orjson
NumPy
orjson | NumPy | |
---|---|---|
17 | 272 | |
5,588 | 26,413 | |
- | 1.1% | |
8.3 | 10.0 | |
4 days ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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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.
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
ujson
SymPy - A computer algebra system written in pure Python
ormsgpack - Msgpack serialization/deserialization library for Python, written in Rust using PyO3 and rust-msgpack. Reboot of orjson. msgpack.org[Python]
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
blaze - NumPy and Pandas interface to Big Data
pysimdjson - Python bindings for the simdjson project.
SciPy - SciPy library main repository
cookiecutter-fastapi-firestore
Numba - NumPy aware dynamic Python compiler using LLVM
mashumaro - Fast and well tested serialization library
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).