FedComp Index

Federal contractor competitive intelligence. Classifies every federal contractor in a state into one of four Posture Classes using two-axis thresholds on USASpending award data, then provides proximity maps, velocity tracking, and pre-classified datasets.

This is the meta-package. It installs:

• fedcomp-index-scoring - posture classification engine
• fedcomp-index-data - pre-classified contractor datasets

Install

pip install fedcomp-index

Usage

from fedcomp_index import classify, classify_contractor, load_state, lookup, PostureClass

# Classify a contractor from two axes
cls = classify(total_dollars=12_000_000, base_contract_count=5)
print(cls)   # PostureClass.CLASS_1

# Get a full result object
result = classify_contractor(total_dollars=12_000_000, base_contract_count=5)
print(result.posture_class)         # PostureClass.CLASS_1
print(result.total_dollars)         # 12000000
print(result.base_contract_count)   # 5

# Load pre-classified data
contractors = load_state("NV")
print(f"{len(contractors)} contractors classified")

# Look up by UEI
c = lookup("CGAKREGGN9J3")
print(c["legal_name"])        # FLEET VEHICLE SOURCE INC
print(c["posture_class"])     # Class 1

Classification methodology (v1.1)

Two axes, no composite score, no weighted sum:

Volume includes all contract types (base + delivery orders). Frequency counts base contracts only.

Full methodology: fedcompindex.org/methodology

Packages

Data sources

All public federal records:

• USASpending.gov - award history, dollar amounts, agencies, NAICS, PSC
• SAM.gov - entity registration, certifications
• SBA.gov - certification verification

Datasets

• Nevada Federal Contractors (HuggingFace)
• Nevada Federal Contract Awards (HuggingFace)
• Nevada Federal Contractors (Kaggle)

Also available on npm

npm install fedcomp-index

• fedcomp-index - meta-package
• fedcomp-index-scoring - classification engine
• fedcomp-index-data - pre-classified datasets

Links

• Website: https://fedcompindex.org/
• Nevada Rankings: https://fedcompindex.org/nv/
• Methodology: https://fedcompindex.org/methodology/
• Tabularium: https://fedcompindex.org/tabularium/
• FAQ: https://fedcompindex.org/faq/
• Source: https://github.com/fedcompindex/FedCompIndex
• PyPI: https://pypi.org/project/fedcomp-index/
• PyPI (Scoring): https://pypi.org/project/fedcomp-index-scoring/
• PyPI (Data): https://pypi.org/project/fedcomp-index-data/
• HuggingFace: https://huggingface.co/datasets/npetro6/nevada-federal-contractors
• Kaggle: https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index

Citation

@software{fedcomp_index,
  title = {FedComp Index},
  author = {FedComp Index},
  url = {https://fedcompindex.org/},
  year = {2026}
}

License

MIT