Graphene
SQLAlchemy
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Graphene | SQLAlchemy | |
---|---|---|
19 | 123 | |
7,973 | 8,750 | |
0.6% | 3.3% | |
4.3 | 9.7 | |
about 1 month ago | 6 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Graphene
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Who moved my error codes? Adding error types to your GoLang GraphQL Server
And gqlgen is not alone in this. We found several more GraphQL frameworks that don’t take it upon themselves to address this problem. Widely used GraphQL server implementations, such as graphql-go/graphql and Python’s graphene, have the exact same gap of exposing messages of unexpected errors by default.
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Using GraphQL with Strawberry, FastAPI, and Next.js
There are multiple Python-based GraphQL libraries and they all vary slightly from each other. For the longest time, Graphene was a natural choice as it was the oldest and was used in production at different companies, but now other newer libraries have also started gaining some traction.
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Wasmer and Trademarks
> But you need to know that Wasmer and its sibling projects will stay free forever. We are open source lovers, all of us, and we have a strong background on working on open source projects before joining Wasmer too.
That's great. I'm sure the closed source paid 10x faster editions of the graphene Python GraphQL server written by Syrus "CEO of Graphene" and CEO of wasmer will be open sourced in this spirit.
https://github.com/graphql-python/graphene/issues/268#issuec...
http://graphql-quiver.com/
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graphene django with cloudinary model field
CloudinaryField is a custom model field not a django built in one and graphene-python doesn't know what do with it. See the list of types it does https://github.com/graphql-python/graphene/tree/master/graphene/types
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[Python] What minimal application server do you run your Python x GraphQL services with? Django, Flask....
Thanks for the reply, I was looking at Strawberry a bit but not enough documentation for a graphql noob like me... Hate to turn this into tech support but could you potentially answer a question for me? I'm having a really hard time figuring out how to do this. Given this example: https://github.com/graphql-python/graphene/blob/master/examples/simple_example.py and a slight modification:
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Strawberry Django Plus: Enchanted Strawberry GraphQL integration with Django
Graphene was one of the first (if not the first) lib built on top of graphql-core to provide an easy to use api to build graphql applications. It's been around since 2015 and has a lot of integrations built for it (e.g. Django, SQL Alchemy, etc).
- Graphene – Python GraphQL Library
- Graphene 3.0 is released
- Graphene 3.0 Is Released
SQLAlchemy
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Xz/liblzma: Bash-stage Obfuscation Explained
OK -
can we start considering binary files committed to a repo, even as data for tests, to be a huge red flag, and that the binary files themselves should instead be generated at testing time by source code that's stated as reviewable cleartext. This would make it much harder (though of course we can never really say "impossible") to embed a substantial payload in this way.
when binary files are part of a test suite, they are typically trying to illustrate some element of the program being tested, in this case a file that was incorrectly xz-encoded. Binary files like these weren't typed by hand, they will always ultimately come from something plaintext source.
Here's an example! My own SQLAlchemy repository has a few binary files in it! https://github.com/sqlalchemy/sqlalchemy/blob/main/test/bina... oh noes. Why are those files there? well in this case I just wanted to test that I can send large binary BLOBs into the database driver and I was lazy. This is actually pretty dumb, the two binary files here add 35K of useless crap to the source, and I could just as easily generate this binary data on the fly using a two liner that spits out random bytes. Anyone could see that two liner and know that it isn't embedding a malicious payload.
If I wanted to generate a poorly formed .xz file, I'd illustrate source code that generates random data, runs it through .xz, then applies "corruption" to it, like zeroing out the high bit of every byte. The process by which this occurs would be all reviewable in source code.
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Introducing Flama for Robust Machine Learning APIs
Besides, flama also provides support for SQL databases via SQLAlchemy, an SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. Finally, flama also provides support for HTTP clients to perform requests via httpx, a next generation HTTP client for Python.
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Alembic with Async SQLAlchemy
Alembic is a lightweight database migration tool for usage with SQLAlchemy. The term migration can be a little misleading, because in this context it doesn't mean to migrate to a different database in the sense of using a different version or a different type of database. In this context, migration refers to changes to the database schema: add a new column to a table, modify the type of an existing column, create a new index, etc..
- Imperative vs. Declarative mapping style in Domain Driven Design project
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Unlocking efficient authZ with Cerbos’ Query Plan
To simplify this process, Cerbos developers have come up with adapters for popular Object-Relational Mapping (ORM) frameworks. You can check out for more details on the query plan repo - which also contains adapters for Prisma and SQLAlchemy - as well as a fully functioning application using Mongoose as its ORM.
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Python: Just Write SQL
That above pattern is one I've seen people do even recently, using the "select().c" attribute which from very early versions of SQLAlchemy is defined as "the columns from a subquery of the SELECT" ; this usage began raising deprecation warnings in 1.4 and is fully removed in 2.0 as it was a remnant of a much earlier version of SQLAlchemy. it will do exactly as you say, "make a subquery for each filter condition".
the moment you see SQLAlchemy doing something you see that seems "asinine", send an example to https://github.com/sqlalchemy/sqlalchemy/discussions and I will clarify what's going on, correct the usage so that the query you have is what you expect, and quite often we will add new warnings or documentation when we see people doing things we didn't anticipate.
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A steering council note about making the global
The creator and lead maintainer of SQLAlchemy, one of the most popular and most used Python library for accessing databases (who doesn't?) gave a rather interesting response to PEP703.
If this doesn't ring any alarm bells I don't know what will.
> Basically for the moment the GIL-less idea would likely be burdensome for us and the fact that it's only an "option" seems to strongly imply major compatibility issues that we would not prefer.
https://github.com/sqlalchemy/sqlalchemy/discussions/10002#d...
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More public SQL-queryable databases?
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.
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How useful is Python in accounting and auditing?
When using python with sql databases like postgres or mariadb or SQLite you would use SQLAlchemy or another ORM of if you're feeling brave, you code it by hand. With ORMs you provide the address of your database and it connects for you, letting you use abstractions instead of writing all the SQL yourself (kind of analogous to using vlookups or index match instead of manually entering data).
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Day 46-47: Beginner FastAPI Series - Part 3
Our tool we're going to be using for interfacing with the SQLite database is SQLAlchemy, a SQL toolkit that provides a unified API for various relational databases. If you installed FastAPI with pip install "fastapi[all]", SQLAlchemy is already part of your setup. but if you opted for FastAPI alone, you would need to install SQLAlchemy separately with pip install sqlalchemy.
What are some alternatives?
strawberry - A GraphQL library for Python that leverages type annotations 🍓
tortoise-orm - Familiar asyncio ORM for python, built with relations in mind
ariadne - Python library for implementing GraphQL servers using schema-first approach.
PonyORM - Pony Object Relational Mapper
tartiflette-aiohttp - tartiflette-aiohttp is a wrapper of aiohttp which includes the Tartiflette GraphQL Engine, do not hesitate to take a look of the Tartiflette project.
Peewee - a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
Orator - The Orator ORM provides a simple yet beautiful ActiveRecord implementation.
CherryPy - CherryPy is a pythonic, object-oriented HTTP framework. https://cherrypy.dev
prisma-client-py - Prisma Client Python is an auto-generated and fully type-safe database client designed for ease of use
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
pyDAL - A pure Python Database Abstraction Layer