Zappa
QEMU
Zappa | QEMU | |
---|---|---|
36 | 190 | |
3,060 | 9,277 | |
1.8% | 1.3% | |
7.5 | 10.0 | |
8 days ago | 7 days ago | |
Python | C | |
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.
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Best way to host Django DRF on AWS? (so many competing options)
Use Zappa https://github.com/zappa/Zappa and host as a Lambda, simple setup and deployment, Lambda only costs when processing requests, no servers to mess around with
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How to deploy a project from git lab backend where I used django on backend and database
One of my favorite options that is probably the most cost-effective is to deploy using a 'severless' model on AWS Lambda using zappa which supports deploying Python webapps to AWS in this way. Zappa also makes it super easy to deploy in just a couple commands! The README includes instructions for everything you might need, including handling sensitive information like your database passwords, running django management commands, setting up DNS, etc.
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I’m 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.
- lambda API deployment
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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
QEMU
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QEMU Version 9.0.0 Released
My most-wanted QEMU feature: https://github.com/qemu/qemu/commit/a2260983c6553
Using `gic-version=3` on macOS you can now use more than 8 cores on ARM chips.
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Autoconf makes me think we stopped evolving too soon
A better solution is just to write a plain ass shell script that tests if various C snippets compile.
https://github.com/oilshell/oil/blob/master/configure
https://github.com/oilshell/oil/blob/master/build/detect-pwe...
Not an unholy mix of m4, shell, and C, all in the same file.
---
These are the same style as a the configure scripts that Fabrice Bellard wrote for tcc and QEMU.
They are plain ass shell scripts, because he actually understands the code he writes.
https://github.com/qemu/qemu/blob/master/configure
https://github.com/TinyCC/tinycc/blob/mob/configure
OCaml’s configure script is also “normal”.
You don’t have to copy and paste thousands of lines of GNU stuff that you don’t understand.
(copy of lobste.rs comment)
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WASM Instructions
Related:
A fast Pascal (Delphi) WebAssembly interpreter:
https://github.com/marat1961/wasm
WASM-4:
https://github.com/aduros/wasm4
Curated list of awesome things regarding WebAssembly (wasm) ecosystem:
https://github.com/mbasso/awesome-wasm
Also, it would be nice if there was a WASM (soft) CPU for QEMU, which (if it existed!) would go here:
https://github.com/qemu/qemu/tree/master/target
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Revng translates (i386, x86-64, MIPS, ARM, AArch64, s390x) binaries to LLVM IR
> architectural registers are always updated
In tiny code, the guest registers (global TCG variables) are stored in the host's registers until you either call an helper which can access the CPU state or you return (`git grep la_global_sync`). This is the reason why QEMU is not so terribly slow.
But after a check, this also happens when you access the guest memory address space! https://github.com/qemu/qemu/blob/master/include/tcg/tcg-opc... (TCG_OPF_SIDE_EFFECTS is what matters)
But still, in the end, it's the same problem. What QEMU does, can be done in LLVM too. You could probably be more efficient in LLVM by using the exception handling mechanism (invoke and friends) to only serialize back to memory when there's an actual exception, at the cost of higher register pressure. More or less what we do here: https://rev.ng/downloads/bar-2019-paper.pdf
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State of x86-64 emulation of non-MacOS binaries
Um, in case you don't know, UTM (based on QEMU) is out for quite a while.
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Multipass: Ubuntu Virtual Machines Made Easy
Some of these tools include Oracle VM VirtualBox (that I've used since before the acquisition of Sun Microsystems by Oracle), VMWare Workstation Player, and QEMU, but last year, I found out about Multipass.
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Libsodium: A modern, portable, easy to use crypto library
For C/C++ projects that use meson as the build system, there is an excellent way to manage dependencies:
https://mesonbuild.com/Wrapdb-projects.html
https://mesonbuild.com/Wrap-dependency-system-manual.html
meson will download and build the libraries automatically and give you a variable which you pass as a regular dependency into the built target:
https://github.com/qemu/qemu/tree/005ad32358f12fe9313a4a0191...
https://github.com/harfbuzz/harfbuzz/tree/main/subprojects
https://github.com/harfbuzz/harfbuzz/blob/37457412b3212463c5...
Or, if you're using proper operating systems, they're managed by the usual package manager, just like everything else.
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Top 6 Virtual Machine Software in 2023
For all the users of the Linux platform, QEMU is the VM that you should go for. This software comes without any price tag and works as an emulator of various machines with utmost ease and completion; the software uses dynamic translations to emulate hardware peripherals and enhances its overall performance. If you are using QEMU as a virtualizer, then it will function exactly like the host system (provided you have the right set of hardware).
- Show HN: I'm 17 and wrote this guide on how CPUs run programs
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UTM for Developers
In this tutorial, we set up macOS and Windows virtual machines on UTM, a macOS application that provides a GUI wrapper for QEMU, a powerful open-source emulator and virtualizer. UTM allows you to easily manage and run virtual machines without memorizing complex commands. It also has special handling for macOS, making it simpler to install compared to other virtual machine software.
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
UTM - Virtual machines for iOS and macOS
mangum - AWS Lambda support for ASGI applications
TermuxArch - Experience the pleasure of the Linux command prompt in Android, Chromebook, Fire OS and Windows on smartphone, smartTV, tablet and wearable https://termuxarch.github.io/TermuxArch/
chalice - Python Serverless Microframework for AWS
Unicorn Engine - Unicorn CPU emulator framework (ARM, AArch64, M68K, Mips, Sparc, PowerPC, RiscV, S390x, TriCore, X86)
Poetry - Python packaging and dependency management made easy
Vagrant - Vagrant is a tool for building and distributing development environments.
aws-sqs-jobs-processer - Serverless jobs processor on AWS
xemu - Original Xbox Emulator for Windows, macOS, and Linux (Active Development)
sample-django-docker - A sample of using Django with Docker and docker-compose
em-dosbox - An Emscripten port of DOSBox