Averroes

En effet en plaçant "*arg" dans la définition de la fonction les arguments seront reçus sous forme d'un tuple.
En effet en plaçant "**arg" dans la définition de la fonction les arguments seront reçus sous forme d'un dictionnaire

Averroes

# example.py
#
# Example of calculating with dictionaries

prices = {
   'ACME': 45.23,
   'AAPL': 612.78,
   'IBM': 205.55,
   'HPQ': 37.20,
   'FB': 10.75

Averroes

# example.py
#
# Determine the most common words in a list

words = [
   'look', 'into', 'my', 'eyes', 'look', 'into', 'my', 'eyes',
   'the', 'eyes', 'the', 'eyes', 'the', 'eyes', 'not', 'around', 'the',
   'eyes', "don't", 'look', 'around', 'the', 'eyes', 'look', 'into',
   'my', 'eyes', "you're", 'under'
]

Averroes

# example of extracting a subset from a dictionary
from pprint import pprint

prices = {
   'ACME': 45.23,
   'AAPL': 612.78,
   'IBM': 205.55,
   'HPQ': 37.20,
   'FB': 10.75
}

Averroes

# Examples of different ways to filter data

mylist = [1, 4, -5, 10, -7, 2, 3, -1]

# All positive values
pos = [n for n in mylist if n > 0]
print(pos)

# All negative values
neg = [n for n in mylist if n < 0]

Averroes

# example.py
#
# Find out what two dictionaries have in common

a = {
   'x' : 1,
   'y' : 2,
   'z' : 3
}

Averroes

# example.py
#
# Example of using heapq to find the N smallest or largest items

import heapq

portfolio = [
   {'name': 'IBM', 'shares': 100, 'price': 91.1},
   {'name': 'AAPL', 'shares': 50, 'price': 543.22},
   {'name': 'FB', 'shares': 200, 'price': 21.09},

Averroes

rows = [
    {'address': '5412 N CLARK', 'date': '07/01/2012'},
    {'address': '5148 N CLARK', 'date': '07/04/2012'},
    {'address': '5800 E 58TH', 'date': '07/02/2012'},
    {'address': '2122 N CLARK', 'date': '07/03/2012'},
    {'address': '5645 N RAVENSWOOD', 'date': '07/02/2012'},
    {'address': '1060 W ADDISON', 'date': '07/02/2012'},
    {'address': '4801 N BROADWAY', 'date': '07/01/2012'},
    {'address': '1039 W GRANVILLE', 'date': '07/04/2012'},
]

Averroes

# example.py
#
# Example of a priority queue

import heapq

class PriorityQueue:
    def __init__(self):
        self._queue = []
        self._index = 0

Averroes

from collections import deque

def search(lines, pattern, history=5):
    previous_lines = deque(maxlen=history)
    for line in lines:
        if pattern in line:
            yield line, previous_lines
        previous_lines.append(line)

# Example use on a file