List

2.3. List#

2.3.1. any: Check if Any Element of an Iterable is True#

If you want to check if any element of an iterable is True, use any. In the code below, I use any to find if any element in the text is in uppercase.

text = "abcdE"
any(c.isupper() for c in text)

True

2.3.2. all: Check if All Elements of an Interable Are Strings#

If you want to check if all elements of an iterable are strings, use all and isinstance.

l = ['a', 'b', 1, 2]

all(isinstance(item, str) for item in l)

False

2.3.3. filter: Get the Elements of an Iterable that a Function Evaluates True#

If you want to get only the elements of an iterable that satisfy the given condition, use filter.

nums = [1, 2, 3, 4, 5]

# Get even numbers
list(filter(lambda num: num % 2 == 0, nums))

[2, 4]

2.3.4. map method: Apply a Function to Each Item of an Iterable#

If you want to apply a function to each element of an iterable, use map.

nums = [1, 2, 3, 4, 5]

# Multiply every number by 2
list(map(lambda num: num * 2, nums))

[2, 4, 6, 8, 10]

2.3.5. sort: Sort a List of Tuples by the First or Second Item#

To sort a list of tuples, use the sort() method and pass in the key parameter to indicate which item to sort by.

prices = [('orange', 1), ('grape', 3), ('banana', 2)]

# Sort by the first item
by_letter = lambda x: x[0]
prices.sort(key=by_letter)
prices

[('banana', 2), ('grape', 3), ('orange', 1)]

# Sort by the second item
by_price = lambda x: x[1]
prices.sort(key=by_price)
prices

[('orange', 1), ('banana', 2), ('grape', 3)]

2.3.6. Simplify List Condition Evaluation with any and List Comprehensions#

When checking if a condition is true for any list element in Python, use any with a list comprehension instead of a for loop and if-else statements for more readable code.

FRUITS = ['apple', 'orange', 'grape']

def check_mention_fruit_1(text: str):
    for fruit in FRUITS:
        if fruit in text:
            return True 

check_mention_fruit_1('I got an apple.')

True

def check_mention_fruit_2(text: str):

    return any(fruit in text for fruit in FRUITS)


check_mention_fruit_2("I got an apple.")

True

sum([1, 2, 3], start=10)

16

2.3.7. random.choice: Get a Randomly Selected Element From a Python List#

Besides getting a random number, you can also get a random element from a Python list using random. In the code below, “stay at home” was picked randomly from a list of options.

import random

to_do_tonight = ["stay at home", "attend party", "do exercise"]

random.choice(to_do_tonight)

'stay at home'

l = [1, 2, 3]
l.pop()

3

2.3.8. random.choices: Get Weighted Random Choices From a Python List#

If you want to get a list of random elements from a specific list, use random.choices. This method also allows you to weigh the possibility for each value with the weights parameter.

In the code below, I use random.choices to get a list of 10 random values. 0 is two times more likely to be selected than 1 and is ten times more likely to be selected than 2.

import random

random.choices([0, 1, 2], weights=[10, 5, 1], k=10)

[0, 1, 0, 0, 1, 0, 0, 0, 1, 0]

2.3.9. random.sample: Get Multiple Random Elements from a Python List#

If you want to get n random elements from a list, use random.sample.

import random

random.seed(1)
nums = [1, 2, 3, 4, 5]
random_nums = random.sample(nums, 2)
random_nums

[2, 1]

2.3.10. heapq: Find n Max Values of a Python List#

If you want to extract n max values from a large Python list, using heapq will speed up the code.

In the code below, using heapq is more than 2 times faster than using sorting and indexing. Both methods try to find the max values of a list of 10000 items.

import heapq
import random
from timeit import timeit

random.seed(0)
l = random.sample(range(0, 10000), 10000)

def get_n_max_sorting(l: list, n: int):
    l = sorted(l, reverse=True)
    return l[:n]

def get_n_max_heapq(l: list, n: int):
    return heapq.nlargest(n, l)

expSize = 1000
n = 100
time_sorting = timeit("get_n_max_sorting(l, n)", number=expSize,
                        globals=globals())
time_heapq = timeit('get_n_max_heapq(l, n)', number=expSize,
                    globals=globals())

ratio = round(time_sorting/time_heapq, 3)
print(f'Run {expSize} experiments. Using heapq is {ratio} times'
' faster than using sorting')

Run 1000 experiments. Using heapq is 3.69 times faster than using sorting

2.3.11. join method: Turn an Iterable into a Python String#

If you want to turn an iterable into a string, use join().

In the code below, I join elements in the list fruits using “, “.

fruits = ['apples', 'oranges', 'grapes']

fruits_str = ', '.join(fruits)

print(f"Today, I need to get some {fruits_str} in the grocery store")

Today, I need to get some apples, oranges, grapes in the grocery store

2.3.12. Zip: Associate Elements from Two Iterators based on the Order#

If you want to associate elements from two iterators based on the order, combine list and zip.

nums = [1, 2, 3, 4]
string = "abcd"
combinations = list(zip(nums, string))
combinations

[(1, 'a'), (2, 'b'), (3, 'c'), (4, 'd')]

2.3.13. Python 3.10’s strict=True: Preventing Data Loss in zip Operations#

zip allows you to aggregate elements from each of the iterables. However, if the iterables are not the same length, the remaining elements of the longer iterables are not paired, potentially leading to unnoticed bugs.

fruits = ["apple", "orange", "grape"]
prices = [1, 2]

list(zip(fruits, prices))

[('apple', 1), ('orange', 2)]

Starting with Python 3.10, using the strict keyword argument with zip raises a ValueError if the lengths of the iterables are unequal.

try:
    list(zip(fruits, prices, strict=True))
except ValueError as e:
    print(f"Error: {e}")

Error: zip() argument 2 is shorter than argument 1

2.3.14. Unzip a List of Iterables#

You can turn a list of iterables into 2 separate iterables using zip(*list).

comb = [(1, 'a'), (2, 'b'), (3, 'c'), (4, 'd')]

nums_2, chars_2 = zip(*comb)
nums_2

(1, 2, 3, 4)

2.3.15. Difference between list append and list extend#

If you want to add a list to another list, use the append method. To add elements of a list to another list, use the extend method.

# Add a list to a list
a = [1, 2, 3, 4]
a.append([5, 6])
a

[1, 2, 3, 4, [5, 6]]

a = [1, 2, 3, 4]
a.extend([5, 6])

a

[1, 2, 3, 4, 5, 6]

2.3.16. Clean Iterables Unpacking in Python#

Are you extracting items from an iterable using indexing?

l = [1, 2, 3]

a = l[0]
b = l[1]
c = l[2]

A more efficient way to achieve the same result is to assign the iterable to multiple variables simultaneously.

l = [1, 2, 3]
a, b, c = l

print("a =", a)
print("b =", b)
print("c =", c)

a = 1
b = 2
c = 3

This can make our code easier to read and understand, and is a common practice in Python.

2.3.17. Extended Iterable Unpacking: Ignore Multiple Values when Unpacking a Python Iterable#

If we have a longer iterable but we only want to extract the subset of the iterable, we can use the “splat” operator (*) to represent the elements that we don’t care about:

a, *_, b = [1, 2, 3, 4]

print("a =", a)
print("b =", b)
print("_ =", _)

a = 1
b = 4
_ = [2, 3]
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