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Welcome to Kegger

PyPI version

A lightweight tool for interfacing with the KEGG (Kyoto Encyclopedia of Genes and Genomes) database.

kegger allows you to retrieve biological pathways, genome annotations, and gene-to-pathway mappings for use in Pandas DataFrames or downstream databases (like Django or SQLAlchemy).

Key Features

  • Automated Parsing: Converts tricky KEGG flat-files into clean Python dictionaries.
  • Pandas Integration: Native support for converting KEGG lists into DataFrames.
  • Smart Caching: Optional SQLite caching to speed up repeated calls and reduce server load.

Quick Start

To get started, you can initialize the optional cache and fetch a specific pathway record:

import kegger as kg

# Optional: Enable caching for 30 days
kg.initialize_kegger(cache_path="my_kegg_cache", expire_days=30)

# Fetch Glycolysis for E. coli
org = "eco"
path_id = "eco00010"  # or 'path:eco00010'
path_record = kg.get_path(path_id)

# Parse the raw text into a structured dictionary
path_dict = kg.kegg_parser(path_record)

print(path_dict.keys())
print(path_dict.get("NAME"))
print(path_dict.get("GENE")[:5]) # Show first 5 genes

dict_keys(['ENTRY', 'NAME', 'DESCRIPTION', 'CLASS', 'PATHWAY_MAP', 'MODULE',
            'DBLINKS', 'ORGANISM', 'GENE', 'ORTHOLOG', 'COMPOUND', 'REFERENCE',
            'AUTHORS', 'TITLE', 'JOURNAL', 'REL_PATHWAY', 'KO_PATHWAY'])

Glycolysis / Gluconeogenesis - Escherichia coli K-12 MG1655

['b0114', 'b0115', 'b0116', 'b0325', 'b0356']

Project layout

kegger/
    kegg_tools.py    # Core library functions
examples/
    basic_usage.py   # Starter script
    genome_mapping.py # Advanced DataFrame examples

Data Attribution and Citations

This package retrieves data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) REST API.

  • Data Source: KEGG REST API
  • Terms of Use: Please note that KEGG is for academic use by academic users at academic institutions. For-profit users may require a license. See the KEGG Terms of Use for details.

If you use data retrieved via kegger in a publication, please cite the primary KEGG reference:

Kanehisa, M. and Goto, S.; KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27-30 (2000). doi:10.1093/nar/28.1.27

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