Neha Christina

Posted on Mar 27

5 Python Built-ins You’re Not Using (But Should Be)

#python #codenewbie #beginners #programming

You don’t need a library. You don’t need to pip install anything. These five tools are already sitting inside Python, waiting for you to use them.

Most junior developers don’t know they exist. Senior developers reach for them every single day.

Let’s fix that.

1. zip()

Loop over multiple lists at the same time.

How most beginners do it:

names = ['Alice', 'Bob', 'Carol']
scores = [95, 87, 92]

for i in range(len(names)):
    print(names[i], scores[i])

How you should do it:

for name, score in zip(names, scores):
    print(name, score)

zip() pairs up elements from two (or more) iterables and lets you loop over them together. It stops when the shortest one runs out.

You can also use it to combine lists into a dictionary:

name_score = dict(zip(names, scores))
# {'Alice': 95, 'Bob': 87, 'Carol': 92}

2. any() and all()

Check conditions across a list without writing a loop.

The verbose way:

scores = [85, 92, 78, 95]
has_pass = False
for s in scores:
    if s >= 80:
        has_pass = True
        break

The clean way:

has_pass = any(s >= 80 for s in scores)
all_pass = all(s >= 80 for s in scores)

any() returns True if at least one item meets the condition. all() returns True only if every item does. Both short-circuit — they stop checking as soon as the answer is known, which makes them fast.

3. enumerate()

Get the index AND value without range(len()).

The clunky version:

fruits = ['apple', 'banana', 'cherry']
for i in range(len(fruits)):
    print(i, fruits[i])

The Pythonic version:

for i, fruit in enumerate(fruits):
    print(i, fruit)

Want to start counting from 1 instead of 0?

for i, fruit in enumerate(fruits, start=1):
    print(i, fruit)

range(len()) is considered a code smell in Python. If you find yourself writing it, reach for enumerate() instead.

4. map()

Apply a function to every item in a list.

The loop version:

names = ['alice', 'bob', 'carol']
capitalised = []
for name in names:
    capitalised.append(name.upper())

With map():

capitalised = list(map(str.upper, names))

Or with a lambda for custom logic:

doubled = list(map(lambda x: x * 2, numbers))

map() is great for simple, single-function transformations. For more complex logic involving conditions or multiple steps, a list comprehension is usually more readable:

capitalised = [name.upper() for name in names]

Both are valid — pick whichever reads more clearly for your use case.

5. collections

Counter, defaultdict, deque — all built in.

The manual counting approach:

words = ['cat', 'dog', 'cat', 'bird', 'cat']
counts = {}
for word in words:
    if word in counts:
        counts[word] += 1
    else:
        counts[word] = 1

With Counter:

from collections import Counter

counts = Counter(words)
# Counter({'cat': 3, 'dog': 1, 'bird': 1})

top_2 = counts.most_common(2)
# [('cat', 3), ('dog', 1)]

collections also gives you:

defaultdict — like a regular dict, but never raises a KeyError. Automatically creates a default value for missing keys.

from collections import defaultdict
d = defaultdict(list)
d['missing'].append(1)  # No KeyError!

deque — a double-ended queue. Much faster than a list for appending or popping from both ends.

namedtuple — a tuple where you can access items by name instead of index.

The Cheat Sheet

Built-in	What it does	When to use it
`zip()`	Pairs up multiple iterables	Looping over two lists together
`any()`	True if at least one item passes	Checking if any condition is met
`all()`	True if every item passes	Validating a whole list
`enumerate()`	Gives index + value	When you need both in a loop
`map()`	Applies a function to each item	Simple transformations
`Counter`	Counts occurrences	Frequency analysis
`defaultdict`	Dict with default values	Avoiding KeyErrors

The Key Takeaway

None of these require installing anything. They’re all part of Python’s standard library, designed specifically for the problems you solve every day.

The difference between a junior and senior Python developer often isn’t the complex stuff — it’s knowing these small tools exist and reaching for them instead of writing loops from scratch.

Which one did you NOT know about before reading this? Comment below 👇

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