How to use cython to speed up python

cython is a programming language that makes writing c extensions for python as easy as python itself. it allows you to gain c-like performance with code that is written mostly in python, and it's particularly useful for speeding up computationally intensive tasks.

### getting started with cython

#### 1. setup

to use cython, you need to have it installed. you can install cython using pip:

make sure you have a c compiler installed as well, as cython will need to compile c code.

#### 2. write a cython file

create a new cython file with a `.pyx` extension. let’s say we want to speed up a simple function that computes the fibonacci sequence.

#### 3. create a setup file

#### 4. compile the cython code

to compile the cython code, run the following command in your terminal:

this will create a compiled shared library (a `.so` file on linux/macos or a `.pyd` file on windows) that you can import in your python code.

#### 5. use the compiled cython code

#### 6. run the python script

execute the python script:

you should see the output of the fibonacci number and the time taken to compute it.

### performance comparison

to see the performance benefits of using cython, you can compare the cython implementation with a pure python implementation. here’s a pure python version of the fibonacci function for comparison:

### additional tips

1. **type declarations**: you can declare variable types in cython to further improve performance. for example:


2. **using numpy**: if you are working with numerical data, consider using cython with numpy to take advantage of its capabilities.

3. **profiling**: use python profilers such as `cprofile` to identify bottlenecks in your code before optimizing with ...

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