Introduction aux packages et à la documentation

Principes de génie logiciel en Python

Adam Spannbauer

Machine Learning Engineer at Eastman

Packages et PyPi

PyPi Logo

Introduction à pip

PyPi pip install

Introduction à pip

PyPi pip install

Utiliser pip pour installer numpy

datacamp@server:~$ pip install numpy

Collecting numpy
    100% |████████████████████████████████| 24.5MB 44kB/s 
Installing collected packages: numpy
Successfully installed numpy-1.15.4

Comment utilisons-nous numpy ?

Lecture de la documentation

Lecture de la documentation avec help()

help(numpy.busday_count)

busday_count(begindates, enddates)
    Counts the number of valid days between `begindates` and
    `enddates`, not including the day of `enddates`.


    Parameters
    ----------
    begindates : the first dates for counting.
    enddates : the end dates for counting (excluded from the count)


    Returns
    -------
    out : the number of valid days between the begin and end dates.


    Examples
    --------
    >>> # Number of weekdays in 2011
    ...  np.busday_count('2011', '2012')
    260

Lecture de la documentation avec help()

import numpy as np
help(np)

    Provides
      1. An array object of arbitrary homogeneous items
      2. Fast mathematical operations over arrays
      3. Linear Algebra, Fourier Transforms, Random Number Generation

help(42)

class int(object)
 |  int(x=0) -> integer
 |  int(x, base=10) -> integer
 |  
 |  Convert a number or string to an integer, or return 0 if no arguments
 |  are given.  If x is a number, return x.__int__().  For floating point
 |  numbers, this truncates towards zero.

Passons à la pratique !

Principes de génie logiciel en Python