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Python for AI: Syntax Cheat Sheet & Developer Lookup Guide

Tutorial Blog & Quick Reference
Grounded in "Python for AI - Full Beginner Course"
High-density, copy-pasteable lookup guide for AI developers, covering core Python syntax, environment setups, data operations, and modern workflows.

Table of Contents​

  1. Environment & Setup Reference
  2. Syntax, Variables & Data Types
  3. Control Flow & Operators
  4. Data Structures (Lists, Dicts, Tuples, Sets)
  5. Functions & Scope
  6. Modules, Packages & API Calls
  7. Data Analysis & Charts (Pandas & Matplotlib)
  8. Object-Oriented Programming (OOP)
  9. Error Handling & Debugging
  10. Modern Developer Toolkit (Git, ENV, Ruff & UV)

1. Environment & Setup Reference​

Terminal & Environment Commands​

# Verify Python version
python3 --version

# Create & Activate Virtual Environment
python3 -m venv venv
source venv/bin/activate  # macOS/Linux
.\venv\Scripts\activate   # Windows

# Managing Packages with Pip
pip install requests pandas matplotlib python-dotenv ruff
pip freeze > requirements.txt
pip install -r requirements.txt

Essential VS Code Keyboard Shortcuts​

  • Run Line in Interactive Window: Shift + Enter (Requires pip install ipykernel)
  • Run File in Terminal: Cmd + Enter or Ctrl + F5
  • Toggle Terminal: Cmd + J / Ctrl + J
  • Command Palette: Cmd + Shift + P / Ctrl + Shift + P

2. Syntax, Variables & Data Types​

PEP 8 Naming Rules​

  • Variables & Functions: snake_case (e.g., user_age, calculate_total)
  • Classes: PascalCase (e.g., DataValidator, APIConfig)
  • Constants: ALL_CAPS (e.g., MAX_RETRIES = 5, BASE_URL)
  • Indentation: Exactly 4 spaces per block level.

Variable Assignment & Data Types​

# String
model_name = "gpt-4o"

# Numbers
batch_size = 32          # Integer
learning_rate = 0.001    # Float

# Booleans
is_active = True
has_error = False

# Checking Types
print(type(model_name))  # <class "str">

Strings & F-Strings​

# F-Strings (Dynamic Format)
user_name = "Dave"
tokens = 150
summary = f"User {user_name} used {tokens} tokens."

# Essential String Methods
text = "  python for ai  "
print(text.strip())             # "python for ai" (Removes spaces)
print(text.upper())             # "  PYTHON FOR AI  "
print(text.title())             # "  Python For Ai  "
print(text.replace("ai", "ML")) # "  python for ML  "
print("python" in text)         # True (Substring test)

3. Control Flow & Operators​

Operators Quick Lookup​

OperatorMeaningExample
==Equal tox == 10
!=Not equal tostatus != "error"
> / <Greater / Less thanscore > 85
>= / <=Greater/Less or equalage >= 18
andTrue if both clauses are Truehas_key and is_active
orTrue if either clause is Trueis_admin or is_mod
notInverts boolean truth valuenot is_logged_in

Conditionals (if / elif / else)​

temperature = 28

if temperature > 30:
    status = "Hot"
elif temperature >= 20:
    status = "Optimal"
else:
    status = "Cold"

print(f"Status: {status}")

Loops Reference​

# Loop N times (0 to 4)
for i in range(5):
    print(f"Iteration: {i}")

# Custom Range: range(start, stop_before, step)
for count in range(10, 0, -2):
    print(count)  # 10, 8, 6, 4, 2

# While Loop
retries = 3
while retries > 0:
    print(f"Retrying... {retries} left")
    retries -= 1

4. Data Structures (Lists, Dicts, Tuples, Sets)​

1. Lists (Ordered, Mutable)​

# Definition
models = ["gpt-4o", "claude-3-5-sonnet", "llama-3"]

# Indexing & Slicing
first_item = models[0]       # "gpt-4o"
last_item = models[-1]       # "llama-3"
sliced_items = models[0:2]   # ["gpt-4o", "claude-3-5-sonnet"]

# Common Methods
models.append("gemini-1.5")  # Append to end
models.insert(1, "mistral")  # Insert at index 1
models.remove("llama-3")     # Remove by value
popped = models.pop(0)       # Remove by index
list_length = len(models)    # Total elements

2. Dictionaries (Key-Value Pairs)​

# Definition
config = {
    "model": "gpt-4o",
    "temperature": 0.7,
    "max_tokens": 1000
}

# Lookup & Modification
current_model = config["model"]           # "gpt-4o"
config["temperature"] = 0.2               # Modify value
config["stream"] = True                   # Add key

# Safe Lookup
temp = config.get("temperature", 0.5)     # Default 0.5 if missing

# Iteration
for key, value in config.items():
    print(f"{key}: {value}")

3. Tuples & Sets​

# Tuples (Immutable)
location = (37.7749, -122.4194)
lat, lon = location  # Unpacking

# Sets (Unique items)
raw_tags = ["ai", "python", "ai", "ml", "python"]
unique_tags = set(raw_tags)  # {"ai", "python", "ml"}
unique_tags.add("nlp")

5. Functions & Scope​

Function Syntax & Default Parameters​

def calculate_total(price: float, tax_rate: float = 0.08, discount: float = 0.0) -> float:
    """Calculates final order price including tax and optional discount."""
    subtotal = price * (1 - discount)
    final_price = subtotal * (1 + tax_rate)
    return round(final_price, 2)

# Calling with Keyword Arguments
total = calculate_total(price=100.0, discount=0.10)
print(f"Final Total: ${total}")

Returning Multiple Values​

def get_min_max(numbers: list):
    return min(numbers), max(numbers)

min_val, max_val = get_min_max([12, 45, 2, 89, 33])

6. Modules, Packages & API Calls​

Import Syntax​

import math                  # Standard module
from math import sqrt, pi    # Specific function
import pandas as pd          # Alias import

Fetching APIs with Requests​

import requests

url = "https://api.example.com/v1/weather"
params = {
    "latitude": 48.8566,
    "longitude": 2.3522,
    "current_weather": True
}

response = requests.get(url, params=params)

if response.status_code == 200:
    data = response.json()  # Parse JSON into dictionary
    temperature = data["current_weather"]["temperature"]
    print(f"Current Temperature: {temperature}°C")
else:
    print(f"API Error: {response.status_code}")

7. Data Analysis & Charts (Pandas & Matplotlib)​

Data Wrangling with Pandas​

import pandas as pd

# Load & Inspect
df = pd.read_csv("data/sales.csv")
print(df.head())

# Calculated Column
df["Total"] = df["Quantity"] * df["Price"]
high_value_df = df[df["Total"] > 100]

# Export
df.to_csv("output/processed_sales.csv", index=False)
df.to_json("output/processed_sales.json")

Plotting with Matplotlib​

import matplotlib.pyplot as plt

dates = ["2026-10-01", "2026-10-02", "2026-10-03", "2026-10-04"]
revenue = [1500, 2300, 1800, 3100]

plt.figure(figsize=(8, 4))
plt.plot(dates, revenue, marker="o", color="b", label="Daily Revenue ($)")
plt.title("Q4 Revenue Performance")
plt.xlabel("Date")
plt.ylabel("USD ($)")
plt.grid(True)
plt.legend()

plt.savefig("output/revenue_chart.png", dpi=150, bbox_inches="tight")
plt.close()

8. Object-Oriented Programming (OOP)​

Class Definition & Methods​

class APIConfig:
    """Class to manage environment configuration and model parameters."""

    def __init__(self, key_name: str, model_name: str = "gpt-4o"):
        self.key_name = key_name          # Attribute
        self.model_name = model_name      # Attribute
        self.request_count = 0            # Counter attribute

    def log_request(self):
        """Instance Method to track state."""
        self.request_count += 1
        print(f"[{self.model_name}] Request #{self.request_count} logged.")

# Instantiate Object & Call Method
dev_config = APIConfig(key_name="my_config_key", model_name="gpt-4o-mini")
dev_config.log_request()  # Output: [gpt-4o-mini] Request #1 logged.

9. Error Handling & Debugging​

try / except / else / finally Structure​

try:
    with open("data/config.json", "r") as file:
        content = file.read()
except FileNotFoundError:
    print("Error: Targeted file does not exist.")
except Exception as err:
    print(f"Unexpected error: {err}")
else:
    print("File content successfully loaded.")
finally:
    print("Completed file handler execution.")

10. Modern Developer Toolkit (Git, ENV, Ruff & UV)​

1. Environment Variables (.env)​

Store sensitive configuration in .env and add .env to .gitignore.

# Reading .env in Python
import os
from dotenv import load_dotenv

load_dotenv()  # Ingests .env key-value pairs

config_value = os.getenv("APP_ENV_KEY")
print(f"Loaded config state: {config_value is not None}")

2. Git Workflow Commands​

# Initialize & Add Remote
git init
git branch -M main
git add .
git commit -m "Initial commit"

# Daily Git Routine
git status
git add .
git commit -m "Updated data pipeline"
git push origin main

3. Ruff Linter & Formatter​

  • Install Ruff extension in VS Code.
  • Enable Format on Save in VS Code settings.
  • Instantly formats indentation, trailing commas, and unused imports upon saving files.

4. UV Package & Project Manager​

# Create Project
uv init my-ai-app
cd my-ai-app

# Add & Remove Dependencies
uv add requests pandas matplotlib python-dotenv
uv remove pandas

# Sync Environment
uv sync

Reference cheat sheet built for Python AI developers.