Moto
Poetry
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Moto | Poetry | |
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32 | 377 | |
7,363 | 29,397 | |
1.1% | 2.3% | |
9.9 | 9.6 | |
6 days ago | about 19 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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Class Credentials does not exist
Unfortunately I do not believe AWS provides any "test" gateways. I do know there are mock AWS servers you can run on your own. The one I use is called Moto. It does not cover everything (unfortunately it's the most comprehensive out there AFAIK), but it's decent enough to test most standard calls via the sdk. I'm not sure if it covers authorization though...we tend to use security roles on tasks for authorization.
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What is the development enviroment for AWS?
If using Python use Moto to mock AWS Services
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Unit testing Athena ETL?
You can use a library such as moto https://github.com/getmoto/moto
- Looking for resources for building unit testing for boto3 code and mocking AWS services in pytest
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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.
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Mock AWS Services on Docker
Has anyone managed to configure moto (https://docs.getmoto.org/en/latest/) in a docker container in the similar way LocalStack does?
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Unit Testing an Airflow Dag
As for mocking, you can take a look at the moto library for mocking the AWS SDK, or for more simple cases even just use a `unittest.Mock/MagicMock` object. If you're having trouble trying to use the mocks in your code, it's a good sign your code is too highly coupled and it'd pay to re-factor, for example using dependency injection, design patterns like adapter/facade etc. (but don't over-do it)
- 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.
Poetry
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Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
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Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
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From Kotlin Scripting to Python
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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How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
What are some alternatives?
LocalStack - 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
Pipenv - Python Development Workflow for Humans.
aws-sdk-go - AWS SDK for the Go programming language.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
aws-cdk-local - Thin wrapper script for using the AWS CDK CLI with LocalStack
hatch - Modern, extensible Python project management
VCR.py - Automatically mock your HTTP interactions to simplify and speed up testing
pyenv - Simple Python version management
responses - A utility for mocking out the Python Requests library.
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
freezegun - Let your Python tests travel through time
virtualenv - Virtual Python Environment builder