Python Tutorial: Conventions and PEP 8
Skills:
AI Workflow Automation60%
Key Takeaways
Covers Python conventions and PEP 8 guidelines
Original Description
Want to learn more? Take the full course at https://learn.datacamp.com/courses/software-engineering-for-data-scientists-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work.
---
Great work on those exercises.
In our short time together we've seen how helpful the Python community can be. Not only have they provided some excellent packages for us to use, but they've also provided documentation to help us use them.
Something you probably know from real life is that different cultures and communities follow different guidelines that help them run smoothly. For example, this can be seen in different greetings, depending on which community setting you're in it might make sense to say hello by shaking hands, bowing, or bumping fists. These unwritten rules are known as social conventions. The world of software engineering also has conventions that differ based on the language and community.
Luckily for Pythonistas, these conventions aren't unwritten. We can turn to Python Enhancement Protocol 8, or PEP 8. PEP 8 is the defacto Style Guide for Python Code. It lets us know how to format our code to be as readable as possible, and to quote PEP 8, 'code is read much more often than it is written'. So readability is not something that should be overlooked.
Let's see an example.
Here we have some code that violates PEP 8 best practices.
To put it simply, the code here is hard to the read. A few problems are: The module import isn't at the top of the file, the spacing and indentation is inconsistent, and the lack of line breaks makes it difficult to tell when one idea finishes and the next begins.
Even without knowing the specific PEP 8 rules being broken, you can probably tell this isn't the most readable chunk of code.
Let's see what the same chunk of code looks like after being rewritten to conform to PEP 8. Much better.
By following the agreed-upon rules in PEP 8 and using whitespace appropriately, th
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Playlist
Uploads from DataCamp · DataCamp · 0 of 60
← Previous
Next →
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
SQL Server Tutorial: Date manipulation
DataCamp
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
R Tutorial: Adding aesthetics to represent a variable
DataCamp
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
Python Tutorial: Preparation for modeling
DataCamp
Python Tutorial: Machine Learning modeling steps
DataCamp
R Tutorial: The prior model
DataCamp
R Tutorial: Data & the likelihood
DataCamp
R Tutorial: The posterior model
DataCamp
R Tutorial: An Introduction to plotly
DataCamp
R Tutorial: Plotting a single variable
DataCamp
R Tutorial: Bivariate graphics
DataCamp
Python Tutorial: Customer Segmentation in Python
DataCamp
Python Tutorial: Time cohorts
DataCamp
Python Tutorial: Calculate cohort metrics
DataCamp
Python Tutorial: Cohort analysis visualization
DataCamp
R Tutorial: Building Dashboards with flexdashboard
DataCamp
R Tutorial: Anatomy of a flexdashboard
DataCamp
R Tutorial: Layout basics
DataCamp
R Tutorial: Advanced layouts
DataCamp
Python Tutorial: Time Series Analysis in Python
DataCamp
Python Tutorial: Correlation of Two Time Series
DataCamp
Python Tutorial: Simple Linear Regressions
DataCamp
Python Tutorial: Autocorrelation
DataCamp
R Tutorial: The gapminder dataset
DataCamp
R Tutorial: The filter verb
DataCamp
R Tutorial: The arrange verb
DataCamp
R Tutorial: The mutate verb
DataCamp
R Tutorial: What is cluster analysis?
DataCamp
R Tutorial: Distance between two observations
DataCamp
R Tutorial: The importance of scale
DataCamp
R Tutorial: Measuring distance for categorical data
DataCamp
Python Tutorial: Plotting multiple graphs
DataCamp
Python Tutorial: Customizing axes
DataCamp
Python Tutorial: Legends, annotations, & styles
DataCamp
Python Tutorial: Introduction to iterators
DataCamp
Python Tutorial: Playing with iterators
DataCamp
Python Tutorial: Using iterators to load large files into memory
DataCamp
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
SQL Tutorial: Tables: At the core of every database
DataCamp
SQL Tutorial: Update your database as the structure changes
DataCamp
Python Tutorial: Classification-Tree Learning
DataCamp
Python Tutorial: Decision-Tree for Classification
DataCamp
Python Tutorial: Decision-Tree for Regression
DataCamp
Python Tutorial: Census Subject Tables
DataCamp
Python Tutorial: Census Geography
DataCamp
Python Tutorial: Using the Census API
DataCamp
R Tutorial: A/B Testing in R
DataCamp
R Tutorial: Baseline Conversion Rates
DataCamp
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
R Tutorial: Introduction to qualitative data
DataCamp
R Tutorial: Understanding your qualitative variables
DataCamp
R Tutorial: Making Better Plots
DataCamp
SQL Tutorial: OLTP and OLAP
DataCamp
SQL Tutorial: Storing data
DataCamp
SQL Tutorial: Database design
DataCamp
Python Tutorial: Introduction to spaCy
DataCamp
Python Tutorial: Statistical Models
DataCamp
Python Tutorial: Rule-based Matching
DataCamp
More on: AI Workflow Automation
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
X now offers an MCP server to make its platform easier for AI tools to use
TechCrunch AI
n8n Automation Repurpose Video Content: The 2025 Production Guide
Dev.to AI
You’re Still Paying $200/Month for AI Tools You Could Replace With a Free Local Setup Tonight
Medium · Data Science
Top 10 AI Tools Every College Student Should Know in 2026
Medium · AI
🎓
Tutor Explanation
DeepCamp AI