Python Cheat Sheet: Syntax Reference on One Page

Python with AI Tutorial · Chapter 48 of 48

This Python cheat sheet puts the syntax from all 48 chapters of the course on one page: variables, strings, collections, control flow, functions, classes, files and pandas basics. Each table shows the statement, a short business-flavoured example and the result, and links to the chapter that explains it. Bookmark it and keep it open while you write code with or without an AI assistant.

Variables and data types

Chapters: Variables, Data Types, Casting, Booleans.

Syntax	Example	Result / note
Assign	`revenue = 26150`	int
Multiple assign	`qty, price = 4, 1100.0`	int, float
Type check	`type(price)`	`<class 'float'>`
Cast	`int("42")`, `float("3.5")`, `str(7)`	42, 3.5, ‘7’
Boolean	`paid = total > 0`	True / False
Truthiness	`bool("")`, `bool([])`, `bool(0)`	all False
None	`discount = None`	"no value yet"
Constants (convention)	`VAT_RATE = 0.18`	upper case, module level

Numbers and operators

Chapters: Numbers, Operators, Math.

Syntax	Example	Result
Arithmetic	`7 / 2`, `7 // 2`, `7 % 2`, `2 ** 10`	3.5, 3, 1, 1024
Round	`round(314.7255, 2)`	314.73
Compound assign	`total += 49.5`	adds and stores
Comparison	`a == b`, `a != b`, `a >= b`	bool
Logic	`paid and not overdue`, `x or y`	bool
Membership	`"North" in regions`	bool
math module	`math.ceil(4.2)`, `math.sqrt(16)`	5, 4.0
Big numbers	`1_000_000`	underscores allowed

Strings and formatting

Chapters: Strings, String Formatting, Regex.

Syntax	Example	Result
f-string	`f"Total: {total:,.2f}"`	Total: 2,063.23
Padding	`f"{name:<10}{qty:>4}"`	left / right align
Debug form	`f"{qty=}"`	qty=4
Slice	`"INV-2026-0042"[4:8]`	‘2026’
Case	`s.lower()`, `s.upper()`, `s.title()`	new string
Clean	`s.strip()`, `s.replace(",", "")`	new string
Split / join	`"a,b".split(",")`, `", ".join(items)`	list / string
Search	`s.startswith("INV")`, `s.find("-")`	bool / index or -1
Regex	`re.findall(r"\d{4}", s)`	list of matches

Lists, tuples and sets

Chapters: Lists, Tuples, Sets.

Syntax	Example	Result
Create	`sales = [4400, 2500, 1250]`	list (mutable)
Index / slice	`sales[0]`, `sales[-1]`, `sales[1:]`	4400, 1250, [2500, 1250]
Add / remove	`sales.append(900)`, `sales.pop()`, `sales.remove(2500)`	in place
Sort	`sorted(sales, reverse=True)`, `sales.sort()`	new list / in place
Aggregate	`sum(sales)`, `len(sales)`, `max(sales)`	8150, 3, 4400
Comprehension	`[s * 1.18 for s in sales if s > 2000]`	filtered new list
Tuple	`row = ("North", 46200)`; `region, rev = row`	immutable, unpack
Set	`set(["N", "S", "N"])`	{‘N’, ‘S’} unique
Set ops	`a \| b`, `a & b`, `a - b`	union, intersection, difference
Enumerate / zip	`for i, s in enumerate(sales, 1)`, `zip(a, b, strict=True)`	index pairs / parallel loop

Dictionaries

Chapter: Dictionaries.

Syntax	Example	Result
Create	`row = {"Region": "North", "Revenue": 46200}`	dict
Read	`row["Revenue"]`, `row.get("Units", 0)`	46200, 0 (no KeyError)
Write	`row["Units"] = 42`	adds or updates
Delete	`del row["Units"]`, `row.pop("Units", None)`	removes key
Loop	`for k, v in row.items():`	key, value pairs
Views	`row.keys()`, `row.values()`	iterables
Comprehension	`{r: t * 1.1 for r, t in totals.items()}`	new dict
Counting	`Counter(words).most_common(3)`	from collections
Merge	`{defaults, overrides}` or `a \| b`	right side wins

Control flow

Chapters: If Else, While Loops, For Loops.

Syntax	Example	Note
if / elif / else	`if n < 0: ... elif n == 0: ... else: ...`	colon + 4-space indent
Conditional expression	`label = "late" if days > 0 else "on time"`	one-line if
for	`for order in orders:`	over any iterable
range	`for i in range(1, 13):`	1 to 12
while	`while balance > 0:`	needs an exit condition
break / continue	`if not text: continue`; `if text == "quit": break`	skip / leave loop
match	`match status: case "paid": ... case _: ...`	Python 3.10+
pass	`def todo(): pass`	placeholder

Functions, lambda and scope

Chapters: Functions, Lambda, Scope.

Syntax	Example	Note
Define	`def net(price, vat=0.18): return price * (1 + vat)`	default argument
Type hints	`def net(price: float, vat: float = 0.18) -> float:`	documentation, not enforced
Keyword call	`net(100, vat=0.05)`	clearer than positional
args / *kwargs	`def log(items, *options):`	tuple / dict inside
Return several	`return total, count`; `t, c = f()`	tuple unpacking
Lambda	`sorted(rows, key=lambda r: r["Revenue"])`	one-expression function
Docstring	`"""Return net price."""`	first line of body
Scope	local inside function; `global x` to write a module variable	avoid global

Errors and exceptions

Chapters: Try Except, Debugging with AI.

Syntax	Example	Note
try / except	`try: float(s) except ValueError: ...`	catch specific types
Access error	`except KeyError as e: print(e)`	message in e
else / finally	`else:` runs if no error; `finally:` always	cleanup in finally
Raise	`raise ValueError("pct must be 0-100")`	your own checks
Custom error	`class BudgetError(Exception): pass`	subclass Exception
Debugger	`breakpoint()` then `p`, `n`, `c`, `q`	built-in pdb

Classes and inheritance

Chapters: Classes and Objects, Inheritance, Iterators and Generators.

Syntax	Example	Note
Class	`class Invoice:`	CapWords name
Constructor	`def __init__(self, number, total):`	self first
Attribute	`self.total = total`	per instance
Method	`def is_paid(self) -> bool:`	called as `inv.is_paid()`
String form	`def __str__(self): return f"Invoice {self.number}"`	used by print
Inherit	`class CreditNote(Invoice):`	reuse parent
Parent call	`super().__init__(number, -total)`	inside child __init__
Dataclass	`@dataclass class Row: region: str; revenue: float`	auto __init__, __repr__
Generator	`def rows(): yield row`	lazy iteration

Files, CSV and JSON

Chapters: File Handling, CSV, JSON.

Syntax	Example	Note
Read text	`with open("notes.txt", encoding="utf-8") as f: text = f.read()`	with closes the file
Write / append	`open("log.txt", "w")`, `open("log.txt", "a")`	w overwrites
Lines	`for line in f:`	memory friendly
pathlib	`Path("data") / "sales.csv"`, `p.exists()`, `p.read_text()`	modern file paths
CSV read	`for row in csv.DictReader(f):`	row is a dict
CSV write	`csv.writer(f).writerow([...])`	open with `newline=""`
JSON to text	`json.dumps(data, indent=2)`	string
JSON from text	`json.loads(text)`	dict / list
JSON file	`json.dump(data, f)`, `json.load(f)`	no s = file objects

Modules, dates, input and the web

Chapters: Modules and pip, Dates, User Input, Requests and APIs.

Syntax	Example	Note
Import	`import math`, `from datetime import date`, `import pandas as pd`	alias with as
Install	`pip install requests`	in the terminal, inside a venv
Today	`date.today()`, `datetime.now()`	date / datetime
Format	`f"{d:%d %b %Y}"`	05 Sep 2026
Parse	`datetime.strptime("2026-09-05", "%Y-%m-%d")`	string to datetime
Difference	`(due - today).days`, `d + timedelta(days=30)`	timedelta
Input	`age = int(input("Age: "))`	always returns str
HTTP GET	`requests.get(url, params={...}, timeout=10).json()`	check `raise_for_status()`
Env variable	`os.environ["OPENAI_API_KEY"]`	never hard-code keys

pandas basics

Chapters: NumPy, pandas, pandas with Excel, Matplotlib.

Syntax	Example	Note
Load	`pd.read_csv("sales.csv")`, `pd.read_excel("sales.xlsx", sheet_name="Data")`	DataFrame
Inspect	`df.head()`, `df.info()`, `df.describe()`, `df.shape`	first look
Select	`df["Revenue"]`, `df[["Region", "Revenue"]]`	Series / DataFrame
Filter	`df[df["Revenue"] > 10000]`, `df.query("Region == 'North'")`	boolean mask
New column	`df["Margin"] = df["Revenue"] - df["Cost"]`	vectorised
Group	`df.groupby("Region")["Revenue"].sum()`	add `.reset_index()` for a table
Pivot	`df.pivot_table(index="Region", columns="Product", values="Revenue", aggfunc="sum")`	Excel-style pivot
Sort / missing	`df.sort_values("Revenue", ascending=False)`, `df.dropna()`, `df.fillna(0)`	new DataFrame
Save	`df.to_excel("out.xlsx", index=False)`, `df.to_csv("out.csv", index=False)`	openpyxl for xlsx
Chart	`df.plot(kind="bar")`; `plt.savefig("chart.png")`	matplotlib

AI APIs in one glance

Chapters: Call an AI API, Chatbot, Automate Excel with AI.

Task	OpenAI	Anthropic
Install	`pip install openai`	`pip install anthropic`
Client	`client = OpenAI()`	`client = anthropic.Anthropic()`
Call	`client.responses.create(model="gpt-5", input="...")`	`client.messages.create(model="claude-sonnet-5", max_tokens=1024, messages=[...])`
Text	`r.output_text`	`m.content[0].text`
System prompt	`instructions="..."`	`system="..."`
Usage	`r.usage.input_tokens`	`m.usage.input_tokens`

Try it with AI

Turn any row of these tables into a worked example in seconds.

Give me a runnable Python 3.12 example, under 10 lines, that demonstrates df.pivot_table(index="Region", columns="Product", values="Revenue", aggfunc="sum") on a small DataFrame of six sales rows, and show the exact printed output.

Tip: when an assistant’s code uses a method that is not in these tables, check the official documentation before running it. Hallucinated method names such as df.sum_by() or list.add() look plausible and fail immediately.

Try it with AI

Use the sheet as a quiz generator.

Using only the Python topics variables, strings, lists, dictionaries, loops, functions and pandas basics, write 10 short quiz questions with a one-line answer each. Mix syntax questions with "what does this print" questions using small business examples. Do not show the answers until I ask.

Common mistakes

Forgetting the colon after if, for, def and class, and mixing tabs with spaces.
Treating input() results as numbers without casting.
Expecting sorted() or df.sort_values() to change the original in place; both return a new object.
Using == to compare with None; write is None.
Opening files without encoding="utf-8" and getting garbled accents on Windows.

Related chapters

FAQ

Is this Python cheat sheet enough to learn Python?

No, it is a reference. Work through the 48 chapters for explanations and exercises, then use this page to look up syntax while you build the projects.

Which Python version does the cheat sheet cover?

Python 3.12. Everything here also runs on 3.10 and later, including match statements, the dict union operator and zip with strict=True.

Can I print the Python cheat sheet?

Yes. Use your browser’s print function; the tables are plain HTML and fit on a few A4 pages in landscape orientation.

Working with spreadsheets too? Ready-made Excel, Google Sheets and Power BI templates are at NextGenTemplates.com.

Chapter 48 of 48 · Python with AI: all 48 chapters