semvec/pypi-packages huggingface dataset:
datacatalog-storage 1.0.0
Catalog-based data storage system with pluggable serializers
Requires Python: >=3.8
Keywords: data, storage, serialization, catalog, numpy, scipy

# DataCat - Data Storage System

[![PyPI version](https://badge.fury.io/py/datacat.svg)](https://pypi.org/project/datacat/)
[![GitHub tag](https://img.shields.io/github/v/tag/papasaidfine/datacat?sort=semver)](https://github.com/papasaidfine/datacat/tags)

A data storage system with catalog storage and pluggable serializers.

## Features

- **CatalogStorage**: Manages DuckDB catalog with hashed file paths
- **Serializer Interface**: Pluggable serialization system
- **SparseMatrixSerializer**: Handles scipy sparse matrices and numpy arrays
- **NumpyArraySerializer**: Pure numpy arrays without pickle dependency

## Installation

```bash
pip install -r requirements.txt
```

## Usage

### With Sparse Matrices

```python
from datacat import CatalogStorage, SparseMatrixSerializer
import numpy as np
import scipy.sparse as sp

# Initialize with sparse matrix support
serializer = SparseMatrixSerializer()
storage = CatalogStorage(
    catalog_columns=['dim1', 'dim2', 'date'],
    serializer=serializer
)

# Save mixed data
data = {
    'returns': sp.csr_matrix([[1, 2, 0], [0, 0, 3]]),
    'stock_names': np.array(['AAPL', 'MSFT']),
    'weights': np.array([0.5, 0.5])
}
storage.save(data, dim1="v1", dim2="v2", date="2024-01-01")
```

### With Pure NumPy Arrays

```python
from datacat import CatalogStorage, NumpyArraySerializer
import numpy as np

# Initialize with numpy-only support (no pickle)
serializer = NumpyArraySerializer()
storage = CatalogStorage(
    catalog_columns=['experiment', 'model', 'date'],
    serializer=serializer
)

# Save pure numpy data
data = {
    'features': np.random.rand(100, 10).astype(np.float32),
    'labels': np.array(['class_A', 'class_B'] * 50),
    'timestamps': np.array(['2024-01-01', '2024-01-02'], dtype='datetime64[D]')
}
storage.save(data, experiment="classification", model="cnn", date="2024-01-01")
```
pxr-work-dev 25.8
C++ headers and CMake config for developing with pxr-work
Requires Python: >=3.8
Keywords: pixar, open-usd, dev

# Pixar Work

[![PyPi version](https://img.shields.io/pypi/v/pxr-work.svg?logo=pypi&label=PyPI&logoColor=gold)](https://pypi.python.org/pypi/pxr-work)
[![CMake](https://img.shields.io/badge/CMake-3.23...4.1-blue.svg?logo=CMake&logoColor=blue)](https://cmake.org)
[![Linux](https://github.com/untwine/pxr-work/actions/workflows/linux.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/linux.yml)
[![MacOs](https://github.com/untwine/pxr-work/actions/workflows/macos.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/macos.yml)
[![Windows](https://github.com/untwine/pxr-work/actions/workflows/windows.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/windows.yml)
[![License](https://img.shields.io/badge/License-TOST-yellow.svg)](https://github.com/untwine/pxr-work/blob/main/LICENSE.txt)

Multi-threaded dispatch library used in OpenUSD.

This repository is a decoupled version of the "work" library from the
[OpenUSD](https://graphics.pixar.com/usd/release/index.html) library, created
by Pixar.

It is regularly rebased over the "release" branch of the original
[repository](https://github.com/PixarAnimationStudios/OpenUSD) to provide
explicit divergence information from the latest updates and is currently
synchronized with
[v25.08](https://github.com/PixarAnimationStudios/OpenUSD/releases/tag/v25.08).
pxr-work 25.8
Multi-threaded dispatch library used in OpenUSD
Requires Python: >=3.8
Keywords: pixar, open-usd

# Pixar Work

[![PyPi version](https://img.shields.io/pypi/v/pxr-work.svg?logo=pypi&label=PyPI&logoColor=gold)](https://pypi.python.org/pypi/pxr-work)
[![CMake](https://img.shields.io/badge/CMake-3.23...4.1-blue.svg?logo=CMake&logoColor=blue)](https://cmake.org)
[![Linux](https://github.com/untwine/pxr-work/actions/workflows/linux.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/linux.yml)
[![MacOs](https://github.com/untwine/pxr-work/actions/workflows/macos.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/macos.yml)
[![Windows](https://github.com/untwine/pxr-work/actions/workflows/windows.yml/badge.svg?branch=main)](https://github.com/untwine/pxr-work/actions/workflows/windows.yml)
[![License](https://img.shields.io/badge/License-TOST-yellow.svg)](https://github.com/untwine/pxr-work/blob/main/LICENSE.txt)

Multi-threaded dispatch library used in OpenUSD.

This repository is a decoupled version of the "work" library from the
[OpenUSD](https://graphics.pixar.com/usd/release/index.html) library, created
by Pixar.

It is regularly rebased over the "release" branch of the original
[repository](https://github.com/PixarAnimationStudios/OpenUSD) to provide
explicit divergence information from the latest updates and is currently
synchronized with
[v25.08](https://github.com/PixarAnimationStudios/OpenUSD/releases/tag/v25.08).
sparx-ai 1.1.0
A lightweight collection of Generative AI code examples and utilities
Requires Python: >=3.7

# Sparx-AI

A Python library containing a collection of Generative AI code examples and utilities for learning and development.

## Installation

```bash
pip install sparx-ai
```

## Usage

### Basic Usage

```python
from sparx import show_code

# Display a specific code example
show_code('prac1.txt')
```

### List Available Examples

```python
from sparx import list_examples

# Show all available code examples
list_examples()
```

### Advanced Usage

```python
from sparx import show_code, get_file_description

# Show code without line numbers
show_code('prac2.txt', line_numbers=False)

# Get description of a file
description = get_file_description('prac1.txt')
print(description)
```

## Available Examples

The library includes the following code examples:

- `prac1.txt` - Basic Data Preprocessing for Generative AI
- `prac2.txt` - Visualizing Data Distributions for Generative AI
- `prac3.txt` - TensorFlow Computation Graph with Eager Execution
- `prac4.txt` - [Description automatically extracted]
- `prac5.txt` - GloVe Pre-trained Embeddings
- And more...

## Features

- 📁 Easy access to curated AI/ML code examples
- 🔍 Search and display specific examples
- 📝 Line-numbered code display
- 📚 List all available examples
- 🏷️ Get descriptions from code files

## Requirements

- Python 3.7+
- Dependencies: numpy, matplotlib, scikit-learn, tensorflow, torch, spacy, transformers, and more

## License

MIT License

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
kautolog 1.1.14
Kali/Linux auto-logging of all terminal sessions using script(1), with optional tmux, logrotate, and rclone sync.
Requires Python: >=3.8
Keywords: kali, linux, logging, terminal, script, tmux, logrotate, rclone

# kautolog

[![PyPI version](https://img.shields.io/pypi/v/kautolog.svg)](https://pypi.org/project/kautolog/)

Auto-log **everything you see** in every terminal tab on Kali/Linux using `script(1)`. Captures prompt, commands, output, ANSI colors, and ncurses apps with optional timing/replay, tmux per-pane logs, logrotate, and rclone cloud sync.

## Install

Recommended:

```bash
pipx install kautolog
kautolog install
```

This will:

- Hook into both `~/.bashrc` and `~/.zshrc` for Zsh and Bash auto-logging.
- Install kautolog-replay script into `~/.local/bin`.

### `kautolog install` Options

| Flag | Default | Description |
|------|---------|-------------|
| `--logdir PATH` | `~/terminal-logs` | Custom log output directory |
| `--with-tmux` | `False` | Add autologging to `~/.tmux.conf` |
| `--with-logrotate / --no-logrotate` | `True` | Install user-level logrotate config |
| `--with-sync remote:path` | *(none)* | Enable rclone sync (e.g. `gdrive:kautolog-logs`) |
| `--interval N` | `10` | Sync interval in minutes for systemd timer |

## Replaying logs

To replay a session with timing:

```bash
kautolog replay ~/terminal-logs/2025/08/10/kali-33608-203123
```

To instantly dump the log without delay:

```bash
kautolog replay -i ~/terminal-logs/2025/08/10/kali-33608-203123
```

### `kautolog replay` Options

| Flag / Arg | Description | Notes |
|------------|-------------|-------|
| `<log_base>` | Path to `.log` file or base name (no extension) | Required |
| `-i` | Instant dump (no timing) | Just prints the `.log` file |
| `-d <num>` | Speed divisor (multiplier) | `-d 2` = 2× faster, `-d 10` = 10× faster, `-d 0.5` = 2× slower |
| `-m <secs>`, `--maxdelay <secs>` | Maximum delay between lines | Clamps long pauses (e.g. `-m 0.1`) |
| `--target <secs>` | Normalize total replay to target duration | Auto-computes divisor; also sets `--maxdelay 0.12` if not provided |

## Log Format

Logs are saved to:

```bash
~/terminal-logs/YYYY/MM/DD/hostname-PID-TIMESTAMP.log
~/terminal-logs/YYYY/MM/DD/hostname-PID-TIMESTAMP.timing
```

If `--with-tmux` is used, each tmux pane logs independently.

## Enabling Automatic Log Cleanup (Optional)

By default, `kautolog install` places a logrotate config at:

```bash
~/.config/logrotate.d/terminal-logs
```

Most systems **do not run** logrotate from this location.  
To enable automatic log cleanup, copy it to the system logrotate directory:

```bash
sudo cp ~/.config/logrotate.d/terminal-logs /etc/logrotate.d/terminal-logs
```

This will:

- Rotate logs daily
- Keep 14 days of logs
- Compress old logs
- Prevent unlimited disk usage

## Uninstall

```bash
kautolog uninstall
```

Removes all shell hooks and scripts cleanly.

If you installed using pipx:

```bash
pipx uninstall kautolog
```

## License

The scripts and documentation in this project are released under the [MIT License](https://github.com/marksowell/kautolog/blob/main/LICENSE)
py-uds-address 2.0.0
Collection of UDS addresses for various ECUs.
Requires Python: >=3.9
Keywords: uds, unified-diagnostic-services, automotive, on-board-diagnostic, obd, obd2, vehicle-diagnostic, iso14229, iso-14229, iso15765, iso-15765, ECU, address

*************
UDS - ADDRESS
*************

|LatestVersion| |PythonVersions| |PyPIStatus| |TotalDownloads| |MonthlyDownloads| |Licence|

This is extension to `py-uds`_ package with addresses of ECUs.


ECU address
-----------
If you look for an address of a certain ECU, either search by spare part number and bus type in
`ecu section <https://github.com/mdabrowski1990/uds-address/tree/main/uds_address/ecu>`_
or by OEM, carline and production year and bus, e.g.
`Hyundai i20 2021, CAN bus accessible via OBD-2
<https://github.com/mdabrowski1990/uds-address/blob/main/uds_address/hyundai/i20/year_2021/can_obd2.py>`_.


How to add ECU?
---------------
If you know an address of some ECU (or a group of ECUs), please create
`an issue <https://github.com/mdabrowski1990/uds-address/issues/new?template=01_add_ecu.md>`_
and provide all the required details, so we could use this information as part of this package.


Documentation
-------------
This package contains only addresses of ECUs. For full user documentation about UDS go to: https://uds.readthedocs.io/


Contact
-------
- e-mail: uds-package-development@googlegroups.com
- group: `UDS package development`_
- discord: https://discord.gg/y3waVmR5PZ

If you want to become a contributor, please read `CONTRIBUTING.md`_ file.


.. _CONTRIBUTING.md: https://github.com/mdabrowski1990/uds-address/blob/main/CONTRIBUTING.md

.. _UDS package development: https://groups.google.com/g/uds-package-development/about

.. _py-uds: https://github.com/mdabrowski1990/uds


.. |LatestVersion| image:: https://img.shields.io/pypi/v/py-uds-address.svg
   :target: https://pypi.python.org/pypi/py-uds-address
   :alt: The latest Version of UDS package

.. |PythonVersions| image:: https://img.shields.io/pypi/pyversions/py-uds-address.svg
   :target: https://pypi.python.org/pypi/py-uds-address/
   :alt: Supported Python versions

.. |PyPIStatus| image:: https://img.shields.io/pypi/status/py-uds-address.svg
   :target: https://pypi.python.org/pypi/py-uds-address/
   :alt: PyPI status

.. |TotalDownloads| image:: https://pepy.tech/badge/py-uds-address
   :target: https://pepy.tech/project/py-uds-address
   :alt: Total PyPI downloads

.. |MonthlyDownloads| image:: https://pepy.tech/badge/py-uds-address/month
   :target: https://pepy.tech/project/py-uds-address
   :alt: Monthly PyPI downloads

.. |Licence| image:: https://img.shields.io/badge/License-MIT-blue.svg
   :target: https://lbesson.mit-license.org/
   :alt: License Type
forktex 0.1.3
Official Python library to interact with Forktex API
Requires Python: >=3.11


# Forktex Python CLI 🚀

[![PyPI version](https://img.shields.io/pypi/v/forktex.svg)](https://pypi.org/project/forktex/)
[![Python Versions](https://img.shields.io/pypi/pyversions/forktex.svg)](https://pypi.org/project/forktex/)

[![Publish](https://github.com/forktex/forktex-python/actions/workflows/publish.yml/badge.svg)](https://github.com/forktex/forktex-python/actions)

**Forktex** is the official Python CLI & SDK for interacting with the [Forktex API](https://forktex.com).  
It enables developers and teams to call AI models, manage cloud resources, and integrate Forktex services directly from the terminal or Python scripts.

---

## ✨ Features

- 🤖 **AI models** — call Forktex-hosted AI models with simple CLI commands  
- ☁️ **Cloud resource management** — create, manage, and monitor Forktex cloud resources  
- 🛠️ **Developer-friendly** — designed for automation, CI/CD, and scripting  
- 📦 **PyPI-ready** — install & upgrade via pip

---

## 📦 Installation

```bash
pip install forktex
```

Upgrade to the latest version anytime:

```bash
pip install --upgrade forktex
```

---

## 🚀 Quickstart (CLI)

After installation, the `forktex` CLI is available globally:

```bash
forktex --help
```

### Example: Call an AI model

```bash
forktex ai call --model ro-hero --prompt "Hello, world!"
```

### Example: Manage cloud resources

```bash
forktex cloud list
forktex cloud create --type vm --name test-vm
```

---

## ⚙️ Configuration

You’ll need an API key from the [Forktex Dashboard](https://forktex.com).

Set it as an environment variable:

```bash
export FORKTEX_API_KEY="your_api_key_here"
```

Or configure via CLI:

```bash
forktex config set api_key your_api_key_here
```

---

## 📖 Usage as a Python Library

You can also use Forktex as a Python SDK:

```python
from forktex import Client

client = Client(api_key="your_api_key")

# Call an AI model
result = client.ai.call(model="ro-hero", prompt="Hello world!")
print(result.output)

# List cloud resources
resources = client.cloud.list()
print(resources)
```

---


## 🤝 Contributing

Contributions are welcome!  
- Open issues and feature requests at [GitHub Issues](https://github.com/forktex/forktex-python/issues)  
- Submit PRs to improve the library and CLI  

---