Cython Reviews and Details

Social recommendations and mentions

• I Use Nim Instead of Python for Data Processing

  >Not type safe That's the point. Look up what duck typing means in Python. Your program is meant to throw exceptions if you pass in data that doesn't look and act how it needs to. This means that in Python you don't need to do defensive programming. It's not like in C where you spend many hundreds of lines safe-guarding buffer lengths, memory allocation, return codes, static type sizes, and so on. That means that... - Source: Hacker News / almost 2 years ago

• Ask HN: C/C++ developer wanting to learn efficient Python

  Https://cython.org can help with that. - Source: Hacker News / over 2 years ago

• How to make a c++ python extension?

  The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints. Source: about 3 years ago

• Codon: Python Compiler

  Just for reference, * Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11." * Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles. * Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... Makes writing C... - Source: Hacker News / about 3 years ago

• Any faster Python alternatives?

  Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.). Source: over 3 years ago

• What exactly is 'JIT'?

  JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython. Source: over 3 years ago

• Been using Python for 3 years, never used a Class.

  There are also just-in-time compilers available for some Python features, that compile those parts to machine code. That includes Numba (usable as a library within CPython) and Pypy (an alternative Python implementation that includes a JIT compiler to improve performance). There’s also Cython, which is a superset of Python that allows more directly interfacing with C and C++ functions, and compiling the resulting... Source: over 3 years ago

• Python-based compiler achieves orders-of-magnitude speedups

  That would be things like cython (https://cython.org/) and rpython (https://rpython.readthedocs.io/en/latest/). - Source: Hacker News / over 3 years ago

• My Python Code is importing C functions

  However, you can't run it with just python, since it's not actually plain python code. Instead, you'll need the cython compiler. Source: over 3 years ago

• Starlite development updates January ’23

  As you can see, in this benchmark Starlite handily beats even blakchseep, a notoriously fast ASGI framework written in Cython. Source: over 3 years ago

• Codon: A high-performance Python compiler

  How does this relate to https://cython.org/ ? Would it be possible to write performance-sensitive parts of a Python system in Codon and link that to a CPython or PyPy runtime that supports more dynamic features? - Source: Hacker News / over 3 years ago

• Do you guys have any resources for learning C++ and/or Fortran programming for physics?

  If you're already familiar with python and numpy, you might want to look into cython as an intermediate step before going straight into C. It allows you to compile most python code into a static binary that can be imported into a python script just like any other library. This allows you to get performance close to raw C without having to invest much effort, and has a lot of bells and whistles like... Source: over 3 years ago

• Python devs Vs C++ chads

  Now I understand why you didn't like it. As is with most libraries cross compiling with python is not as easy as it sounds. Only pure python code is cross platform everything else needs specific instructions for compilation. Can be tedious in some cases. PyO3 looks interesting. Is there anything equivalent to cython for rust? Cython is a very popular way to export computer intensive tasks to c with a python like... Source: over 3 years ago

• In One Minute : Pandas

  Pandas is a Python library for PANel DAta manipulation and analysis, example: multidimensional time series and cross-sectional data sets commonly found in statistics, experimental science results, econometrics, or finance. Pandas is implemented primarily using NumPy and Cython; it is intended to be able to integrate very easily with NumPy-based scientific libraries, such as statsmodels. - Source: dev.to / over 3 years ago

• What is the best open source/community IDE with Cython syntax highlighting

  In the simplest terms possible, a way to compile normal or normalish python to the scariest c-code imaginable in terms of reading, but it can run insanely fast compared to python using CPython, but still be import into python the same way as other modules. https://cython.org. Source: almost 4 years ago

• Is it time for Python to have a statically-typed, compiled, fast superset?

  Cython is a statically typed, compiled, fast superset, and it's been out for years. It's neat. Source: almost 4 years ago

• CyRK – An Open-Source, Cython and Numba Based Runge-Kutta Integrator That Works With Python Functions

  CyRK's [numba](https://numba.discourse.group/) (njit-safe) implementation is 10-25x faster than scipy's solve_ivp function (except for very long integrations). The [cython](https://cython.org/) implementation is about 20x faster. The cython function is also largely pre-compiled which avoids most of the initial performance hit found with using the numba version. Source: almost 4 years ago

• Are there any cases for using C to interact with Python?

  Long answer: use this https://cython.org/. Source: almost 4 years ago

• Multistage Programming / First Class runtime compiler support

  There are several packages that do this for Python. Cython is probably the most used. Usually it's used for compiling modules at installation time, but it can be used for dynamic compilation (I wouldn't call it just-in-time, more like 'as-needed'). Source: almost 4 years ago

• My supervisor wants me to rewrite a code into another language

  If the motivation is to have everything the lab produces in the same language, C++, then I would say that the end goal is for your code to be useable from C++. Therefore, you can make a C++ wrapper that calls the Python code. Depending on how your code is written, it may be easy to do or not. See https://cython.org/ and https://docs.python.org/3/extending/embedding.html. Source: almost 4 years ago

• Which other programming language best complements Python - Rust, Go, or something else?

  If your main interest is optimizing the slow bits of your Python code, Cython https://cython.org/ might also be a good fit for you. It's designed to let you write 99% of your code in regular Python while allowing you to optimize the one or two slow loops that take up most of your execution time in C or C++ code. Source: almost 4 years ago