tomlplusplus
Poetry
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tomlplusplus | Poetry | |
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23 | 377 | |
1,400 | 29,483 | |
- | 2.6% | |
6.4 | 9.7 | |
about 1 month ago | 4 days ago | |
C++ | Python | |
MIT License | 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.
tomlplusplus
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how to handle config files in c++?
Unless you want to make your own config file parser as an exercise (which is a good idea) I'd recommend using toml++.
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Cmake fetchContent not working in a docker container.
It's a public repo - this one: https://github.com/marzer/tomlplusplus but thank you
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Poxy - a Doxygen frontend - v0.9.0 released
For a live demo, see the toml++ homepage: https://marzer.github.io/tomlplusplus/
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Preferred way to read in application settings/config in C++
Added bonus, tomlplusplus is a solid C++ implementation, actively updated, and easy to drop into a project (header only, CMake, vcpkg, Conan, etc.). Very easy to use for what I've needed.
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toml++ v3.2.0 released
Key links: - Homepage: https://marzer.github.io/tomlplusplus/ - Repository: https://github.com/marzer/tomlplusplus - "What is TOML?": https://toml.io/
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CMake for toml not working
cmake_minimum_required(VERSION 3.23) project(testProj) set(CMAKE_CXX_STANDARD 23) set(FETCHCONTENT_BASE_DIR ${PROJECT_SOURCE_DIR}/${CMAKE_PROJECT_NAME}/libs CACHE PATH "Missing description." FORCE) include(FetchContent) FetchContent_Declare( tomlplusplus GIT_REPOSITORY https://github.com/marzer/tomlplusplus.git GIT_TAG v3.1.0 ) FetchContent_MakeAvailable(tomlplusplus) add_executable(testProj testProj/src/main.cpp) target_link_libraries(testProj tomlplusplus)
- toml++: Header-Only TOML Config File Parser And Serializer For C++
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What are some use cases of using shared_ptr in a single threaded program?
I use them in toml++ to store the path of the source document for all the data nodes parsed from that document. Storing it as a separate std::string allocation for every single object would have been very wasteful, and the alternative would have been to make an overall document class that owned everything, which I didn't want to do, so shared_ptr was a good compromise.
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toml++ v3.1.0 released
Key links: - Homepage: https://marzer.github.io/tomlplusplus/ - Repository: https://github.com/marzer/tomlplusplus - "What is TOML?": https://toml.io/
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What are some projects that taught you a lot?
toml++ was both my first 'public'/open-source project, and my first ever attempt at a parser. There's a few things I'd do differently now if I were to write it from scratch, but I've learned a lot along the way (particularly about making things build 'clean' on multiple platforms).
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?
https://github.com/python-poetry/poetry/issues/6409
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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
[1] https://github.com/python-poetry/poetry/issues/2184
[2] https://pypi.org/project/pypiserver/
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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?
toml11 - TOML for Modern C++
Pipenv - Python Development Workflow for Humans.
Magic Enum C++ - Static reflection for enums (to string, from string, iteration) for modern C++, work with any enum type without any macro or boilerplate code
PDM - A modern Python package and dependency manager supporting the latest PEP standards
toml - Tom's Obvious, Minimal Language
hatch - Modern, extensible Python project management
toml - Python lib for TOML
pyenv - Simple Python version management
json_test_data - Test data for nlohmann/json
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
cmkr - Modern build system based on CMake and TOML.
virtualenv - Virtual Python Environment builder