Zappa
conda
Our great sponsors
Zappa | conda | |
---|---|---|
36 | 30 | |
3,006 | 6,051 | |
2.7% | 1.7% | |
7.0 | 9.8 | |
8 days ago | about 13 hours ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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.
Zappa
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Jets: The Ruby Serverless Framework
If people aren't familiar, there's a similar project for Python that's fantastic: https://github.com/zappa/Zappa
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Building serverless websites (lambdas written with python) - do I use FastAPI or plain old python?
Chalice was a consequence, a reaction from AWS to the release of (Zappa Framework)[https://github.com/zappa/Zappa] that provide a very good alternative to migrate very quickly a Django/Flask or any WSGI compliant solution in Python.
Flask has a GREAT tool called Zappa that makes deploying serverless to AWS as simple as typing "zappa update." It deploys the API Gateway, configures it, etc. Wonderful tool.
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Iām a Brazilian salesforce developer and want to work with django stack. Any tips?
Deployment works nicely with Docker. I often use AWS AppRunner because it's really easy and just scales. Some people use AWS Lambda with Zappa but I don't recommend it unless you really want to spend less than $15 a month. You will probably need Django Storages to save uploads to an S3 bucket. At some stage you might want to put a CloudFront distribution in front of everything but the configuration of the caching behaviour might be a bit confusing when you do it the first time.
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Why or why not use AWS Lambda instead of a web framework for your REST APIs? (Business projects)
It doesn't have to be an either-or! I have several apps in production that were developed on Django or Flask, and deployed to Lambda using Zappa.
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Backend Server with Django Rest API
If you need a relational DB, you can use AWS Aurora or RDS and use cloud functions ('lambda' in AWS) that you can invoke with HTTP to process the document first. Zappa will do a lot of the configuration for you if you go that route.
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Easiest/Best way to deploy django to AWS?
Lambda + API gateway, this library bundles a Django application into a lambda https://github.com/zappa/Zappa . 1 million free invokes from aws, scale to zero, plugs into your RDS
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We clone a running VM in 2 seconds
I use Zappa, it just schedules a frequent execution of the lambda: https://github.com/zappa/Zappa#keeping-the-server-warm
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Serverless Templates for AWS and Python
This repository should ease up your project setup by using Cookiecutter for choosing Flask or Django and Zappa for deploying your AWS Lambda.
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How to make Django package smaller for Serverless deployment
Really great š Zappa has been moved here https://github.com/zappa/Zappa
conda
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How to Create Virtual Environments in Python
Python's venv module is officially recommended for creating virtual environments since Python 3.5 comes packaged with your Python installation. While there still are additional older tools available, such as conda and virtualenv, if you are new to virtual environments, it is best to use venv now.
- Installing Anaconda on ChromeOS using Linux
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PSA: conda-libmamba-solver can cut two hours off of your Anaconda install, but has only 47 GitHub stars. It deserves more praise.
conda's dependency solver solves a harder problem than pip's. This quote alludes to it "Conda will never be as fast as pip, so long as we're doing real environment solves and pip satisfies itself only for the current operation." (from https://github.com/conda/conda/issues/7239). Thus mamba was created to improve performance and now conda is bringing in that performance boost.
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How to get the best Conda environment experience in Codespaces
The other challenge I ran into sometimes was that if I was running a lower memory/storage Codespace instance, when I tried to use Conda from the command line to modify environments, the process would be killed after a few seconds. This turns out to be related to some performance issues Conda has that make it consume a lot of memory when trying to work with the conda-forge installation channel. You can always then just increase the size of the Codespace your are working with (just go to your Codespaces list and use the triple dots to change the settings for a Codespace).
- Python 3.11.0 final is now available
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Processing JSON 2.5x faster than simdjson with msgspec
I wrote this up as a demo of some potential optimization work in conda, but the same principle could be applied to other projects.
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One-Click Install Stable Diffusion GUI App for M1 Mac. No Dependencies Needed
Which would be less of an issue if I didn't have to fix a conda bug while installing StableDiffusion.
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Issues during install with Miniconda3
Yeah, it's most likely that. Try reinstalling, and if that doesn't fix it, see this issue and related ones for other possible solutions.
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For you, data scientist
Thanks for letting us know about that. I will try this since conda was giving me some problems like causing powershell startup delays of over 4 seconds. See here: https://github.com/conda/conda/issues/11648 .
- Recommendations when publishing a WASM library
What are some alternatives?
mamba - The Fast Cross-Platform Package Manager
Poetry - Python packaging and dependency management made easy
miniforge - A conda-forge distribution.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
pip - The Python package installer
wheel - Adoption analysis of Python Wheels: https://pythonwheels.com/
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
PyInstaller - Freeze (package) Python programs into stand-alone executables
mangum - AWS Lambda support for ASGI applications
rez - An integrated package configuration, build and deployment system for software
pyright - Static Type Checker for Python