semvec/pypi-packages huggingface dataset:
teda-temporal 0.1.0
Temporal EDA for feature drift, PCA, breakpoints, and trends
Requires Python: >=3.8

# TEDA - Temporal Exploratory Data Analysis

A Python package for temporal feature analysis and drift detection.

## Features

### 1. **Feature Overview Table**
- Comprehensive statistics for all features
- Missing values, zero rates, unique percentages
- Volatility and PSI (Population Stability Index) tracking
- Correlation with target variable

### 2. **Monthly PSI Tracking**
- Track Population Stability Index over time
- Automatic threshold warnings

### 3. **3D PCA Visualization**
- Monthly mean projection in PCA space
- Travel distance bar chart showing monthly movement

### 4. **Structural Breakpoint Detection**
- Uses Ruptures library for changepoint detection
- Monthly aggregation with PELT/Binseg/Dynp algorithms
- Visual breakpoint markers on time series

### 5. **Feature Importance Evolution**
- Track feature importance over time
- Multiple models: RandomForest & XGBoost

### 6. **HP Filter Decomposition**
- Hodrick-Prescott filter for trend extraction
- Seasonal pattern detection
- Residual analysis

## Installation

```bash
pip install teda
```

Or install from source:
```bash
git clone https://github.com/tergelitu/teda.git
cd teda
pip install -e .
```

## Requirements

- Python 3.8+
- pandas >= 1.3.0
- numpy >= 1.21.0
- plotly >= 5.0.0
- scikit-learn >= 1.0.0
- xgboost >= 1.5.0
- ruptures >= 1.1.0
- statsmodels >= 0.13.0
- ipywidgets >= 7.6.0

## 📖 Quick Start

**See full example usage in [teda-demo.ipynb](teda-demo.ipynb)**

```python
import pandas as pd
import teda as te

# Load your data
df = pd.read_csv('your_data.csv')

# 1. Feature Overview
te.overview_table(df, date_col='date', target_col='target', exclude_cols=['id'])

# 2. PSI Tracking
te.plot_monthly_psi(df, date_col='date', feature_col='col')

# 3. 3D PCA Visualization
te.plot_monthly_pca(df, date_col='date', exclude_cols=['id', 'target'])

# 4. Structural Breakpoints
te.detect_change_points(df, date_col='date', feature_col='col', model='l2')

# 5. Feature Importance Evolution
te.plot_monthly_importance(df, date_col='date', target_col='target', feature_name='col')

# 6. HP Filter Decomposition
te.plot_hp_decomposition(df, date_col='date', feature_col='col')
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Author

**Tergel Munkhbaatar**
- GitHub: [@tergelitu](https://github.com/tergelitu)

## Use Cases

- **Model Monitoring**: Track feature drift in production ML systems
- **Data Quality**: Identify distribution shifts and anomalies
- **Feature Engineering**: Understand temporal patterns and breakpoints
- **Exploratory Analysis**: Quick overview of time-series feature behavior

---

**Star ⭐ this repo if you find it useful!**
pilot-platform-common 0.9.0
Centralize cross-service functionality shared across all Pilot Platform services.
Requires Python: <3.11,>=3.10

# common

[![Run Tests](https://github.com/PilotDataPlatform/pilot-hdc-common/actions/workflows/run-tests.yml/badge.svg?branch=main)](https://github.com/PilotDataPlatform/pilot-hdc-common/actions/workflows/run-tests.yml)
[![Python](https://img.shields.io/badge/python-3.10-brightgreen.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/pypi/v/pilot-platform-common.svg)](https://pypi.org/project/pilot-platform-common/)

Importable package responsible for cross-service tasks within the Pilot Platform.


## Getting Started

### Installation & Quick Start
The latest version of the common package is available on [PyPi](https://pypi.org/project/pilot-platform-common/) and can be installed into another service via Pip.

Pip install from PyPi:
```
pip install pilot-platform-common
```

In `pyproject.toml`:
```
pilot-platform-common = "^<VERSION>"
```

Pip install from a local `.whl` file:
```
pip install pilot_platform_common-<VERSION>-py3-none-any.whl
```

## Contribution

You can contribute the project in following ways:

* Report a bug.
* Suggest a feature.
* Open a pull request for fixing issues or adding functionality. Please consider using [pre-commit](https://pre-commit.com) in this case.
* For general guidelines on how to contribute to the project, please take a look at the [contribution guide](CONTRIBUTING.md).
aiosend 3.0.5
sync & async Crypto Pay API client.
Requires Python: >=3.10
Keywords: Crypto Bot, Crypto Pay API, CryptoBot, CryptoPayAPI, crypto pay, crypto pay api, cryptobot, cryptopayapi

<p align="center"> <!-- markdownlint-disable MD033 MD041 MD045 MD013-->
  <img src="https://raw.githubusercontent.com/vovchic17/static/refs/heads/main/src/aiosend.png" align="center"/>
  <h1 align="center">aiosend</h1>
</p>

[![Python](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/vovchic17/static/main/src/badges/python310_314.json)](https://www.python.org/)
[![Crypto Pay API](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/vovchic17/static/refs/heads/main/src/badges/cryptopayapi1.5.1.json)](https://help.crypt.bot/crypto-pay-api)
[![Documentation Status](https://readthedocs.org/projects/aiosend/badge/?version=latest)](https://aiosend.readthedocs.io/en/latest/?badge=latest)
[![Pydantic v2](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json)](https://pydantic.dev)
[![Aiohttp](https://img.shields.io/badge/aiohttp-v3-2c5bb4?logo=aiohttp)](https://docs.aiohttp.org/en/stable/)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Code linter: ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/charliermarsh/ruff)
[![Checked with mypy](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/vovchic17/static/main/src/badges/mypy.json)](https://mypy-lang.org/)

**aiosend** is a synchronous & asynchronous [Crypto Pay API](https://help.crypt.bot/crypto-pay-api) client.

> ## [Official documentation](https://aiosend.readthedocs.io/en/latest/)
>
> ## [<img src="https://raw.githubusercontent.com/vovchic17/static/refs/heads/main/src/telegram_logo.svg" width="30" align="top">  Telegram chat](https://aiosend.t.me/)

## Quick start

```python
import asyncio
from aiosend import CryptoPay


async def main():
    cp = CryptoPay(token="TOKEN")
    app = await cp.get_me()
    print(app.name)  # Your App's Name


if __name__ == "__main__":
    asyncio.run(main())
```

## aiogram 3.x integration example

```python
import asyncio
from aiogram import Bot, Dispatcher
from aiosend import CryptoPay

cp = CryptoPay("TOKEN")
bot = Bot("TOKEN")
dp = Dispatcher()


@dp.message()
async def get_invoice(message):
    invoice = await cp.create_invoice(1, "USDT")
    await message.answer(f"pay: {invoice.bot_invoice_url}")
    invoice.poll(message=message)


@cp.invoice_paid()
async def handle_payment(invoice, message):
    await message.answer(f"invoice #{invoice.invoice_id} has been paid")


async def main():
    await asyncio.gather(
        dp.start_polling(bot),
        cp.start_polling(),
    )


if __name__ == "__main__":
    asyncio.run(main())
```
microservice-chassis-grupo2-cc-prod 3.0.0
A reusable library for microservices
Requires Python: >=3.10

# 🧩 Microservice Chassis Grupo 2

**Repository link:** https://github.com/Grupo-MACC/Chassis

---

## Functionalities

This repository provides a **shared chassis** for microservices, containing configuration, database management, authentication, messaging, and helper utilities.  
It allows microservices to reuse common functionalities such as database connections, JWT validation, RabbitMQ communication, and standardized base models.

Below is a detailed list of the available functionalities:

| **Module** | **Functionality** | **Description** |
|-------------|------------------|-----------------|
| `core/config.py` | **Settings Management** | Centralized configuration for the chassis. Defines constants like the encryption algorithm (`RS256`), RabbitMQ connection parameters (`RABBITMQ_HOST`), and exchange name (`broker`). |
| `core/security.py` | **Token Decoding and Verification** | Handles JWT decoding using a public RSA key. Validates tokens and raises appropriate HTTP errors if invalid or missing. |
| `core/dependencies.py` | **Database Session & Authentication Dependency** | Provides FastAPI dependencies to manage asynchronous database sessions (`get_db`) and current user retrieval (`get_current_user`) from a JWT token. |
| `core/rabbitmq.py` | **RabbitMQ Channel & Exchange Management** | Creates asynchronous connections to RabbitMQ using `aio_pika`. Declares durable topic exchanges for inter-service communication. |
| `core/utils.py` | **Helper Functions and Service URLs** | Defines service URLs (order, machine, delivery, payment, auth) and provides error handling utilities with standardized logging (`raise_and_log_error`). |
| `sql/database.py` | **Database Engine & Session Configuration** | Configures SQLAlchemy’s asynchronous engine and sessionmaker. Supports `SQLALCHEMY_DATABASE_URL` via environment variable (defaults to SQLite). |
| `sql/base_class.py` | **Base Model for ORM Classes** | Provides a reusable abstract base class (`BaseModel`) for all database models, including timestamp columns (`creation_date`, `update_date`) and helper methods for converting models to dictionaries. |

---

## Functionalities per Microservice

| **Microservice** | **Used Functionalities** |
|------------------|--------------------------|
| `payment` | `core/config`, `core/security`, `core/dependencies`, `core/rabbitmq`, `core/utils`, `sql/database`, `sql/base_class` |

---

## Summary

This chassis allows the `payment` microservice (and potentially others in the future) to operate with consistent patterns for:
- Secure token validation.
- Standardized database access and sessions.
- Centralized configuration.
- RabbitMQ-based inter-service communication.
- Common helper utilities and error management.
- Unified base ORM models.

It provides a robust foundation for building scalable and maintainable microservices within the system.