Moto
Poetry
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Moto | Poetry | |
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32 | 375 | |
7,339 | 29,170 | |
1.4% | 3.3% | |
9.9 | 9.6 | |
6 days ago | about 22 hours ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
Moto
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OpenTF Announces Fork of Terraform
> OpenMoto
I dunno if you're trying to play on "hashimoto" but https://github.com/getmoto/moto#readme would be a prime name collision for any such "OpenMoto" name
But yes, please, to adopting Vault. I don't have a horse in the race about Consul but my suspicion is such an effort would only be worthwhile if trying to adopt Nomad, too, which I gravely doubt
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What is the development enviroment for AWS?
If using Python use Moto to mock AWS Services
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Guide to AWS Serverless & Lambda Testing Best Practices — Part 1
The Pythonic motto library mocks AWS services, removing the need to deploy your application or pay for API calls against AWS services. Other programming languages have their motto implementation.
- Final FLiP Stack Weekly of 2022
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Do unit tests make sense here?
To add on to the integration tests point, for mocking out your AWS resources you should check out moto if you don't want run your test against real AWS resources as they may cost you and is usually slower.
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Do some developers actually, REALLY, have no local environment and run everything in AWS? Is the individual cloud dev environment a real alternative to having things running locally?
You should be able to unit test your application on any device. (I use moto to help there.) And then when you want to ensure that you've given your lambda the right security groups or whatever, you deploy to a real but non-production lambda, and that deployment can be from anywhere.
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Getting started with testing DynamoDB code in Python
The Python package moto bundles mocks for many AWS services, including DynamoDB. The DynamoDB mock behaves mainly like the service - we can create tables, add data, query data, remove data, and much more. Not all features are supported, though - the documentation lists the available API calls. We can use this in combination with pytest to create a simple test setup.
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Mocking AWS Dynamo Db calls during testing
moto is an amazing library to mock any AWS Dynamo DB based calls. You can check out the development on their GitHub page.
- How to handle cloud resources in your application while running localhost
- Localstack – Local AWS Emulator
Poetry
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How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
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Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
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Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
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Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
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Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
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Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
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Poetry VS instld - a user suggested alternative
2 projects | 9 Dec 2023
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Navigating the Release Journey of txtToWeb
For the release of txtToWeb, I opted for Poetry as my release tool and TestPyPI as the package registry. Poetry's simplicity and TestPyPI's environment for testing releases were crucial factors in my decision.
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📜 RepoList - A tool to generate wordlists based on GitHub repositories
I've used Python with Poetry to create Repolist. Poetry is fairly new to me and It was a great experience using it. Easy setup and dependency management. With few commands, I was able to create the project and publish it to PyPI. I will definitely use it for my future projects.
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My first Software Release using GitHub Release
There were various approaches recommended depending on our language and ecosystem. My classmates who developed using Node.js were recommended npm, and PyPI or poetry for Python. Since my program is written in C++, I was recommended to look into one of vcpkg or conan, but I ultimately did not use either package manager.
What are some alternatives?
Pipenv - Python Development Workflow for Humans.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
hatch - Modern, extensible Python project management
LocalStack - 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
pyenv - Simple Python version management
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
virtualenv - Virtual Python Environment builder
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
pipx - Install and Run Python Applications in Isolated Environments
flit - Simplified packaging of Python modules
PyInstaller - Freeze (package) Python programs into stand-alone executables
pip - The Python package installer