semvec/pypi-packages huggingface dataset:
pytest-testkit 0.1.8
A collection of convenient testing utilities for Python
Requires Python: >=3.10
Keywords: fixtures, json, mocking, pytest, sql, testing

# pytools

A collection of Python testing utilities.

## Installation

```bash
pip install pytest-testkit
```

## Modules

| Module | Description | Docs |
|--------|-------------|------|
| [sql](docs/sql.md) | Execute SQL files before/after tests | [docs/sql.md](docs/sql.md) |
| [read](docs/read.md) | Inject JSON fixtures into test functions | [docs/read.md](docs/read.md) |
| [http](docs/http.md) | Record and replay HTTP calls | [docs/http.md](docs/http.md) |
| [JsonAssert](docs/json_assert.md) | Compare objects to JSON files | [docs/json_assert.md](docs/json_assert.md) |
| [ObjectMapper](docs/object_mapper.md) | Bidirectional object-JSON mapping | [docs/object_mapper.md](docs/object_mapper.md) |

## Quick examples

### sql

```python
from pytools import sql, Phase

@sql(path="./setup.sql")
@sql(path="./cleanup.sql", phase=Phase.AFTER)
def test_database():
    # SQL executed before and after test
    pass
```

### read

```python
from pytools import read

@read.fixture(path="./fixtures/user.json", fixture_name="user", object_class=User)
def test_user(user: User):
    assert user.name == "John"
```

### http

```python
from pytools import http

@http(path="./fixtures/api.json")
def test_api():
    # First run: records HTTP calls
    # Next runs: replays from file
    response = requests.get("https://api.example.com/users")
    assert response.status_code == 200
```

### JsonAssert

```python
from pytools import JsonAssert

def test_response():
    data = {"name": "John", "age": 30}
    JsonAssert(data).ignore("age").compare_to_file("./expected.json")
```

### ObjectMapper

```python
from pytools import ObjectMapper

# Object to JSON
user = User(name="John", age=30)
data = ObjectMapper(user).to_json()

# JSON to object
data = {"name": "John", "age": 30}
user = ObjectMapper(data).to_object(User)
```

## Public API

```python
from pytools import (
    # Decorators
    sql,
    read,
    http,
    # Enums
    Phase,
    # Config
    SqlTestConfig,
    HttpTestConfig,
    # Classes
    JsonAssert,
    ObjectMapper,
)
```
clear-skies-cortex 2.0.8
Cortex module for Clearskies
Requires Python: <4.0,>=3.11


# cortex


Cortex module for Clearskies

This template scaffolds a dynamic Clearskies module for any kind of logic, integration, or API. You can use it to build modules for data processing, service integration, automation, or any custom business logic.

Your module can implement any logic you need: fetch data, process input, interact with external services, or perform custom actions. The endpoints and payloads are up to you.

## Installation

```bash
# Install uv if not already installed
pip install uv

# Create a virtual environment and install dependencies
uv sync
```

## Development

To set up your development environment with pre-commit hooks:

```bash
# Install uv if not already installed
pip install uv

# Create a virtual environment and install all dependencies (including dev)
uv sync

# Install dev dependencies (including ruff, black, mypy) in the project environment
uv pip install .[dev]

# Install pre-commit hooks
uv run pre-commit install

# Optionally, run pre-commit on all files
uv run pre-commit run --all-files
```

## Usage Example

```python
import clearskies
import clearskies_cortex

wsgi = clearskies.contexts.WsgiRef(
    clearskies_cortex.build__module()
)
wsgi()
```
zetaalpha.rag-agents 0.0.13
The Agents SDK is designed to provide a flexible, scalable, and efficient framework for building, testing, and deploying LLM agents.
Requires Python: >=3.12

<p align="center">
  <a href="https://zeta-alpha.com">
    <source media="(prefers-color-scheme: dark)" srcset="https://search.zeta-alpha.com/assets/img/zeta-logo-full-white.svg">
    <source media="(prefers-color-scheme: light)" srcset="https://search.zeta-alpha.com/assets/img/zeta-logo-full-black.svg">
    <img src="https://search.zeta-alpha.com/assets/img/zeta-logo-full-black.svg" alt="Zeta Alpha">
  </a>
</p>
<p align="center">
  <b>Build Intelligence and Drive Results</b>
</p>
<p align="center">
  <em>Advanced AI solutions for the enterprise</em>
</p>

The Agents SDK is designed to provide a flexible, scalable, and efficient framework for building, testing, and deploying LLM agents.

# Quick Start

Create your first conversational AI agent.

```bash
# Install the package
pip install zetaalpha.rag-agents

# Initialize a new project
rag_agents init

# Start the development UI
rag_agents dev
```

https://github.com/user-attachments/assets/2d0b86f8-2d1e-4131-8de9-9d3d1909b631

For more detailed information and resources, check out the following:

- [Tutorials](https://docs.zeta-alpha.com/gen-ai/customize/getting-started): Step-by-step tutorials to guide you through specific tasks and help you get started quickly.
- [Guides](https://docs.zeta-alpha.com/gen-ai/customize/guides): Practical how-to guides that provide solutions to common problems and use cases.
- [Advance Topics](https://docs.zeta-alpha.com/gen-ai/customize/advanced): In-depth explanations of concepts, features, and the underlying technology to help you understand how things work.
- [Reference](https://docs.zeta-alpha.com/gen-ai/customize/reference): Detailed reference material, including API documentation, configuration options, and command-line tools.
files-collections 1.0.0
Read a collection of files using information from their names
Requires Python: >=3.8

# Files Collections

[![Linting](https://github.com/robin-cls/fcollections/actions/workflows/pre-commit.yaml/badge.svg)](https://github.com/robin-cls/fcollections/actions/workflows/pre-commit.yaml)
[![Tests](https://github.com/robin-cls/fcollections/actions/workflows/tests.yaml/badge.svg)](https://github.com/robin-cls/fcollections/actions/workflows/tests.yaml)
[![Documentation](https://github.com/robin-cls/fcollections/actions/workflows/doc.yaml/badge.svg)](https://github.com/robin-cls/fcollections/actions/workflows/doc.yaml)
![License](https://img.shields.io/github/license/robin-cls/fcollections)


Select and read a collection of files

- Information contained in files and folders names are used to create basic
  selection filters
- Both local and remote file systems (FTP, S3, ...) can be explored
- Multiple implementations for handling different products and their specificities
- Easy building of an implementation for a new product


## Quick start

```bash
conda install files_collections
```

```python
from fcollections.implementations import NetcdfFilesDatabaseSwotLRL3
fc = NetcdfFilesDatabaseSwotLRL3("data")
fc.query(cycle_number=1, pass_number=1)
```

## Documentation

📘 **Full documentation:**
https://robin-cls.github.io/fcollections/index.html#

Key pages:
- [Getting started](https://robin-cls.github.io/fcollections/getting_started.html)
- [Installation](https://robin-cls.github.io/fcollections/install.html)
- [Catalog](https://robin-cls.github.io/fcollections/implementations/catalog.html)
- [Changelog](https://robin-cls.github.io/fcollections/changelog.html)

## Project status

⚠️ This project is still subject to breaking changes. Versioning will reflects
the breaking changes using SemVer convention

## License

Apache 2.0 — see [LICENSE](LICENSE)