semvec/pypi-packages huggingface dataset:
posty 2.1.1.post1
A static site generator
Requires Python: >=3.10

# Posty

[![Build Status](https://travis-ci.org/nickpegg/posty.svg?branch=release-2.0)](https://travis-ci.org/nickpegg/posty) [![Documentation Status](https://readthedocs.org/projects/posty/badge/?version=latest)](http://posty.readthedocs.io/en/latest/?badge=latest)

A simple static site generator tool. Reads in a series of posts and pages
containing YAML metadata and Markdown text, and renders them as HTML.

This is what powers [my personal website](https://nickpegg.com).

This was mostly written for fun. There are other, probably better and
definitely more full-featured static site generators out there.

## Super-Quickstart
```
$ posty init
$ vim pages/blah.yaml
$ vim posts/1970-01-01_my-post.yaml
$ posty build
# Then deploy to your web server
```

Go check out [the docs](http://posty.readthedocs.io/) for a more info.
django-osm-field 0.6.0
Django OpenStreetMap Field
Requires Python: >=3.9
Keywords: Django, Geo, Geoposition, OpenStreetMap, OSM

================
django-osm-field
================

.. image:: https://img.shields.io/github/actions/workflow/status/MarkusH/django-osm-field/main.yml.svg?branch=main&style=for-the-badge
   :target: https://github.com/MarkusH/django-osm-field/actions?workflow=CI

.. image:: https://img.shields.io/badge/Coverage-100%25-success?style=for-the-badge
  :target: https://github.com/MarkusH/django-osm-field/actions?workflow=CI

.. image:: https://img.shields.io/pypi/v/django-osm-field.svg?style=for-the-badge
   :target: https://pypi.org/project/django-osm-field/

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg?style=for-the-badge
   :target: https://github.com/psf/black

.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white&style=for-the-badge
   :target: https://github.com/pre-commit/pre-commit
   :alt: pre-commit

An OpenStreetMap field for Django.

----

Requirements
------------

Python 3.9 to 3.14 supported.

Django 4.2 to 6.0 supported.

Documentation: https://django-osm-field.readthedocs.io/
effect-form-validators 1.5.0
Form validation classes for the EFFECT trial
Requires Python: <3.14,>=3.12
Keywords: django, clinicedc, form validators, EFFECT EDC, EDC, clinical trials, META Trial, ISRCTN30579828

|pypi| |actions| |codecov| |downloads| |clinicedc|


effect-form-validators
----------------------

Form validator classes for `EFFECT Edc <https://github.com/effect-trial/effect-edc#readme>`_ model forms

.. |pypi| image:: https://img.shields.io/pypi/v/effect-form-validators.svg
   :target: https://pypi.python.org/pypi/effect-form-validators

.. |actions| image:: https://github.com/effect-trial/effect-form-validators/actions/workflows/build.yml/badge.svg
   :target: https://github.com/effect-trial/effect-form-validators/actions/workflows/build.yml

.. |codecov| image:: https://codecov.io/gh/effect-trial/effect-form-validators/branch/develop/graph/badge.svg
   :target: https://codecov.io/gh/effect-trial/effect-form-validators

.. |downloads| image:: https://pepy.tech/badge/effect-form-validators
   :target: https://pepy.tech/project/effect-form-validators

.. |clinicedc| image:: https://img.shields.io/badge/framework-Clinic_EDC-green
   :alt:Made with clinicedc
   :target: https://github.com/clinicedc
chroma-tui 0.1.1
A TUI for ChromaDB
Requires Python: >=3.8

# Chroma TUI

A terminal user interface (TUI) for browsing and managing ChromaDB instances.

## Features

- Browse collections and view document counts
- View complete documents with metadata and embeddings
- Create and delete collections
- Add documents to collections
- Search documents using semantic similarity
- Interactive and intuitive interface

## Installation

### From PyPI

```bash
pip install chroma-tui
```

### From Source

1. Clone this repository:
   ```bash
   git clone https://github.com/Mukhunyeledzi-Muthuphei/chromadb-tui.git
   cd chromadb-tui
   ```

2. Install the package:
   ```bash
   pip install -e .
   ```

## Usage

Run the TUI from your terminal:

```bash
chroma-tui
```

You'll be prompted to enter your ChromaDB server connection details (host and port). Once connected, you can:

- **View Collections**: Browse all collections and their document counts
- **Create Collection**: Add new collections to your database
- **Delete Collection**: Remove collections from your database
- **View Document**: Display complete document details including text, metadata, and optional embedding vectors
- **Search Documents**: Perform semantic similarity searches across documents
- **Add Document**: Insert new documents into collections

## Requirements

- Python 3.8+
- ChromaDB server instance (running separately)

## License

MIT License
lazyip 1.0.0
获取ip信息，支持ipv4和ipv6

# lazyip

#### 介绍
{**以下是 Gitee 平台说明，您可以替换此简介**
Gitee 是 OSCHINA 推出的基于 Git 的代码托管平台（同时支持 SVN）。专为开发者提供稳定、高效、安全的云端软件开发协作平台
无论是个人、团队、或是企业，都能够用 Gitee 实现代码托管、项目管理、协作开发。企业项目请看 [https://gitee.com/enterprises](https://gitee.com/enterprises)}

#### 软件架构
软件架构说明


#### 安装教程

1.  xxxx
2.  xxxx
3.  xxxx

#### 使用说明

1.  xxxx
2.  xxxx
3.  xxxx

#### 参与贡献

1.  Fork 本仓库
2.  新建 Feat_xxx 分支
3.  提交代码
4.  新建 Pull Request


#### 特技

1.  使用 Readme\_XXX.md 来支持不同的语言，例如 Readme\_en.md, Readme\_zh.md
2.  Gitee 官方博客 [blog.gitee.com](https://blog.gitee.com)
3.  你可以 [https://gitee.com/explore](https://gitee.com/explore) 这个地址来了解 Gitee 上的优秀开源项目
4.  [GVP](https://gitee.com/gvp) 全称是 Gitee 最有价值开源项目，是综合评定出的优秀开源项目
5.  Gitee 官方提供的使用手册 [https://gitee.com/help](https://gitee.com/help)
6.  Gitee 封面人物是一档用来展示 Gitee 会员风采的栏目 [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)
clinicedc-tests 1.1.0
Shared test config and utils for clinicedc projects and related apps
Requires Python: <3.14,>=3.12
Keywords: django, clinicedc, edc, clinical trials, research, data management, esource

|pypi| |downloads| |clinicedc|

.. |pypi| image:: https://img.shields.io/pypi/v/clinicedc-tests.svg
    :target: https://pypi.python.org/pypi/clinicedc-tests

.. |downloads| image:: https://pepy.tech/badge/clinicedc-tests
   :target: https://pepy.tech/project/clinicedc-tests

.. |clinicedc| image:: https://img.shields.io/badge/framework-Clinic_EDC-green
   :alt:Made with clinicedc
   :target: https://github.com/clinicedc
py-samsungtv 1.0.2
Async Samsung 2024+ TV control via the HTTPS JSON-RPC interface
Requires Python: >=3.11

# pysamsungtv

`pysamsungtv` is an async Python library that talks to Samsung TVs over HTTPS JSON-RPC.

## Why

Samsung, in their infinite wisdom, disabled ports 8001 and 8002. This breaks the existing Home Assistant integration/libraries for all 2024+ models. They still expose their JSON-RPC over port 1516/1515, but it is undocumented.

I got frustrated enough to do a clean-room implemenation of it here.

## Installation

```bash
# pypi
pip install pysamsungtv

# local dev
just install
```

The package depends on `aiohttp` for HTTP/1.1 TLS transport. TLS verification is disabled by default because Samsung panels present self-signed certificates; set `verify_ssl=True` when the certificate chain is trusted on your host.

## Usage

Check [tests](tests/integration/test_live_client.py) for example usage.

Every helper method corresponds to the JSON-RPC methods in the protocol notes (e.g. `get_tv_states`, `direct_channel_control`, `volume_up_down`, `remote_key_control`, `sound_mode_control`, etc). Each coroutine returns the parsed `result` body or raises a `SamsungTVError` subclass on transport/protocol failures. Custom RPCs can be issued with `SamsungTVClient.send_request()`.

The optional `on_update` callback is invoked sequentially after every response. It receives the RPC method name and the parsed payload, making it easy to wire into Home Assistant's entity update routines.

## Development

- Install and run `pre-commit` (`pip install pre-commit && pre-commit install`) to ensure `mypy` and `pytest` pass locally before committing.
- All code is typed and passes `mypy` using the configuration in `pyproject.toml`.
- Run the test suite with `pytest`. Unit tests use fully mocked transports.
- Integration tests require a real TV: set `SAMSUNG_TV_HOST` (plus optional `SAMSUNG_TV_PORT` and/or `SAMSUNG_TV_TOKEN`) and run `pytest -m integration`. If no token is supplied the first run will prompt for authorization and cache the returned token under `.pytest_cache/samsung_tv_token` for later runs.
- A `Justfile` is included for convenience: `just install`, `just install-tests`, `just test`, `just mypy`, etc.
- All command inputs are exposed as enums in `pysamsungtv.enums` (also re-exported at the package root) so you can rely on autocomplete/validation for things like `InputSource`, `PictureMode`, `SoundMode`, and `RemoteKey`.
- Convenience helpers such as `set_picture_mode`, `set_sound_mode`, `select_speaker`, `select_input_source`, `set_volume`, `mute()/unmute()`, and `art_mode_on()/art_mode_off()` call the corresponding `*_control` RPCs for you.
datascav-switch 1.1.0
Modules to convert different types of files using AI based validations and conversions.
Requires Python: >=3.12

# datascav-switch

[![Python](https://img.shields.io/badge/python-3.12%2B-blue.svg)](https://www.python.org/)
[![LangChain](https://img.shields.io/badge/langchain-ecosystem-blueviolet)](https://github.com/langchain-ai/langchain)
[![OpenAI](https://img.shields.io/badge/openai-required-important)](https://platform.openai.com/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

**datascav-switch** is a Python package for intelligent document format conversion, leveraging generative AI (OpenAI) and a scalable architecture. This project is part of a suite of tools for automation, data extraction, and transformation.

---

## Main Features

- PDF to Markdown conversion with layout preservation
- Support for multiple input formats (file, URL, base64, bytes)
- Parallel processing and dynamic logging
- Detailed token tracking
- Native integration with [LangChain](https://github.com/langchain-ai/langchain) and tracing via LangSmith

---

## Installation

```bash
pip install datascav-switch
```

> **Requirements:**
> - Python 3.12+
> - OpenAI API key (`OPENAI_API_KEY`)

---

## Quick Start

```python
from scav_switch.converters.pdf import ScavToMarkdown
scav = ScavToMarkdown(model='gpt-4.1', verbose=True)
markdown = scav.dig('/path/to/file.pdf')
print(markdown)
```

For complete examples and detailed documentation, see the [`docs/`](docs/) folder and the notebooks for each module.

---

## Documentation

- Detailed documentation and usage examples are available in each [`docs/`](docs/) subfolder, including notebooks such as [`docs/conveters/pdf/ScavToMarkdown/ScavToMarkdown.ipynb`](docs/conveters/pdf/ScavToMarkdown/ScavToMarkdown.ipynb).
- Also check the [official LangChain documentation](https://github.com/langchain-ai/langchain) for advanced integration.

---

## License

MIT
invcalc 0.1.2
A Python library for inventory management and electronic component validation
Requires Python: >=3.8

# invcalc

**invcalc** is a Python library for inventory management and electronic component validation. It includes tools to calculate EOQ, reorder points, stock turnover, and perform ABC analysis, along with validators for resistors, capacitors, and voltage ratings.

## Installation

Install via PyPI:

```bash
pip install invcalc