Peloton-Data-to-Google-Sheets
PyPika
Peloton-Data-to-Google-Sheets | PyPika | |
---|---|---|
3 | 4 | |
11 | 2,378 | |
- | 1.1% | |
3.5 | 5.6 | |
27 days ago | 12 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
Peloton-Data-to-Google-Sheets
- I feel like someone is pranking me, so here’s me making a post about my script
- Pretty Awesome Google Sheets Tracker
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Where are the Data Geeks? 🤓🎉
I’ve got a python script that imports it into google sheets for you. I’d be willing to help walk you through it on your own computer if you’re not familiar with python. All you have to do is run it and it does all the magic for you. Alternatively, I can rearrange it to work on excel. https://github.com/tychaney/Peloton-Data-to-Google-Sheets
PyPika
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any recommendations for a good query builder library with good support?
I recently started using drizzle orm and I am now looking for something similar in python, my goal is to be as close to sql syntax as possible without just passing dml commands as strings, type safety would be cool as well, I saw this one pypika but it ha a lot of open issues and no commits for a year, is there anything similar but more stable?
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Ask HN: Is SQLAlchemy the industry standard Python ORM in 2023?
Yes it is. I haven't seen many Python projects using Prisma and
Note that there are several types of technologies that can help connect an application to an SQL database:
- SQL builders: the best known project seems to be Pypika by Kayak (https://github.com/kayak/pypika) but it seems to be dead of sleeping.
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Write an SQL query builder in 150 lines of Python
https://github.com/kayak/pypika
Have used in multiple projects and have found it's the right balance between ORMs and writing raw SQL. It's also easily extensible and takes care of the many edge cases and nuances of rolling your own SQL generator.
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Migrating to SQLAlchemy 2.0
There is a middle-ground between writing SQL statement strings in your code, and a full-blown ORM: query builders. At least in my experience with small to medium projects, these have far fewer footguns while keeping the code composable and readable. Here's one for Python: https://github.com/kayak/pypika
What are some alternatives?
peloton-to-garmin - Convert workout data from Peloton into JSON/TCX/FIT files and automatically upload to Garmin Connect
TinyDB - TinyDB is a lightweight document oriented database optimized for your happiness :)
testcontainers-python - Testcontainers is a Python library that providing a friendly API to run Docker container. It is designed to create runtime environment to use during your automatic tests.
sqlc - Generate type-safe code from SQL
pylotoncycle - Python Library for getting your Peloton workout data
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
PyFreeDB - PyFreeDB is a Python library that provides common and simple database abstractions on top of Google Sheets.
PipelineDB - High-performance time-series aggregation for PostgreSQL
tksheet - Python tkinter table widget for displaying tabular data
pickleDB - pickleDB is an open source key-value store using Python's json module.
django-compositepk-model - Extended Django Model class with composite-primary-key support
postgres-typed