semvec/pypi-packages huggingface dataset:
trainlytics 0.1.0
Open-source Python package for workout analysis and recommendations.
Requires Python: >=3.8




# trainlytics

[![PyPI version](https://img.shields.io/pypi/v/trainlytics.svg)](https://pypi.org/project/trainlytics/)
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## Overview
Open-source Python package for physical training analysis and recommendations. Ingests workout logs, computes metrics, detects plateaus, and suggests weekly progressions. Professional structure, automation, tests, and robust documentation.

- **Target audience:** Data scientists, fitness professionals, enthusiasts, and developers.
- **Highlights:** Professional structure, strong documentation, tests, CI/CD, reproducible data and reports.

## Quick Demo
![Demo GIF](docs/demo.gif) <!-- Replace with a real GIF -->

## Installation
```bash
pip install trainlytics
```

## Quickstart
```python
from trainlytics import ingest, clean, features, model, recommender
# See notebooks/ for complete examples
```

## Project Structure
- `src/trainlytics/`: Core package modules
- `notebooks/`: EDA, modeling, reporting
- `tests/`: Unit and integration tests
- `docs/`: Documentation, changelog, references
- `.github/workflows/`: CI/CD
- `data/`: Sample data

## Sample Data
- CSV format: `data/sample_workout_log.csv`
- Schema: `date,exercise,sets,reps,weight`
- Note: Example data only, for educational purposes.

## How to Use
1. Install dependencies: `pip install -r requirements.txt`
2. Activate the virtual environment: `source .venv/bin/activate` (Linux/Mac) or `.venv\Scripts\Activate.ps1` (Windows)
3. Run notebooks in `notebooks/` for full examples.
4. Run tests: `PYTHONPATH=src pytest tests` (Linux/Mac) or `$env:PYTHONPATH="$(Resolve-Path .\src)"; pytest tests` (Windows)

## Automation & Tasks
- CI/CD: Lint, test, build, and publish artifacts via GitHub Actions
- VS Code tasks: Lint, format, test (see `.vscode/tasks.json`)

## FAIR & Reproducibility
- Versioned data and code
- Notebooks with controlled outputs
- Metadata and citation in `CITATION.cff`

## Roadmap
- [x] Initial structure
- [ ] Ingestion and cleaning modules
- [ ] Modeling and recommendation
- [ ] Micro-app and reporting
- [ ] Tests and coverage

## How to Cite
See `CITATION.cff` for BibTeX/APA.

## How to Contribute
See `CONTRIBUTING.md` and open a PR!

## License
MIT
ros-foonathan-memory-vendor 1.3.1
A ROS package that vendors the Foonathan Memory library, enabling custom and efficient memory allocation.

Built using https://github.com/ycheng517/ros-python-wheels.

# Foonathan Memory Vendor

[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_linux/badge/icon?subject=%20%20%20Linux%20CI%20)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_linux/)
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[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_mac/badge/icon?subject=%20%20%20%20%20%20%20Mac%20CI%20)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_mac/)
[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=Win32,toolset=v141/badge/icon?subject=%20%20%20%20Windows%20CI%20-%20Win32-v141)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=Win32,toolset=v141)
[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=Win32,toolset=v142/badge/icon?subject=%20%20%20%20Windows%20CI%20-%20Win32-v142)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=Win32,toolset=v142)
[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=x64,toolset=v141/badge/icon?subject=%20%20%20%20Windows%20CI%20-%20x64-v141)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=x64,toolset=v141)
[![Build Status](http://jenkins.eprosima.com:8080/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=x64,toolset=v142/badge/icon?subject=%20%20%20%20Windows%20CI%20-%20x64-v142)](http://jenkins.eprosima.com:8080/view/Nightly%20Foonathan%20Memory/job/nightly_foonathan_memory_master_windows/label=windows-secure,platform=x64,toolset=v142)


Vendor package for [foonathan/memory](https://github.com/foonathan/memory).
This package will download, patch, build and install *foonathan/memory* for its use with Fast DDS.

## Quality Declaration

This package claims to be in the **Quality Level 2** category, see the [Quality Declaration](QUALITY_DECLARATION.md) for more details.