Week 1 - Python Foundations

Overview

Python Setup

Data Types and Variables

Control Flow: Logic and Loops

Functions and Modules

Type Hints for Clearer Code

Command-Line Interface Habits

🐛 Errors and Debugging

📝 Logging in Python

File Operations

Azure Setup and Account Access

🛠️ Practice

🎒 Assignment

⚠️ Gotchas & Pitfalls

🗓️ Lesson Plan

Control Flow: Logic and Loops

Data engineering is all about processing streams of data. To do that, you need to make decisions (conditionals) and repeat actions (loops). This lesson covers the logic you'll use in almost every script.

Conditionals (if/elif/else)

Conditionals let your code make decisions based on data.

Basic Syntax

score = 85

if score >= 90:
    print("Grade: A")
elif score >= 80:
    print("Grade: B")
else:
    print("Grade: C or lower")

Checking for "Truthiness"

Python allows you to check if lists, strings, or numbers are "empty" or "zero" directly:

# Check if a list has items
users = []
if not users:
    print("No users found!")

# Check if a string is missing
name = None
if not name:
    print("Name is missing")

# Check if a number is non-zero
count = 0
if count:
    print(f"Count is {count}")
else:
    print("Count is zero")

Loops

for Loops

Use for loops when you want to iterate over a collection (like a list of files or rows in a CSV).

# Loop over a list
files = ["data1.csv", "data2.csv", "data3.csv"]
for filename in files:
    print(f"Processing {filename}...")

# Loop with an index using enumerate()
for i, filename in enumerate(files):
    print(f"File {i+1}: {filename}")

# Loop over a dictionary
user = {"name": "Alice", "role": "Engineer"}
for key, value in user.items():
    print(f"{key}: {value}")

while Loops

Use while loops when you don't know how many times to repeat, but you have a condition to stop (e.g., waiting for a file to appear, or retrying a network request).

import time

retries = 3
while retries > 0:
    print(f"Connecting to database... ({retries} retries left)")
    # simulate connection attempt
    success = False 

    if success:
        print("Connected!")
        break  # Exit the loop immediately

    retries -= 1
    time.sleep(1) # Wait 1 second before retrying

if retries == 0:
    print("Failed to connect.")

break and continue

• break: Exits the loop entirely.
• continue: Skips the rest of the current iteration and jumps to the next one.

records = [10, 20, -1, 30, -5, 40]

valid_records = []
for record in records:
    if record < 0:
        print(f"Skipping invalid record: {record}")
        continue  # Skip negative numbers

    if record > 50:
        print("Limit reached, stopping.")
        break     # Stop processing if value is too high

    valid_records.append(record)

List Comprehensions

List comprehensions are a concise, "Pythonic" way to create lists. They are extremely popular in data engineering for simple transformations.

Syntax

# [expression for item in iterable if condition]

Examples

1. Transform a list (Map)

# Old way
numbers = [1, 2, 3, 4]
squared = []
for num in numbers:
    squared.append(num * 2)

# List comprehension way
squared = [num * 2 for num in numbers]
# Result: [2, 4, 6, 8]

2. Filter a list

# Get only even numbers
evens = [num for num in numbers if num % 2 == 0]

3. Clean data strings

raw_names = ["  Alice ", "Bob", "  Charlie  "]
clean_names = [name.strip().lower() for name in raw_names]
# Result: ['alice', 'bob', 'charlie']

<aside> ⚠️ Pro Tip: If your list comprehension is getting too complex (e.g., nested loops or multiple distinct conditions), switch back to a regular for loop for readability.

</aside>

Nested Loops

Sometimes you need to loop loop inside a loop.

departments = {
    "Engineering": ["Alice", "Bob"],
    "Sales": ["Charlie", "David"]
}

for dept, employees in departments.items():
    print(f"--- {dept} ---")
    for employee in employees:
        print(f"  - {employee}")

Output:

--- Engineering ---
  - Alice
  - Bob
--- Sales ---
  - Charlie
  - David

This pattern is useful when processing grouped data (e.g., records by department, transactions by customer).

Try it yourself

Test your understanding of loops and logic with this interactive exercise:

[HYF-Teach Interactive Check]

<aside> 🚀 Open the HYF-Teach Widget: asse.be/simple-hyf-teach-widget

</aside>

Challenge: The code in the widget loops through a list but has logic errors. Use break and continue to filter the data correctly as per the instructions in the widget.

🧠 Knowledge Check

1. What is the "truthiness" of an empty list [] in Python?
2. When would you use a while loop instead of a for loop?
3. How would you rewrite this loop as a list comprehension: squared = []; for x in range(5): squared.append(x**2)?

Cheatsheet

Conditionals

if x > 10:
    pass
elif x == 5:
    pass
else:
    pass

Loops

## For loop

for item in items:

    # do something

## With index

for index, item in enumerate(items):

    # do something

## List Comprehension

new_list = [transform(x) for x in old_list if condition(x)]

## Dictionary Iteration

for key, value in my_dict.items():

    # do something

Control

• break: stop loop
• continue: skip to next iteration
• pass: do nothing (placeholder)

Next lesson: Functions and Modules

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