	List every entry in a KEGG database	database, organism (for pathways)
get	Fetch full flat-file records by id	ids
find	Keyword search inside a database	database, queries
link	Cross-references between databases	linkTarget, linkSource

Databases

pathway, disease, drug, compound, module, enzyme, organism.

Note: KEGG's /list/organism endpoint currently returns HTTP 400 upstream; the Actor automatically falls back to /list/genome, which carries the same organism table (T-number code description).

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Input

{
  "mode": "list",
  "database": "pathway",
  "organism": "hsa",
  "ids": ["hsa00010"],
  "queries": ["glucose"],
  "linkTarget": "pathway",
  "linkSource": "hsa:10458",
  "maxItems": 300
}

Field	Type	Default	Description
mode	select	list	list / get / find / link
database	select	pathway	Target DB for list / find
organism	string	hsa	KEGG organism code for listing pathways (e.g. hsa, mmu, eco)
ids	array	–	Entry ids for get, e.g. ["hsa00010","C00031"]
queries	array	–	Keywords for find, e.g. ["glucose"]
linkTarget	string	–	Target DB for link, e.g. pathway
linkSource	string	–	Source id/db for link, e.g. hsa:10458
maxItems	integer	300	Cap on output records (max 5000)

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Output

list → list_entry

{ "type": "list_entry", "entry_id": "hsa00010", "database": "pathway",
  "name": "Glycolysis / Gluconeogenesis - Homo sapiens (human)",
  "organism": "hsa", "source": "kegg", "scraped_at": "..." }

get → record (flat-file parsed, continuation-line aware)

{ "type": "record", "entry_id": "hsa00010", "database": "pathway",
  "name": "Glycolysis / Gluconeogenesis - Homo sapiens (human)",
  "description": "Glycolysis is the process of ...",
  "classes": ["Metabolism", "Carbohydrate metabolism"],
  "pathway_map": "hsa00010  Glycolysis / Gluconeogenesis",
  "gene_count": 67,
  "genes": [{ "id": "10327", "symbol": "AKR1A1" }],
  "compound_count": 31, "compounds": ["C00022", "C00024"],
  "module_ids": ["hsa_M00001"], "disease_ids": [],
  "reference_count": 0,
  "url": "https://www.kegg.jp/entry/hsa00010",
  "source": "kegg", "scraped_at": "..." }

find → search_hit · link → link — see the dataset overview view (entry_id, name, database, gene_count).

All fields are nullable; the dataset schema is permissive.

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Use cases

• Metabolic modelling — pull pathway gene/compound membership for FBA/COBRA models.
• Pathway analysis — enrichment against KEGG pathway gene sets.
• Drug research — map KEGG DRUG ids, targets and pathway context.
• Bioinformatics pipelines — reproducible KEGG id/annotation extraction.

How it works

KEGG REST returns tab-separated text (list/find/link) or flat-file records (get) — never JSON. The Actor ships a robust flat-file parser that respects the 12-character field column and reassembles continuation lines, so multi-line GENE / COMPOUND / DESCRIPTION fields are never lost. Requests are rate-limited to respect KEGG's servers.

Disclaimer

Not affiliated with or endorsed by KEGG, Kanehisa Laboratories or Pathway Solutions. Data © Kanehisa Laboratories. Use responsibly and within KEGG's licence terms.