orjson
conda
orjson | conda | |
---|---|---|
17 | 30 | |
5,588 | 6,092 | |
- | 0.7% | |
8.3 | 9.8 | |
4 days ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | 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.
orjson
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
orjson is the fastest JSON library available for python. It natively manages dataclass objects, datetime, numpy and UUID objects.
- Segunda linguagem
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Litestar 2.0
As we began venturing down that road, a few things emerged that would constitute significant changes to some of the core parts of Litestar, but there were two things in particular that started a chain reaction of changes by opening up further possibilities: The new DTOs and our switch from orjson to msgspec.
- orjson: Fast, correct Python JSON lib (supports dataclasses, datetimes, numpy)
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Starlite development updates January ’23
In version 1.45.0, we introduced msgspec as our serialization backend, replacing orjson. This had some immediate performance benefits, but that's not the main reason we made the switch.
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Making Python classes serializable to/from JSON
Doesn't orjson do that already?
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Processing JSON 2.5x faster than simdjson with msgspec
orjson
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Benchmarking Python JSON serializers - json vs ujson vs orjson
For most cases, you would want to go with python’s standard json library which removes dependencies on other libraries. On other hand you could try out ujsonwhich is simple replacement for python’s json library. If you want more speed and also want dataclass, datetime, numpy, and UUID instances and you are ready to deal with more complex code, then you can try your hands on orjson
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Json.dump new line with multiple values in key value pair.
Try https://github.com/ijl/orjson. Not exactly sure if that can help.
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.
- Why does creating my conda environment use so much memory?
- 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.
- Is Anaconda still open source?
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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).
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What is the status of Python 3.11?
It's worth noting that [ana]conda isn't even fully compatible yet with 3.11 (you can use it to create 3.11 environments--and you really should rather than waiting on relying on the system python--but conda itself can only run on 3.10.
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Miniconda finally released for Python 3.10
It took some time but as great Christmas present Miniconda was finally released with Python 3.10!
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TW: ZSH (and BASH?) does not show current working dir etc anymore
The September update broke it.
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Python 3.11.0 is now available
According to this this issue is high on their priority list (whatever that means).
What are some alternatives?
ujson
mamba - The Fast Cross-Platform Package Manager
ormsgpack - Msgpack serialization/deserialization library for Python, written in Rust using PyO3 and rust-msgpack. Reboot of orjson. msgpack.org[Python]
Poetry - Python packaging and dependency management made easy
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
miniforge - A conda-forge distribution.
pysimdjson - Python bindings for the simdjson project.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
cookiecutter-fastapi-firestore
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
mashumaro - Fast and well tested serialization library
pip - The Python package installer