strawberry
A GraphQL library for Python that leverages type annotations 🍓 (by strawberry-graphql)
nbdev
Create delightful software with Jupyter Notebooks (by fastai)
| strawberry | nbdev | |
|---|---|---|
| 33 | 45 | |
| 3,778 | 4,744 | |
| 1.4% | 0.6% | |
| 9.4 | 6.5 | |
| 1 day ago | 7 days ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
strawberry
Posts with mentions or reviews of strawberry.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-04.
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My PHP Problems
have a look to http://strawberry.rocks for Python.
I've still to find a better code first implementation too
- Strawberry: A Python Library for GraphQL
-
A question
Strawberry GraphQL with the Apollo library in React.
- Ask HN: Who is hiring? (July 2023)
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Appwrite OSS Fund Sponsors Strawberry
Strawberry is a modern GraphQL library for Python, that leverages Python’s type hint for a concise and intuitive API design. The library makes it easy to build GraphQL API and provides a built-in debug server for testing and debugging, support for Django, FastAPI and other frameworks.
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GitHub Accelerator: our first cohort and what's next
- https://github.com/strawberry-graphql/strawberry: A GraphQL library for Python that leverages type annotations
-
These 20 startups are in 1st ever batch of GitHub OS Accelerator
Strawberry : Python GraphQL library leveraging type annotations
- Startups are in first batch of GitHub OS Accelerator
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What is the best option for writing GraphQL APIs using Django in 2023?
Currently happily using strawberry-graphql for a small project.
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Python package for large scale project.
Hi there, I'm one of the maintainer of Strawberry GraphQL (https://strawberry.rocks/) so I'm definitely biased towards it :)
nbdev
Posts with mentions or reviews of nbdev.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-19.
- The Jupyter+Git problem is now solved
-
What is literate programming used for?
One example I've seen is ML/DL folks using jupyter notebooks to develop DL libraries in jupyter notebooks, see https://github.com/fastai/nbdev
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GitHub Accelerator: our first cohort and what's next
- https://github.com/fastai/nbdev: Increase developer productivity by 10x with a new exploratory programming workflow.
-
Startups are in first batch of GitHub OS Accelerator
9. Nbdev: Boost developer productivity with an exploratory programming workflow - https://nbdev.fast.ai/
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Start learning python for a Statistician with SAS experience and little R experience
See if you like nbdev way of working with data through python and jupyter. nbdev is an optional part that will create python packages from jupyter notebooks. Also even the simple tutorials are opinionated and will guide you to unit test your code and write CICD pipelines.
- FastKafka - free open source python lib for building Kafka-based services
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isn't this just too much for a take home assignment?
You probably don’t have time for this for the purposes of your task, but I will also throw in the recommendation of nbdev especially if you’re a Python person. I haven’t had a project to use it on yet, but I’ve gone through the docs and the walkthrough and it seems like a great framework for starting potential projects with all the infrastructure needed for if/when they eventually get big and need all the packaging and stuff
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Any experience dealing with a non-technical manager?
nbdev: jupyter notebooks -> python package
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Resources to bridge the gap between jupyter notebooks and regular python development
Take a look at https://github.com/fastai/nbdev - haven't used it but supposedly the whole if fast.ai library was written that way. It sounds like a natural direction in your scenario - allowing your to keep working in a familiar environment and still producing production ready code (will, at least in paper 😅)
- Rant: Jupyter notebooks are trash.
What are some alternatives?
When comparing strawberry and nbdev you can also consider the following projects:
Graphene - GraphQL framework for Python
papermill - 📚 Parameterize, execute, and analyze notebooks
ariadne - Python library for implementing GraphQL servers using schema-first approach.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
ariadne - A fancy diagnostics & error reporting crate
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
ariadne-extended - niceties when working with ariadne and Django
rr - Record and Replay Framework
starsessions - Advanced sessions for Starlette and FastAPI frameworks
Jupyter-PowerShell - Jupyter Kernel for PowerShell