3 Python Tricks That Will Improve Your Code

Roman Orac
Aug 10, 2021

I’ve been coding in Python for more than 10 years. There was a time when I thought I knew it all, which was a clear sign I was getting complacent.

Then I decided to do a bit of research about Python improvements. Those 3.6, 3.7, 3.8 Python versions aren’t there for nothing, right?

After going through release notes, I found these neat tricks that I would like to share with you.

By reading this article, you’ll learn:
  • How to format big integers more clearly
  • A better way to work with file paths
  • The proper way of string formating

1. Formatting big integers

Using Underscores in Numeric Literals. Image by Roman Orac

From Python 3.6 (and onwards) you can use underscores to make numbers easier to read. See PEP 515 for more details.

Let’s look at an example:

a = 1000000000
# Is variable a billion or 100 millions?
# Let's use underscores to make it easier to read
a = 1_000_000_000
# You can group numbers as you like
b = 1_0_9_0

It also works with hexadecimal addresses and grouping bits.

# grouping hexadecimal addresses by words
addr = 0xCAFE_F00D
# grouping bits into nibbles in a binary literal
flags = 0b_0011_1111_0100_1110

2. Pathlib

Working with paths can be challenging especially if your code needs to run on multiple operating systems.

Luckily for us, Python standard library has pathllib.

Let’s look at an example:

from pathlib import Path
path = Path("some_folder")
# output: some_folder
# We can add more subfolders in a readable way
path = path / "sub_folder" / "sub_sub_folder"
# output: some_folder/sub_folder/sub_sub_folder
# make path absolute
# output: /Users/r.orac/some_folder/sub_folter/sub_sub_folder

Despite using / sign as the separator to concatenate paths, pathlib makes it operating system agnostic, meaning it will also work on Windows OS.

Also read: Using Python And Pandas Datareader to Analyze Financial Data

3. Simplify string formatting

f-string formatting in Python. Image by Roman Orac

I’m used to using old school string formatting in Python:

person = 'Roman'
exercise = 0
print("%d-times %s exercised during corona epidemic" % (exercise, person))
# output
# 0-times Roman exercised during corona epidemic

Until recently, I didn’t know there is a better (more modern) way of string formatting in Python.

In Python 3.6, PEP 498 introduces Literal String Interpolation, which simplifies the string formatting.

We can rewrite the example above to:

person = 'roman'
exercise = 0
print(f"{exercise}-times {person} exercised during corona epidemic")
# output
# 0-times Roman exercised during corona epidemic

A string prefixed with f is known as fstring.

fstrings even support math operations:

print(f"{exercise+1}-times {person} exercised during corona epidemic")
# Output
# '1-times roman exercised during corona epidemic'

But I didn’t exercise during the corona epidemic so adding +1 in the fstring would simply be a lie 😂

What about formatting float values?

f = 0.333333
print(f"this is f={f:.2f} rounded to 2 decimals")
# Output
this is f=0.33 rounded to 2 decimals


These Python tricks will make your code more concise and will make coding more enjoyable.

Many Python developers don’t know about these tricks — you’re not one of them anymore.

Before you go

Follow me on Twitter, where I regularly tweet about Data Science and Machine Learning.

Also read: Understanding Python's Collections Module

“3 Python Tricks That Will Improve Your Code”
– Roman Orac twitter social icon Tweet

Share this article:


Post a comment
Log In to Comment

Related Stories

Sep 25, 2021

10 Highly Probable Data Scientist Interview Questions

The popularity of data science attracts a lot of people from a wide range of professions to make a career change with the goal of becoming a data s...

Soner Yıldırım
By Soner Yıldırım
Sep 17, 2021

5 Google Chrome Extensions Every Data Scientist Should Know About

In this new post we will talk about the best Google Chrome extensions that as data scientists make certain tasks easier for us. You should at least...

Daniel Morales
By Daniel Morales
Sep 10, 2021

Data Scientists are Really Just Product Managers. Here’s Why.

Unpopular opinion?Table of ContentsIntroductionBusiness and Product UnderstandingStakeholder CollaborationSummaryReferencesIntroductionAs mentioned...

Matt Przybyla
By Matt Przybyla

Join our private community in Slack

Keep up to date by participating in our global community of data scientists and AI enthusiasts. We discuss the latest developments in data science competitions, new techniques for solving complex challenges, AI and machine learning models, and much more!

We'll send you an invitational link to your email immediatly.
arrow-up icon