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python3-geomet-0.3.0-4.fc36.noarch: Convert GeoJSON to WKT/WKB (Well-Known Text/Binary), and vice versa.

python3-funcparserlib-1.0.0a0-2.prerelease.fc36.noarch: Parser combinators are just higher-order functions that take parsers as their arguments and return them as result values. Parser combinators are: * First-class values * Extremely composable * Tend to make the code quite compact * Resemble the readable notation of xBNF grammars Parsers made with funcparserlib are pure-Python LL(*) parsers. It means that it's very easy to write them without thinking about look-aheads and all that hardcore parsing stuff. But the recursive descent parsing is a rather slow method compared to LL(k) or LR(k) algorithms. So the primary domain for funcparserlib is parsing little languages or external DSLs (domain specific languages).

python3-flit-3.8.0-1.lbn36.noarch: Flit is a simple way to put Python packages and modules on PyPI. It tries to require less thought about packaging and help you avoid common mistakes. See Why use Flit? for more about how it compares to other Python packaging tools. Install $ python3 -m pip install flit Flit requires Python 3 and therefore needs to be installed using the Python 3 version of pip. Python 2 modules can be distributed using Flit, but need to be importable on Python 3 without errors. Usage Say you’re writing a module foobar — either as a single file foobar.py, or as a directory — and you want to distribute it. Make sure that foobar’s docstring starts with a one-line summary of what the module is, and that it has a __version__: """An amazing sample package!""" __version__ = "0.1" Install flit if you don’t already have it: python3 -m pip install flit Run flit init in the directory containing the module to create a pyproject.toml file. It will look something like this: [build-system] requires = ["flit_co

python3-flask-sockets-0.2.1-1.lbn36.noarch: Flask-Sockets -Elegant WebSockets for your Flask apps.

python3-falcon-3.1.1-1.lbn36.x86_64: |Build Status| |Docs| |codecov.io| |Blue|The Falcon Web Framework Falcon <>__ is a minimalist ASGI/WSGI framework for building mission-critical REST APIs and microservices, with a focus on reliability, correctness, and performance at scale.When it comes to building HTTP APIs, other frameworks weigh you down with tons of dependencies and unnecessary abstractions. Falcon cuts to the chase with a...

python3-eventlet-0.39.1-1.lbn36.noarch: Eventlet is a networking library written in Python. It achieves high scalability by using non-blocking io while at the same time retaining high programmer usability by using coroutines to make the non-blocking io operations appear blocking at the source code level.

python3-db-dtypes-1.1.1-1.lbn36.noarch: Pandas Data Types for SQL systems (BigQuery, Spanner) |ga| |pypi| |versions|Pandas extension data types_ for data from SQL systems such as BigQuery_.- Library Documentation_.. |g .. |pyp .. |version :target:

python3-dataclasses-json-0.6.4-1.lbn36.noarch: Dataclasses JSON![]( library provides a simple API for encoding and decoding [dataclasses]( to and from JSON.It's very easy to get started.[README / Documentation website]( Features a navigation bar and search functionality, and should mirror this README exactly -- take a look! Quickstartpip install dataclasses-jsonpython from dataclasses import dataclass from dataclasses_json import...

python3-dataclasses-0.8-1.lbn36.noarch: This is an implementation of PEP 557, Data Classes. It is a backport for Python 3.6. Because dataclasses will be included in Python 3.7, any discussion of dataclass features should occur on the python-dev mailing list at At this point this repo should only be used for historical purposes (it's where the original dataclasses discussions took place) and for discussion of the actual backport to...

python3-cloudpickle-3.1.1-2.lbn36.noarch: cloudpickle makes it possible to serialize Python constructs not supported by the default pickle module from the Python standard library. cloudpickle is especially useful for cluster computing where Python expressions are shipped over the network to execute on remote hosts, possibly close to the data. Among other things, cloudpickle supports pickling for lambda expressions, functions and classes defined interactively in the __main__ module.

python3-arango-7.5.3-1.lbn36.noarch: ![Logo]( [![CodeQL]( [![codecov](

python3-apache-beam-2.47.0-1.lbn36.x86_64: Apache Beam is a unified programming model for both batch and streaming data processing, enabling efficient execution across diverse distributed execution engines and providing extensibility points for connecting to different technologies and user communities.

python3-analytics-1.4.0-2.lbn36.noarch: Segment is the simplest way to integrate analytics into your application. One API allows you to turn on any other analytics service. No more learning new APIs, repeated code, and wasted development time.This is the official python client that wraps the Segment REST API ().Documentation and more details at

python3-Levenshtein-0.26.1-3.lbn36.x86_64: Levenshtein computes Levenshtein distances, similarity ratios, generalized medians and set medians of Strings and Unicodes.

python3-jsonpointer-2.0-5.fc36.noarch: Library to resolve JSON Pointers according to RFC 6901.

python3-consul-1.2.4-1.lbn36.noarch: Python client for Consul.io

python3-strawberry-graphql-django-0.60.0-1.lbn36.noarch: Strawberry GraphQL Django integration Docs | Discord This package provides powerful tools to generate GraphQL types, queries, mutations and resolvers from Django models. Installing strawberry-graphql-django package from the python package repository. pip install strawberry-graphql-django Supported Features GraphQL type generation from models Filtering, pagination and ordering Basic create, retrieve, update and delete (CRUD) types and mutations Basic Django auth support, current user query, login and logout mutations Django sync and async views Permission extension using django's permissioning system Relay support with automatic resolvers generation Query optimization to improve performance and avoid common pitfalls (e.g n+1) Debug Toolbar integration with graphiql to display metrics like SQL queries Unit test integration Basic Usage from django.db import models class Fruit(models.Model): """A tasty treat""" name = models.CharField( max_le

python3-strawberry-graphql-0.264.0-1.lbn36.noarch: Strawberry GraphQL Python GraphQL library based on dataclasses Installation ( Quick Start ) The quick start method provides a server and CLI to get going quickly. Install with: pip install "strawberry-graphql[debug-server]" Getting Started Create a file called app.py with the following code: import strawberry @strawberry.type class User: name: str age: int @strawberry.type class Query: @strawberry.field def user(self) -> User: return User(name="Patrick", age=100) schema = strawberry.Schema(query=Query) This will create a GraphQL schema defining a User type and a single query field user that will return a hardcoded user. To run the debug server run the following command: strawberry server app Open the debug server by clicking on the following link: http:/0.0.0.0:8000/graphql This will open GraphiQL where you can test the API. Type-checking Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. To enable it, ad

python3-mkdocstrings+python-legacy-0.25.1-1.lbn36.noarch: This is a metapackage bringing in python-legacy extras requires for python3-mkdocstrings. It makes sure the dependencies are installed.

python3-mkdocstrings+python-0.25.1-1.lbn36.noarch: This is a metapackage bringing in python extras requires for python3-mkdocstrings. It makes sure the dependencies are installed.

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