mysqlclient
awesome-postgres
Our great sponsors
mysqlclient | awesome-postgres | |
---|---|---|
4 | 5 | |
2,406 | 9,520 | |
1.1% | - | |
7.7 | 5.0 | |
23 days ago | 7 days ago | |
Python | ||
GNU General Public License v3.0 only | Creative Commons Zero v1.0 Universal |
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.
mysqlclient
-
Can't install mysqclient in python 3.12
for your reference: https://github.com/PyMySQL/mysqlclient/issues/672
- mysqlclient in docker
- What is the defacto python driver for Mysql?
awesome-postgres
-
Ask HN: Best GitHub Repos
Personally love awesome Postgres - https://github.com/dhamaniasad/awesome-postgres
- A curated list of PostgreSQL software, libraries, tools and resources
- Free, open-source tools for Postgres
-
What is the best postgres SQL client for beginners?
Was a nice list of tools here https://dhamaniasad.github.io/awesome-postgres/
What are some alternatives?
PyMySQL - MySQL client library for Python
mysql-python - MySQLdb is a Python DB API-2.0 compliant library to interact with MySQL 3.23-5.1 (unofficial mirror)
awesome-mysql - A curated list of awesome MySQL software, libraries, tools and resources
oursql - oursql is a set of MySQL bindings for python with a focus on wrapping the MYSQL_STMT API to provide real parameterization and real server-side cursors.
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
PySQL - Python wrapper for making MySQL queries easier
pgtt - pgtt is a time traveling tool for PostgreSQL to help speedup development and testing of various applications by enabling the user to easily travel between points in time. This can be useful when for example you have to test a certain mutation multiple times and want to quickly rollback to before the mutation to make changes to the behaviour and test again. This will save time and avoids setting up the data over and over again, especially in larger applications with complex data and flows.