Metadata-Version: 2.4
Name: fedcomp-index-scoring
Version: 2026.3.2
Summary: FedComp Index scoring engine. Computes posture scores and posture classes for federal contractors from USASpending award data.
Author-email: FedComp Index <contact@fedcompindex.org>
License-Expression: MIT
Project-URL: Homepage, https://fedcompindex.org/
Project-URL: Documentation, https://fedcompindex.org/wiki/methodology/
Project-URL: Repository, https://github.com/npetro6/FedCompIndex
Project-URL: Datasets, https://huggingface.co/datasets/npetro6/nevada-federal-contractors
Project-URL: Rankings, https://fedcompindex.org/nv/
Keywords: federal contracting,government procurement,small business,posture scoring,fedcomp index,posture class,usaspending,sam.gov,contractor scoring,federal awards
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Office/Business
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# FedComp Index Scoring

![FedComp Index](https://fedcompindex.org/static/img/FedComp-Index-Tabularium-1.png)

Federal contractor posture scoring. Scores any federal contractor from 0 to 100 based on public award data from USASpending.gov.

Each contractor receives a FedComp Index score and a posture class:

- **Class 1** (score 60+) - dominant award volume, typically $100M+ over 5 years
- **Class 2** (score 40-59) - mid-tier, typically $5M-$100M
- **Class 3** (below 40) - emerging or low-volume

## Install

```bash
pip install fedcomp-index
```

## Usage

```python
from fedcomp_index import score_contractor, PostureClass

result = score_contractor(
    total_awards_usd=45_000_000,
    last_award_date="2025-09-15"
)

result.fedcomp_index    # 58
result.posture_class    # PostureClass.CLASS_2
result.volume_driver    # 55
result.recency_driver   # 100
```

## FedComp Index scoring methodology

Two drivers, no normalization:

| Driver | Weight | How it works |
|--------|--------|-------------|
| Award volume | 90% | log10 of total dollars won, mapped to 0-100 |
| Award recency | 10% | Last award date, bucketed by age |

The FedComp Index score is an absolute measure. A contractor scoring 60 always represents roughly the same award volume regardless of state or time period. Scores are not percentile-ranked against peers.

Posture classes use fixed thresholds tied to the score:

| Posture class | FedComp Index score | Typical award volume |
|---------------|--------------------|--------------------|
| Class 1 | 60-100 | $100M+ |
| Class 2 | 40-59 | $5M-$100M |
| Class 3 | 0-39 | Under $5M |

Full methodology: [fedcompindex.org/wiki/methodology](https://fedcompindex.org/wiki/methodology/)

## Data sources

All data is sourced from public federal records:

- [USASpending.gov](https://www.usaspending.gov/) - award history, dollar amounts, agencies, NAICS codes, PSC codes
- [SAM.gov](https://sam.gov/) - entity registration, certifications, CAGE/UEI
- [SBA.gov](https://www.sba.gov/) - small business certification verification

## Live rankings

Scored contractor rankings with dossier pages, proximity maps, and spectator tracking:

- [Nevada](https://fedcompindex.org/nv/) - 348 contractors scored

## Datasets

Pre-scored datasets available for download:

- [Nevada Federal Contractors - FedComp Index](https://huggingface.co/datasets/npetro6/nevada-federal-contractors) (HuggingFace)
- [Nevada Federal Contract Awards - Monthly](https://huggingface.co/datasets/npetro6/nevada-federal-awards) (HuggingFace)
- [Nevada Federal Contractors - FedComp Index](https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index) (Kaggle)
- [Nevada Federal Contract Awards - Monthly](https://www.kaggle.com/datasets/npetro6/nevada-federal-awards-2026-02) (Kaggle)

## Links

- Website: [https://fedcompindex.org/](https://fedcompindex.org/)
- GitHub: [https://github.com/npetro6/FedCompIndex](https://github.com/npetro6/FedCompIndex)
- Methodology: [https://fedcompindex.org/wiki/methodology/](https://fedcompindex.org/wiki/methodology/)
- Nevada Rankings: [https://fedcompindex.org/nv/](https://fedcompindex.org/nv/)
- HuggingFace (Contractors): [https://huggingface.co/datasets/npetro6/nevada-federal-contractors](https://huggingface.co/datasets/npetro6/nevada-federal-contractors)
- HuggingFace (Awards): [https://huggingface.co/datasets/npetro6/nevada-federal-awards](https://huggingface.co/datasets/npetro6/nevada-federal-awards)
- Kaggle (Contractors): [https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index](https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index)
- Kaggle (Awards): [https://www.kaggle.com/datasets/npetro6/nevada-federal-awards-2026-02](https://www.kaggle.com/datasets/npetro6/nevada-federal-awards-2026-02)
- PyPI: [https://pypi.org/project/fedcomp-index/](https://pypi.org/project/fedcomp-index/)
- PyPI (Scoring): [https://pypi.org/project/fedcomp-index-scoring/](https://pypi.org/project/fedcomp-index-scoring/)
- PyPI (Data): [https://pypi.org/project/fedcomp-index-data/](https://pypi.org/project/fedcomp-index-data/)

## Citation

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

## License

MIT
