semvec/pypi-packages huggingface dataset:
strawberry-openapi 0.2.1
Easily convert your Strawberry GraphQL schema to OpenAPI
License: MIT
Requires Python: >=3.8

<img src=".github/logo.png" width="124" />

# Strawberry OpenAPI

## 🍓 Introduction

Strawberry OpenAPI is a dynamic library that bridges the gap between GraphQL and
REST APIs. Leveraging Strawberry GraphQL, this library allows developers to
create REST APIs compliant with OpenAPI specifications using GraphQL operations
and schemas. Ideal for Python developers looking to combine the best of both
GraphQL and REST worlds.

## 🚀 Features

- **GraphQL to REST**: Easily convert GraphQL operations to RESTful endpoints.
- **OpenAPI Compliance**: Generates OpenAPI specs for your REST API, ensuring
  standardization and interoperability.
- **Strawberry Integration**: Seamlessly integrates with existing Strawberry
  GraphQL schemas.
- **Customizable**: Flexible enough to suit various project needs.
- **Supports multiple frameworks**: Supports Django, FastAPI, and more!

## 🔧 Installation

```bash
pip install strawberry-openapi
```

## 🛠️ Usage

### Basic Setup

```python
from strawberry_openapi import StrawberryOpenAPI

# Create your Strawberry GraphQL schema
schema = ...

# Initialize Strawberry OpenAPI
openapi = StrawberryOpenAPI(schema, operations="./operations/**/*.graphql")


app = openapi.as_django()
```

## 📚 Documentation

For more in-depth documentation, please visit our [official documentation](#).

## 🤝 Contributing

Contributions are welcome! Please read our [Contributing Guidelines](#) for more
information.

## 📄 License

This project is licensed under the [MIT License](#).

---

Feel free to fork, star, and contribute! Let's make API development easier and
more efficient together! 🌟🚀🍓
yelp-scraper-api 1.0.0
Yelp Scraper for hassle-free public Yelp data collection, including search results, comments, profiles, posts, and more.
License: MIT
Requires Python: >=3.6
Keywords: yelp-scraper,Yelp-scraper,yelp-web-scraper,web-scraper-api,scraping-yelp,yelp-data,

# Yelp Scraper
[![Oxylabs promo code](https://user-images.githubusercontent.com/129506779/250792357-8289e25e-9c36-4dc0-a5e2-2706db797bb5.png)](https://oxylabs.go2cloud.org/aff_c?offer_id=7&aff_id=877&url_id=112)


[<u>Yelp Scraper</u>](https://oxylabs.io/products/scraper-api/web/yelp)
enables you to scrape public Yelp data with ease and on any scale. This
guide will show you how to scrape Yelp using Oxylabs’ [<u>Scraper
API</u>](https://oxylabs.io/products/scraper-api).

## How it works

You can extract data from Yelp by sending a request to our API. The
service will send back the HTML of any Yelp page you want to scrape.

### Python code example

This Python code sends a request to the API and retrieves the HTML of
the Yelp search results for the best burgers near Frankfurt am Main,
Hessen:

```python
import requests
from pprint import pprint

# Structure payload.
payload = {
    'source': 'universal_ecommerce',
    'url': 'https://www.yelp.co.uk/search?find_desc=Burgers&find_loc=Frankfurt,%20Hessen,%20Germany'
}

# Get response.
response = requests.request(
    'POST',
    'https://realtime.oxylabs.io/v1/queries',
    auth=('USERNAME', 'PASSWORD'),  # Your credentials go here
    json=payload
)

# Instead of response with job status and results URL, this will return the
# JSON response with results.
pprint(response.json())
```

Head to the
[<u>documentation</u>](https://developers.oxylabs.io/scraper-apis/web-scraper-api)
for information regarding payload parameters.

### Output sample
```json
{
    "results": [
        {
            "content": "<!doctype html>
<html lang="en">
<head>
            ... 
            </script></body>
</html>
",
            "created_at": "2023-06-06 13:24:56",
            "updated_at": "2023-06-06 13:25:01",
            "page": 1,
            "url": "https://www.yelp.co.uk/search?find_desc=Burgers&find_loc=Frankfurt,%20Hessen,%20Germany",
            "job_id": "7071839378003205121",
            "status_code": 200
        }
    ]
}
```
With Oxylabs’ Yelp Scraper API, you can forget about dealing with
complex anti-bot systems and effortlessly collect public Yelp data,
including search results, comments, profiles, posts, images, and much
more. Don’t hesitate to contact us via [<u>live
chat</u>](https://oxylabs.io/) or
[<u>email</u>](mailto:support@oxylabs.io) in case you have any
questions.
pycounts_pcdlf 0.1.0
First test package
License: MIT
Requires Python: >=3.11

# pycounts_pcdlf

First test package

## Installation

```bash
$ pip install pycounts_pcdlf
```

## Usage

- TODO

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_pcdlf` was created by Peter de Looff. It is licensed under the terms of the MIT license.

## Credits

`pycounts_pcdlf` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
agnostica 0.0.2
A platform-agnostic library for creating multi-platform chat bots with ease.
License: MIT
Requires Python: >=3.11

Agnostica is a platform-agnostic library to make the creation of chat bots that function on multiple platforms more simple and streamlined.

## Documentation

Documentation is currently a work in progress.

## Support

There is currently not yet a support server for the library.

<!-- [![shield](https://shields.yoki-labs.xyz/shields/vanity/agnostica)](https://guilded.gg/agnostica) -->