Python Functions — Writing Your Own Tools

A function is a reusable chunk of code with a name. You'll write three, add type hints, and let AI suggest better names and docstrings.

30 min · Reviewed 2026

def name(): the magic word

A function packages logic so you can call it by name anywhere. Name it clearly and your code reads like a story. Name it 'do_stuff' and your future self will curse your past self.

def greet(name: str, enthusiasm: int = 1) -> str: """Return a friendly greeting. Args: name: the person to greet enthusiasm: number of exclamation marks (default 1) """ bangs = "!" * enthusiasm return f"Hello, {name}{bangs}" print(greet("Maya")) print(greet("Maya", enthusiasm=5))Type hints (: str, -> str) are optional but massively improve both human and AI understanding.

Parameters, arguments, defaults

A parameter is the name in the definition (name, enthusiasm)
An argument is the value you pass when calling ("Maya", 5)
Defaults let callers skip arguments — use them to keep simple calls simple
Keyword arguments (enthusiasm=5) make calls self-documenting

Return vs. print — the classic beginner mix-up

def add_broken(a, b): print(a + b) # shows the answer — but returns None def add_good(a, b): return a + b # gives the answer back to the caller result = add_broken(2, 3) # prints 5, but result is None total = add_good(2, 3) # total is 5 — usable print(result * 2) # TypeError: NoneType print(total * 2) # 10If a function needs to be usable in another function, it must return, not print.

Mini-exercise: price calculator

Write calc_total(items: list[float], tax_rate: float = 0.08) -> float
Return the sum of items times (1 + tax_rate), rounded to 2 decimals
Add a docstring
Call it with [3.50, 4.25, 1.99] and print the result
Ask your AI assistant to review your code and suggest improvements

Loose function	Tight function
def do(x)	def fetch_user(user_id: int) -> dict
No docstring	Docstring with Args and Returns
Prints results	Returns results
Hard to test	Easy to test

Big idea: a function is a small contract. Its name says what it does, its signature says how to use it, its docstring says why. AI pair-programming gets dramatically better when you tighten those three things up first.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-prog-python-functions-builders

What is the main idea of "Python Functions — Writing Your Own Tools"?
1. A function is a reusable chunk of code with a name. You'll write three, add type hints, and let AI suggest better names and docstrings.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Python Functions — Writing Your Own Tools"?
1. parameters
2. functions
3. return
4. type hints
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. A parameter is the name in the definition (name, enthusiasm)
4. Use the first answer without checking it
What should a careful learner remember about "Docstrings make AI smarter"?
1. Use "Docstrings make AI smarter" as a reminder to verify the AI output before anyone relies on it.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use the AI answer as a draft, then check it against a reliable source.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about functions be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about functions.
Which action would help you apply "Python Functions — Writing Your Own Tools" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Use the first answer without checking it
4. An argument is the value you pass when calling ("Maya", 5)

← Back to interactive lesson

Tendril · Builders · AI-Assisted Coding

Python Functions — Writing Your Own Tools

A function is a reusable chunk of code with a name. You'll write three, add type hints, and let AI suggest better names and docstrings.

30 min · Reviewed 2026

def name(): the magic word

A function packages logic so you can call it by name anywhere. Name it clearly and your code reads like a story. Name it 'do_stuff' and your future self will curse your past self.

def greet(name: str, enthusiasm: int = 1) -> str: """Return a friendly greeting. Args: name: the person to greet enthusiasm: number of exclamation marks (default 1) """ bangs = "!" * enthusiasm return f"Hello, {name}{bangs}" print(greet("Maya")) print(greet("Maya", enthusiasm=5))Type hints (: str, -> str) are optional but massively improve both human and AI understanding.

Parameters, arguments, defaults

A parameter is the name in the definition (name, enthusiasm)
An argument is the value you pass when calling ("Maya", 5)
Defaults let callers skip arguments — use them to keep simple calls simple
Keyword arguments (enthusiasm=5) make calls self-documenting

Return vs. print — the classic beginner mix-up

def add_broken(a, b): print(a + b) # shows the answer — but returns None def add_good(a, b): return a + b # gives the answer back to the caller result = add_broken(2, 3) # prints 5, but result is None total = add_good(2, 3) # total is 5 — usable print(result * 2) # TypeError: NoneType print(total * 2) # 10If a function needs to be usable in another function, it must return, not print.

Mini-exercise: price calculator

Write calc_total(items: list[float], tax_rate: float = 0.08) -> float
Return the sum of items times (1 + tax_rate), rounded to 2 decimals
Add a docstring
Call it with [3.50, 4.25, 1.99] and print the result
Ask your AI assistant to review your code and suggest improvements

Loose function	Tight function
def do(x)	def fetch_user(user_id: int) -> dict
No docstring	Docstring with Args and Returns
Prints results	Returns results
Hard to test	Easy to test

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-prog-python-functions-builders

What is the main idea of "Python Functions — Writing Your Own Tools"?
1. A function is a reusable chunk of code with a name. You'll write three, add type hints, and let AI suggest better names and docstrings.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Python Functions — Writing Your Own Tools"?
1. parameters
2. functions
3. return
4. type hints
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. A parameter is the name in the definition (name, enthusiasm)
4. Use the first answer without checking it
What should a careful learner remember about "Docstrings make AI smarter"?
1. Use "Docstrings make AI smarter" as a reminder to verify the AI output before anyone relies on it.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use the AI answer as a draft, then check it against a reliable source.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about functions be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about functions.
Which action would help you apply "Python Functions — Writing Your Own Tools" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Use the first answer without checking it
4. An argument is the value you pass when calling ("Maya", 5)

← Back to interactive lesson