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This is a metapackage bringing in vertexai extras requires for python3-pydantic-ai-slim. It makes sure the dependencies are installed.
pydantic-core This package provides the core functionality for pydantic validation and serialization. Pydantic-core is currently around 17x faster than pydantic V1. See tests/benchmarks/ for details. Example of direct usage NOTE: You should not need to use pydantic-core directly; instead, use pydantic, which in turn uses pydantic-core. from pydantic_core import SchemaValidator, ValidationError v = SchemaValidator( { 'type': 'typed-dict', 'fields': { 'name': { 'type': 'typed-dict-field', 'schema': { 'type': 'str', }, }, 'age': { 'type': 'typed-dict-field', 'schema': { 'type': 'int', 'ge': 18, }, }, 'is_developer': { 'type': 'typed-dict-field', 'schema': { 'type': 'default', 'sc
Pydantic Extra Types A place for pydantic types that probably shouldn't exist in the main pydantic lib. See pydantic/pydantic#5012 for more info.
pydantic-graph
pydantic-settings Settings management using Pydantic, this is the new official home of Pydantic's BaseSettings. This package was kindly donated to the Pydantic organisation by Daniel Daniels, see pydantic/pydantic#4492 for discussion. For the old "Hipster-orgazmic tool to mange application settings" package, see version 0.2.5. See documentation for more details.
pydata-google-auth |Build Status| |Version Status| |Coverage Status|**pydata- google-auth** is a package providing helpers for authenticating to Google APIs. Installation Install latest release version via conda .. code-block:: shell $ conda install pydata-google-auth --channel conda-forgeInstall latest release version via pip .. code-block:: shell $ pip install pydata-google- authInstall...
The pydbus module provides pythonic DBUS bindings. It is based on PyGI, the Python GObject Introspection bindings, which is the recommended way to use GLib from Python. Python 3 version.
PyDo pydo is the official Python client library that allows Python developers to interact with and manage their DigitalOcean resources through a Python abstraction layer on top of the raw DigitalOcean API HTTP Interface. A top priority of this project is to ensure the client abides by the API contract. Therefore, the client itself wraps a generated client based on the DigitalOcean OpenAPI Specification to support all of DigitalOcean's HTTP APIs. Getting Started With the Client Prerequisites Python version: >= 3.7.2 Installation To install from pip: pip install git+https:/github.com/digitalocean/pydo.git or, if repo is cloned locally: pip install /<PATH>/<TO>/pydo To install from source: make install pydo Quickstart A quick guide to getting started with the client. pydo must be initialized with pydo.Client(). A DigitalOcean API Token is required. The token can be passed explicitly to pydo.Client(), as such: import os from pydo import Client client = Client(token=os.geten
pydocstyle - docstring style checker :target:
An interface for creating both directed and non directed graphs from Python. Currently all attributes implemented in the Dot language are supported (up to Graphviz 2.16). Output can be inlined in Postscript into interactive scientific environments like TeXmacs, or output in any of the format's supported by the Graphviz tools dot, neato, twopi.