JobsColombia

Tech job scoring and utilities for Colombia.

Description

JobsColombia is a Python library that provides scoring, classification, and utility functions for tech job listings in Colombia.

This library helps you:

• Score job listings based on relevance (technologies, keywords, modality)
• Classify jobs by score ranges
• Identify primary tech stacks from job descriptions
• Export and format job data to CSV

Note: This package does NOT include web scraping. Use any scraper library (like jobs_scraper, linkedin-scraper, or custom solutions) to fetch job data, then use this library to analyze and score them.

Installation

pip install jobscolombia

Or with uv:

uv add jobscolombia

Usage

import pandas as pd
from jobscolombia import calcular_score, clasificar_score

# Score a job listing
score = calcular_score(
    title="Senior Python Developer",
    description="We need a Python developer with Django, PostgreSQL, and AWS experience",
    location="Bogota, Colombia",
    company="Tech Corp"
)
# score = 85 (example)

# Classify the score
category = clasificar_score(score)
# category = "Excelente" (score >= 70)

# Score a DataFrame of jobs
df["score"] = df.apply(
    lambda r: calcular_score(
        str(r.get("title", "")),
        str(r.get("description", "")),
        str(r.get("location", "")),
    ),
    axis=1,
)

API Reference

Scoring

• calcular_score(title, description, location, company) - Calculate job relevance score (0-100)
• clasificar_score(score) - Classify score into category (Bajo, Regular, Bueno, Excelente)
• identificar_stack_principal(text) - Identify main tech stack from text

Utilities

• columnas_export() - Get standard column names for CSV export
• generar_nombre_csv(prefix) - Generate timestamped CSV filename
• formatear_fecha(date) - Format date for export

Logging

• setup_logger(name, log_dir) - Configure logger for the application

See source code for full documentation.

Project Structure

jobscolombia/
├── src/jobscolombia/
│   ├── __init__.py         # Package exports
│   ├── scoring.py         # Scoring and classification
│   ├── utils.py           # Utilities (CSV, dates)
│   ├── logger.py          # Logging setup
│   └── config.py          # Configuration
├── tests/                 # Unit tests
├── pyproject.toml        # Project configuration
├── CHANGELOG.md          # Version history
├── CONTRIBUTING.md       # Contribution guidelines
├── SECURITY.md           # Security policy
└── .github/
    └── workflows/         # GitHub Actions

Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=src/jobscolombia --cov-report=term-missing

Linting

# Check code
ruff check .

# Format code
ruff format .

Type Checking

# Run mypy
mypy src/jobscolombia --ignore-missing-imports

Security

# Run security audit
safety check
pip-audit
bandit -r src/jobscolombia

Tech Stack

• Python 3.11+ - Main language
• Pandas - Data manipulation
• Ruff - Linting and formatting
• Pytest - Testing framework

License

MIT License - see the LICENSE file for details.

Acknowledgments

• Pandas - Data analysis and manipulation tool
• Ruff - Fast Python linter and formatter
• Pytest - Testing framework

Contributing

Contributions are welcome! Please read our CONTRIBUTING.md file for guidelines.