semvec/pypi-packages huggingface dataset:
openstack-placement 12.0.2
Resource provider inventory usage and allocation service
Requires Python: >=3.8

If you are viewing this README on GitHub, please be aware that placement
development happens on `OpenStack git
<https://opendev.org/openstack/placement/>`_ and `OpenStack
gerrit <https://review.opendev.org>`_.

===================
OpenStack Placement
===================

.. image:: https://governance.openstack.org/tc/badges/placement.svg
    :target: https://governance.openstack.org/tc/reference/tags/index.html

OpenStack Placement provides an HTTP service for managing, selecting,
and claiming providers of classes of inventory representing available
resources in a cloud.

API
---

To learn how to use Placement's API, consult the documentation available
online at:

- `Placement API Reference <https://docs.openstack.org/api-ref/placement/>`__

For more information on OpenStack APIs, SDKs and CLIs in general, refer to:

- `OpenStack for App Developers <https://www.openstack.org/appdev/>`__
- `Development resources for OpenStack clouds
  <https://developer.openstack.org/>`__

Operators
---------

To learn how to deploy and configure OpenStack Placement, consult the
documentation available online at:

- `OpenStack Placement <https://docs.openstack.org/placement/>`__

In the unfortunate event that bugs are discovered, they should be reported to
the appropriate bug tracker. If you obtained the software from a 3rd party
operating system vendor, it is often wise to use their own bug tracker for
reporting problems. In all other cases use the master OpenStack bug tracker,
available at:

- `Bug Tracker <https://bugs.launchpad.net/placement>`__
- `File new Bug <https://bugs.launchpad.net/placement/+filebug>`__

Developers
----------

For information on how to contribute to Placement, please see the contents of
CONTRIBUTING.rst.

Further developer focused documentation is available at:

- `Official Placement Documentation <https://docs.openstack.org/placement/>`__
interactive-figure 0.5.0
Create interactive Matplotlib figures!
Requires Python: >=3.8

# Interactive Figure

This package serves for students to learn the basics of Python, Matplotlib and setting up reaction time experiments (visual search task, Stroop task, etc.). For a more accurate timing environment one should refer to e.g. [PsychoPy](https://www.psychopy.org/).

This is currently used at the University of Amsterdam (UvA) in the course *Introduction to Python Programming for Neuroscientists*.

Package created using [Hatch](https://hatch.pypa.io).

## Installation

```shell
pip install interactive-figure
```

## Usage

```python
import interactive_figure as ifig

ifig.create()
# Wait until user input is received.
ifig.wait_for_interaction()
key = ifig.get_last_key_press()
print(f"Pressed key: {key}")
ifig.close()
```

Demos can be found in the *demo* folder on GitHub.

## Limitations

- Waiting for user input will not work in Jupyter Notebooks and the interactive interpreter due to the way Matplotlib handles events.
- Automated testing is hard since tests should cover multiple backends (macosx, QtAgg, Tkgg) on multiple platforms (Windows, macOS, Linux). Tips are very welcome!

## Development

```bash
# Setup
pipx install hatch
hatch shell

# Build
hatch version fix
hatch build -c
./generate_docs.sh

# Publish
hatch publish
```

## Links

- [GitHub](https://github.com/teuncm/interactive-figure)
- [PyPI](https://pypi.org/project/interactive-figure/)
- [Documentation](https://teuncm.github.io/interactive-figure/autoapi/interactive_figure/interactive_figure/index.html)
gfmetadata 0.2.4
A python API for interacting with Google Fonts protobuf definitions
Requires Python: >=3.8

# Google Fonts Metadata Utilities

This crate provides:

* Helpers for reading metadata from a local copy of the Google Fonts repository.
* Access to Protobuf definitions for families, languages, axes and designers.
* Structured access to the tags and categories used in Google Fonts.
vtexpy 0.0.0b43
Unofficial VTEX API's Python SDK
Requires Python: <3.14,>=3.10
Keywords: api, client, sdk, vtex

# VTEXPY
[![PyPI Version](https://img.shields.io/pypi/v/vtexpy.svg)](https://pypi.python.org/pypi/vtexpy)

## Unofficial VTEX API's Python SDK

VTEXPY is an unofficial Python SDK designed to facilitate integration with the VTEX API.

Even though it is still tagged as beta, vtexpy has been in use by a _SaaS_ company in a
production environment for over a year, making millions of requests a day to the VTEX
API. The only reason why it is tagged as beta is that it is still under heavy
development and breaking changes are expected on the external API.

### Features

- Easy to use Python interface for calling VTEX API endpoints
- Response format standardization
- Custom exception handling
- Automatic request retrying
- Request logging

### Getting Started

#### Requirements

- Python >= 3.9, < 3.14

#### Installation

```bash
pip install vtexpy
```

#### Usage

If the API you want to call is not yet implemented, feel free to create an issue on the
VTEXPY Github repository and request it to be added.

```python
from vtex import VTEX, VTEXConfig

# Instantiate your VTEX API configuration:
vtex_config = VTEXConfig(
    account_name="<ACCOUNT_NAME>",
    app_key="<APP_KEY>",
    app_token="<APP_TOKEN>",
    # Other arguments such as: retrying, logging, etc...
)

# Instantiate the VTEX client with your configuration:
vtex_client = VTEX(config=vtex_config)

# Call one of the available APIs, e.g.:
account_response = vtex_client.license_manager.get_account()
list_sku_ids_response = vtex_client.catalog.list_sku_ids(page=1, page_size=1000)
list_orders_response = vtex_client.orders.list_orders(page=1, page_size=100)

# If the API you want to call is not yet implemented you can use the `custom` API.
response = vtex_client.custom.request(
    method="GET",
    environment="vtexcommercestable",
    endpoint="/api/catalog_system/pvt/commercialcondition/list",
    # Other arguments such as: query params, headers, json data, response class, etc...
)
```