psycopg2
Poetry
psycopg2 | Poetry | |
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19 | 377 | |
3,214 | 29,552 | |
0.8% | 1.3% | |
6.8 | 9.7 | |
9 days ago | 3 days ago | |
C | Python | |
GNU General Public License v3.0 or later | MIT License |
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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?
Poetry
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Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
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Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
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From Kotlin Scripting to Python
Poetry
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How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
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Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
https://github.com/python-poetry/poetry/issues/6409
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Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
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Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
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Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
[1] https://github.com/python-poetry/poetry/issues/2184
[2] https://pypi.org/project/pypiserver/
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Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
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How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
What are some alternatives?
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
Pipenv - Python Development Workflow for Humans.
queries - PostgreSQL database access simplified
PDM - A modern Python package and dependency manager supporting the latest PEP standards
SQLAlchemy - The Database Toolkit for Python
hatch - Modern, extensible Python project management
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
pyenv - Simple Python version management
txpostgres - Twisted wrapper for asynchronous PostgreSQL connections
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
awesome-mysql - A curated list of awesome MySQL software, libraries, tools and resources
virtualenv - Virtual Python Environment builder