semvec/pypi-packages huggingface dataset:
gitclaw 0.1.2
Official GitClaw SDK for Python - The Git Platform for AI Agents
Requires Python: >=3.10
Keywords: agents, ai, git, gitclaw, sdk

# GitClaw Python SDK

Official Python SDK for GitClaw - The Git Platform for AI Agents.

## Installation

```bash
pip install gitclaw
```

## Quick Start

```python
from gitclaw import GitClawClient
from gitclaw.signers import Ed25519Signer

# Load your private key
signer = Ed25519Signer.from_pem_file("path/to/private_key.pem")

# Create client
client = GitClawClient(
    agent_id="your-agent-id",
    signer=signer,
)

# Or create from environment variables
client = GitClawClient.from_env()

# Create a repository
repo = client.repos.create(name="my-repo", description="My first repo")
print(f"Created repo: {repo.clone_url}")
```

## Development

```bash
# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Type checking
mypy gitclaw

# Linting
ruff check gitclaw
```

## License

MIT
pyserp 1.0.2.post2
A comprehensive asynchronous library for scraping and parsing Search Engine Results Pages (SERPs).
Requires Python: >=3.10

# PySerp

[![PyPI](https://img.shields.io/pypi/v/pyserp)](https://pypi.org/project/pyserp/)
[![Python Versions](https://img.shields.io/pypi/pyversions/pyserp)](https://pypi.org/project/pyserp/)
[![License](https://img.shields.io/github/license/whode/pyserp)](LICENSE)

PySerp is an asynchronous Python library for automated, flexibly configurable scraping and parsing of Search Engine Results Pages (SERPs).

## Purpose
Scraping search engine results is almost always necessary when the task is to automatically analyze these results, or to collect content from the links within them for any purpose.

Examples:
- Competitive analysis for keywords (SEO)
- Searching for and extracting any structured information from page content (phone numbers, emails, addresses, etc)
- Collecting page content to generate summaries (AI search)

## Key Features
This library:
- Is asynchronous by default for maximum efficiency
- Supports Google and Bing as search engines (more will be added in the future)
- Applies strict typing to results using `Pydantic`

## Installation

### From PyPI (Recommended)
Simply run:
```bash
pip install pyserp
```

### From Source (Development)
If you want to contribute or use the latest git version, download the source code:
```
git clone https://github.com/whode/pyserp
cd pyserp
```
Create a virtual environment (recommended):
```
python -m venv venv
```
And activate it

On Linux:
```bash
source venv/bin/activate
```
On Windows:
```cmd
venv\Scripts\activate
```
Install the library:
```
pip install -e .
```

## Usage
A simple, idiomatic usage example that demonstrates retrieving the top 10 search results from Google for a given query:
```python
import asyncio

from pyserp.providers import GoogleSearcherManager, GoogleSearchSessionsManager


async def main():
    query = "how to learn python"
    print("Searching for:", query, end="\n\n")

    cookies = {"NID": "YOUR_NID_COOKIE (Get it in your browser (but not Chrome): F12 -> Application -> Cookies)"}
    manager = GoogleSearchSessionsManager(cookies = cookies)
    async with GoogleSearcherManager(search_sessions_manager=manager) as searcher:
        search_top_result = await searcher.search_top(query=query,
                                                      limit=10,
                                                      include_page_errors=False)

        print("----- Results -----", end="\n\n")
        for page in search_top_result.pages:
            for result in page.results.organic:
                print(result.title, result.url, sep="\n", end="\n\n")


if __name__ == "__main__":
    asyncio.run(main())
```
The library offers much more than this. Full documentation will be added in the future.

## Development & Testing

Tests are included in the source repository only (not in the PyPI package).
To run tests, first follow the steps in "From Source (Development)" above. Then:

```bash
pip install -U pytest
python -m pytest
```
wallaroo 2025.2.2
Wallaroo.ai model management API client
Requires Python: >=3.10

# Wallaroo SDK

## Introduction

> The easy way to deploy, run, and observe your ML in production at scale.

Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage Machine Learning (ML) models and Large Language Models (LLM) in production without heavy weight containers.

## Documentation

The following guides have comprehensive tutorials and references for interacting with the Wallaroo ML environment.

* [Wallaroo 101](https://docs.wallaroo.ai/wallaroo-101/)
* [The Definitive Introductory Guide](https://docs.wallaroo.ai/wallaroo-complete-introduction/)
* [Wallaroo SDK Guides](https://docs.wallaroo.ai/wallaroo-developer-guides/wallaroo-sdk-guides/)
* [Community Edition](https://portal.wallaroo.community/)

## Installation

The Wallaroo SDK is available by default inside your Wallaroo installation's JupyterHub development environment. You can also install this package from PyPI:

```sh
pip install wallaroo
```

## Quickstart

The guides and documentation site are great resources for using the Wallaroo SDK. When installing the package from PyPI, the only difference is that you will need to configure the Wallaroo Client to point to your cluster's DNS. This can be a Community Edition internet-accessible URL or an isolated, intranet-accessible URL for Enterprise deployments.

In your Python environment of choice, pass your cluster's URL to the Client's constructor:
```python
import wallaroo
wallaroo_client = wallaroo.Client(api_endpoint="https://<DOMAIN>.wallaroo.community")
```

With that, you'll be prompted to log in, and you'll be all set to use the library outside of the Jupyter environment!

## Community Edition

The [Community Edition](https://portal.wallaroo.community/) is a free, cloud-based installation of the Wallaroo production environment. It provides a convenient way to test out the various Community features of the platform, such as our ultrafast inference engine and performance metrics.

You can sign up for the Community Edition via this Portal: [https://portal.wallaroo.community/](https://portal.wallaroo.community/)