SQLAlchemy
psycopg2
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SQLAlchemy | psycopg2 | |
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123 | 19 | |
8,750 | 3,205 | |
3.3% | 1.6% | |
9.7 | 7.2 | |
2 days ago | 22 days ago | |
Python | C | |
MIT License | GNU General Public License v3.0 or later |
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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.
psycopg2
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Can I learn Python while practicing writing queries for SQL simultaneously? I've recently completed learning SQL and trying to get better at it.
You can practice both by using https://www.psycopg.org from your Python code to communicate with your database. When I wanted to practice some SQL, that's what I did (we use psycopg at work, so that's what I practiced with, making a dream journal thingy for myself that was better than just noting stuff in a notepad because I could then look up e.g. what other stuff was correlated with Y, how many times I dreamed of X, etc. etc.)
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Installing psycopg2==2.8.6 throws an error
But seems like it should work with Django 3, which you have specified https://github.com/psycopg/psycopg2/issues/1293
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Uploading CSVs to a SQL table using Python
If you're using Postgres for your SQL, look at the "copy' method of the psycopg module (see https://www.psycopg.org/articles/2020/11/15/psycopg3-copy/) . It's much faster than INSERTs in my experience (YMMV).
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Underappreciated Challenges with Python Packaging
Back when I used Psycopg2, there was no -binary package, so you'd get libpq set up similarly to pg-native. Docs say:
> The binary package is a practical choice for development and testing but in production it is advised to use the package built from sources.
Relevant GitHub discussion: https://github.com/psycopg/psycopg2/issues/674
I dunno, this seems worse to me.
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Integrate PostgreSQL Database In Python - A Hands-On Guide
Just go to the more easily readable docs here. I’m sorry, but the linked article is terrible.
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Has anyone made the switch from developing in Windows to macOS? Any general or specific advice about the switch?
psycopg2-binary. See https://github.com/psycopg/psycopg2/issues/1286.
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Dockerize a Django, React, and Postgres application with docker and docker-compose | by Anjal Bam
psycopg2-binary, PostgreSQL Database adapter for python.
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My Cookiecutter Django Setup
... # psycopg2==2.9.3 # https://github.com/psycopg/psycopg2 ...
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Why "import blescan as blescan"?
I sometimes do this in testing. For example, consider the library used to communicate with a Postgres database, psycopg.
- Engineers complaining about Docker for Mac?
What are some alternatives?
tortoise-orm - Familiar asyncio ORM for python, built with relations in mind
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
PonyORM - Pony Object Relational Mapper
queries - PostgreSQL database access simplified
Peewee - a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb
PostgreSQL - Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
Orator - The Orator ORM provides a simple yet beautiful ActiveRecord implementation.
txpostgres - Twisted wrapper for asynchronous PostgreSQL connections
prisma-client-py - Prisma Client Python is an auto-generated and fully type-safe database client designed for ease of use
awesome-mysql - A curated list of awesome MySQL software, libraries, tools and resources
pyDAL - A pure Python Database Abstraction Layer
Python PG Extras - Python PostgreSQL database performance insights. Locks, index usage, buffer cache hit ratios, vacuum stats and more.