Comprehensions and module checkpoint

You asked about shorter ways to write loops, and Python delivers. Comprehensions let you create new lists (or dicts) in a single line by combining a loop and an optional filter. AI code uses them everywhere for transforming data.

Now for one of Python's most powerful features: comprehensions. They let you create new lists (or dicts) in a single line by combining a loop and an optional filter. AI code uses them everywhere for transforming data.

control_flow.py
python
# List comprehensions (used everywhere in AI code)
scores = [3, 5, 1, 4, 2, 5, 3]

# Filter: keep only high scores
high_scores = [s for s in scores if s >= 4]
print(f"High scores: {high_scores}")  # [5, 4, 5]

# Transform: from the text-to-sql agent
sql_query = "SELECT * FROM orders; SELECT * FROM items; "
statements = [s.strip() for s in sql_query.split(";") if s.strip()]
print(f"SQL statements: {statements}")

Comprehensions create new lists in one line. The pattern is [expression for item in iterable if condition]. AI code uses these constantly for filtering and transforming data.

The same comprehension idea works for dictionaries too. Instead of square brackets, you use curly braces and provide both a key and a value.

control_flow.py
python
# Dict comprehension: same idea, but creates a dictionary
names = ["alice", "bob"]
name_lengths = {name: len(name) for name in names}
print(name_lengths)  # {'alice': 5, 'bob': 3}

Dict comprehensions use {key: value for item in iterable}. They create dictionaries the same way list comprehensions create lists.

Quiz: Quiz

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Ordering exercise: Agent retry loop steps

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Validation checklist: Control flow checklist

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Checkpoint: Python essentials checkpoint

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Timed quiz: Python essentials speed round

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