semvec/pypi-packages huggingface dataset:
datasette-endpoints 0.1
Plugin to add a /-/endpoints debug page listing all configured endpoints
Requires Python: >=3.10

# datasette-endpoints

[![PyPI](https://img.shields.io/pypi/v/datasette-endpoints.svg)](https://pypi.org/project/datasette-endpoints/)
[![Changelog](https://img.shields.io/github/v/release/datasette/datasette-endpoints?include_prereleases&label=changelog)](https://github.com/datasette/datasette-endpoints/releases)
[![Tests](https://github.com/datasette/datasette-endpoints/actions/workflows/test.yml/badge.svg)](https://github.com/datasette/datasette-endpoints/actions/workflows/test.yml)
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/datasette/datasette-endpoints/blob/main/LICENSE)

Plugin to add a /-/endpoints debug page listing all configured endpoints

## Installation

Install this plugin in the same environment as Datasette.
```bash
datasette install datasette-endpoints
```
## Usage

Once installed, this plugin adds two endpoints to your Datasette instance:

- `/-/endpoints.json` - JSON list of all registered endpoints
- `/-/endpoints` - HTML page showing all registered endpoints in a table

### JSON API

Visit `/-/endpoints.json` to get a JSON array of all registered routes:

```json
[
    {
        "path": "/-/plugins",
        "view": "JsonDataView",
        "pattern": "/-/plugins(\\.(?P<format>json))?$"
    },
    {
        "path": "/{database}/{table}",
        "view": "TableView",
        "pattern": "/(?P<database>[^\\/\\.]+)/(?P<table>[^\\/\\.]+)(\\.(?P<format>\\w+))?$"
    }
]
```

Each endpoint object includes:

- **path** - A simplified, human-readable URL path with `{name}` placeholders for URL parameters
- **view** - The name of the view class or function handling the route
- **pattern** - The raw regex pattern used for URL matching

### HTML page

Visit `/-/endpoints` to see a table of all registered endpoints with their paths, view names, and regex patterns. This includes both built-in Datasette routes and any routes added by plugins.

## Development

To set up this plugin locally, first checkout the code. You can confirm it is available like this:
```bash
cd datasette-endpoints
# Confirm the plugin is visible
uv run datasette plugins
```
To run the tests:
```bash
uv run pytest
```
JsonhPy 2.3
JSON for Humans in Python.
Requires Python: >=3.12

<img src="https://github.com/jsonh-org/Jsonh/blob/main/IconUpscaled.png?raw=true" width=180>

[![PyPI](https://img.shields.io/pypi/v/JsonhPy.svg)](https://pypi.python.org/pypi/JsonhPy)

**JSON for Humans.**

JSON is great. Until you miss that trailing comma... or want to use comments. What about multiline strings?
JSONH provides a much more elegant way to write JSON that's designed for humans rather than machines.

Since JSONH is compatible with JSON, any JSONH syntax can be represented with equivalent JSON.

## JsonhPy

JsonhPy is a parser implementation of [JSONH V1 & V2](https://github.com/jsonh-org/Jsonh) for Python 3.

## Example

```jsonh
{
    // use #, // or /**/ comments
    
    // quotes are optional
    keys: without quotes,

    // commas are optional
    isn\'t: {
        that: cool? # yes
    }

    // use multiline strings
    haiku: '''
        Let me die in spring
          beneath the cherry blossoms
            while the moon is full.
        '''
    
    // compatible with JSON5
    key: 0xDEADCAFE

    // or use JSON
    "old school": 1337
}
```

## Usage

Everything you need is contained within `JsonhReader`:

```py
from JsonhPy.JsonhPy import *

jsonh: str = """
{
    this is: awesome
}
"""
json: object = JsonhReader.parse_element_from_string(jsonh).value()
```
synqly 1.0.68
SDK for Synqly APIs
Requires Python: <4.0,>=3.7

# Synqly Python SDK

This repository contains the `SynqlyPythonClient` SDK package, which can be used to integrate a Python application with Synqly APIs. All Synqly SDKs require a valid Synqly Organization token to use.

If you aren't yet a Synqly customer, please feel free to [Schedule a Demo](https://synqly.com/demo/).

The Python Pydantic type checker can, in cases, be stricter than other SDKs. If you run into any type resolution errors such as the following, please report them on Slack and we'll work on patching it as quickly as possible.

```
Error configuring event logging for Tenant XYZ: 1 validation error for ProviderConfig_Siem
config
  none is not an allowed value (type=type_error.none.not_allowed)
```

# Import the SDK

To install the `SynqlyPythonClient` to your local Python environment, run the following command:

```bash
pip3 install git+https://github.com/Synqly/python-sdk.git
```


You should now be able to import packages from the `SynqlyPythonClient` as follows:

```python
from synqly import engine
from synqly import management as mgmt
```

For more detailed examples of how to use the Synqly Python SDK, please refer to the `examples` directory in this repository. Each sub-directory in `examples` contains a standalone example of how to work with a particular Synqly Connector.

# Local Development

While the files under `/src` are auto-generated, it can sometimes be useful to install a local copy of the SDK in order to debug issues such as type mismatches. The following command will install the local version of `SynqlyPythonClient`, overriding the upstream repository. 

```bash
cd ~/python-sdk

pip install -e .
```
writing-machine 0.0.2
A Machine that writes texts.
Requires Python: >=3.10
Keywords: writing-machine

# Writing Machine
A Machine that writes texts.
```bash
  echo '[{"role": "user", "content": "Write an explanatory text..."}]' \
    | uvx writing-machine \
        --provider-api-key=sk-ant-api... \
        --github-token=ghp_... \
        --mode=single
```
Or:
```bash
  pip install writing-machine
```
Then:
```Python
  # Python
  import writing_machine
```
primfunctions 0.1.79
Prim AI Functions
Requires Python: >=3.10

# prim-ai-functions

A comprehensive SDK for interacting with the Prim AI Functions.

## Table of Contents
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Development Setup](#development-setup)

## Prerequisites

- Python 3.12+
- [uv](https://docs.astral.sh/uv/)

If you do not have a uv virtual environment, you can create one with:
```bash
uv venv --python 3.12
```

**Note:** We recommend using uv to install the package due to the incredible speed of the package manager. The package can still be installed via pip directly, but it will be slower.

## Installation

### From PyPI

```bash
pip install primfunctions
```

### From Source

```bash
uv pip install .
```

## Development Setup

### Git Hooks
This project includes git hooks to ensure code quality. To set up the git hooks:

```bash
python setup_hooks.py
```

This will create a pre-commit hook that automatically runs black on Python files before each commit.
nexaai 1.0.45rc1
Run next-generation LLMs and VLMs locally, natively, and at top speed on any hardware.

# nexaai

> **Run next-generation LLMs and VLMs locally, natively, and at top speed on any hardware.**

**nexaai** is the official Python SDK for NexaSDK/NexaML:  
An NPU‑first cross‑platform inference engine that powers LLMs, VLMs, embeddings, audio, and vision models across NPU, GPU, and CPU—on desktop, mobile, automotive, and IoT.

---

## Features

- 🚀 **NPU‑First Performance** — Accelerated AI with automatic device selection and backend optimizations.
- 🔮 **Day‑0 Architecture Support** — Run new LLMs, VLMs, ASR, and CV models immediately (GGUF, MLX, .nexa, and more).
- 🧩 **True Multimodality** — Seamless pipelines for text, vision, and audio.
- 🤖 **OpenAI-Compatible Server** — Supports serving, chat, and function calling.
- 🏆 **Cross‑Platform** — macOS (Apple Silicon), Windows (x64, ARM64), Linux, mobile, embedded.

---

## What is it?

nexaai offers a clean Python API over NexaML’s runtime. Build modern AI applications—chatbots, copilots, vision tools—that run fully **on-device** with maximal hardware utilization. Designed for rapid adoption of new models and formats, especially with NPU acceleration.

---

## Installation & Quickstart

Please refer to our official docs for up-to-date install steps, environment notes, and code examples:

- **Overview:** [NexaAI Python SDK Overview](https://docs.nexa.ai/nexa-sdk-python/overview)
- **Quickstart:** [Quickstart Guide](https://docs.nexa.ai/nexa-sdk-python/quickstart)

The docs include supported Python versions, backend requirements (NPU, MLX, GPU, CPU), and ready-to-run examples for LLMs, VLMs, embeddings, and audio.

---

## Links

- 📚 **Docs:** https://docs.nexa.ai/nexa-sdk-python/overview
- 🐞 **Issues/Discussions:** [NexaAI Issues](https://github.com/NexaAI/nexa-sdk/issues)
- 💬 **Community:**
  - [Discord](https://discord.com/invite/nexa-ai)
  - [Slack](https://nexa-ai-community.slack.com/ssb/redirect)

---