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Compose has one rule: Composable functions should be pure. They take state in and produce UI out. No database calls. No API requests. No timers. No logging. But real apps need those things. You need to start a timer when a screen opens. You need to load data when an ID changes. You need to clean up a listener when a screen closes. That is what side effects are for. They let you safely run “impure” code inside Compose. ...

Bookmark this page. Use Ctrl+F (or Cmd+F on Mac) to find what you need. This cheat sheet covers Python syntax from basics to advanced patterns. Try examples at pythontutor.com. Last updated: March 2026 Variables and Types name = "Alex" # str age = 25 # int height = 1.75 # float is_active = True # bool nothing = None # NoneType Type Example Notes int 42 No size limit float 3.14 64-bit decimal str "hello" Immutable bool True, False Capitalized None None Null equivalent list [1, 2, 3] Mutable, ordered tuple (1, 2, 3) Immutable, ordered dict {"a": 1} Key-value pairs set {1, 2, 3} Unique values, unordered Type Conversions int("42") # 42 float("3.14") # 3.14 str(42) # "42" list((1, 2, 3)) # [1, 2, 3] tuple([1, 2, 3]) # (1, 2, 3) set([1, 1, 2]) # {1, 2} bool(0) # False bool("") # False bool([]) # False bool("hello") # True Strings name = "Alex" f"Hello {name}" # f-string: Hello Alex f"Age: {age + 1}" # f-string with expression f"{price:.2f}" # format: 9.99 f"{name!r}" # repr: 'Alex' f"{num:,}" # thousands separator: 1,000,000 f"{value:>10}" # right-align, width 10 f"{value:<10}" # left-align, width 10 # Common methods "hello".upper() # "HELLO" "HELLO".lower() # "hello" "hello world".title() # "Hello World" " hello ".strip() # "hello" "hello world".split() # ["hello", "world"] "hello world".split("o") # ["hell", " w", "rld"] ", ".join(["a", "b", "c"]) # "a, b, c" "hello".replace("l", "r") # "herro" "hello".startswith("he") # True "hello".endswith("lo") # True "hello world".find("world") # 6 (-1 if not found) "hello world".count("l") # 3 "42".isdigit() # True # Multi-line strings text = """ First line Second line """ # Raw strings (no escape processing) path = r"C:\Users\name\folder" Lists nums = [1, 2, 3, 4, 5] # Access nums[0] # 1 (first) nums[-1] # 5 (last) nums[1:3] # [2, 3] (slice) nums[:3] # [1, 2, 3] (first 3) nums[2:] # [3, 4, 5] (from index 2) nums[::2] # [1, 3, 5] (every 2nd) nums[::-1] # [5, 4, 3, 2, 1] (reversed) # Modify nums.append(6) # add to end nums.insert(0, 0) # insert at index nums.extend([7, 8]) # add multiple nums.remove(3) # remove first occurrence nums.pop() # remove and return last nums.pop(0) # remove and return at index nums.sort() # sort in place nums.sort(reverse=True) # sort descending nums.reverse() # reverse in place nums.clear() # remove all # Functions len(nums) # length min(nums) # smallest max(nums) # largest sum(nums) # total sorted(nums) # new sorted list reversed(nums) # reversed iterator Dictionaries user = {"name": "Alex", "age": 25, "city": "Berlin"} # Access user["name"] # "Alex" (KeyError if missing) user.get("name") # "Alex" user.get("phone", "N/A") # "N/A" (default if missing) # Modify user["age"] = 26 # update user["email"] = "alex@mail.com" # add new key del user["city"] # delete key user.pop("age") # remove and return value # Iterate user.keys() # dict_keys(["name", "age", ...]) user.values() # dict_values(["Alex", 25, ...]) user.items() # dict_items([("name", "Alex"), ...]) for key, value in user.items(): print(f"{key}: {value}") # Merge (Python 3.9+) merged = dict1 | dict2 # dict2 values win on conflict Sets and Tuples # Sets — unique values, unordered colors = {"red", "green", "blue"} colors.add("yellow") colors.remove("red") # KeyError if missing colors.discard("red") # no error if missing a | b # union a & b # intersection a - b # difference a ^ b # symmetric difference # Tuples — immutable point = (10, 20) x, y = point # unpacking name, *rest = ("Alex", 25, "Berlin") # name="Alex", rest=[25, "Berlin"] Control Flow # if / elif / else if age < 18: print("minor") elif age < 65: print("adult") else: print("senior") # Ternary status = "adult" if age >= 18 else "minor" # for loop for item in items: print(item) for i in range(5): # 0, 1, 2, 3, 4 for i in range(2, 10): # 2, 3, ..., 9 for i in range(0, 10, 2): # 0, 2, 4, 6, 8 for i, item in enumerate(items): # index + value print(f"{i}: {item}") for a, b in zip(list1, list2): # parallel iteration print(a, b) # while loop while count > 0: count -= 1 # break / continue for item in items: if item == "skip": continue # skip this iteration if item == "stop": break # exit loop Pattern Matching (Python 3.10+) match status_code: case 200: print("OK") case 404: print("Not Found") case 500: print("Server Error") case _: print(f"Unknown: {status_code}") # Match with destructuring match point: case (0, 0): print("Origin") case (x, 0): print(f"On x-axis at {x}") case (0, y): print(f"On y-axis at {y}") case (x, y): print(f"Point at ({x}, {y})") # Match with guards match user: case {"role": "admin", "name": name}: print(f"Admin: {name}") case {"role": "user", "name": name} if name != "blocked": print(f"User: {name}") Comprehensions # List comprehension squares = [x**2 for x in range(10)] evens = [x for x in nums if x % 2 == 0] pairs = [(x, y) for x in range(3) for y in range(3)] # Dict comprehension word_lengths = {word: len(word) for word in words} filtered = {k: v for k, v in data.items() if v > 0} # Set comprehension unique_lengths = {len(word) for word in words} # Generator expression (lazy, memory-efficient) total = sum(x**2 for x in range(1000000)) Functions # Basic function def greet(name): return f"Hello {name}" # Default parameters def greet(name="World"): return f"Hello {name}" # *args and **kwargs def func(*args, **kwargs): print(args) # tuple of positional args print(kwargs) # dict of keyword args # Lambda double = lambda x: x * 2 sorted(users, key=lambda u: u["age"]) # Type hints (Python 3.10+) def greet(name: str) -> str: return f"Hello {name}" def process(items: list[int]) -> dict[str, int]: return {"sum": sum(items), "count": len(items)} Classes class User: def __init__(self, name: str, age: int): self.name = name self.age = age def greet(self) -> str: return f"Hi, I'm {self.name}" def __repr__(self) -> str: return f"User({self.name!r}, {self.age})" user = User("Alex", 25) # Dataclass (Python 3.7+) — auto-generates __init__, __repr__, __eq__ from dataclasses import dataclass @dataclass class User: name: str age: int city: str = "Unknown" # Inheritance class Admin(User): def __init__(self, name, age, level): super().__init__(name, age) self.level = level Error Handling try: result = 10 / 0 except ZeroDivisionError: print("Cannot divide by zero") except (ValueError, TypeError) as e: print(f"Error: {e}") else: print("Success") # runs if no exception finally: print("Always runs") # cleanup # Raise an exception raise ValueError("Invalid input") File I/O # Read entire file with open("file.txt", "r") as f: content = f.read() # Read lines with open("file.txt", "r") as f: lines = f.readlines() # list of lines # or for line in f: print(line.strip()) # Write with open("file.txt", "w") as f: # overwrite f.write("Hello\n") with open("file.txt", "a") as f: # append f.write("More text\n") # JSON import json data = json.loads('{"name": "Alex"}') # parse string text = json.dumps(data, indent=2) # to string with open("data.json", "r") as f: data = json.load(f) # parse file with open("data.json", "w") as f: json.dump(data, f, indent=2) # write file Async / Await import asyncio async def fetch_data(url: str) -> str: # simulate async work await asyncio.sleep(1) return f"Data from {url}" # Run async function async def main(): result = await fetch_data("https://api.example.com") print(result) asyncio.run(main()) # Run tasks in parallel async def main(): results = await asyncio.gather( fetch_data("https://api1.example.com"), fetch_data("https://api2.example.com"), ) print(results) # both complete in ~1 second, not 2 Common Built-in Functions Function Description Example len(x) Length len([1,2,3]) → 3 range(n) Sequence 0..n-1 range(5) → 0,1,2,3,4 enumerate(x) Index + value enumerate(["a","b"]) zip(a, b) Pair elements zip([1,2], ["a","b"]) map(fn, x) Apply function map(str, [1,2,3]) filter(fn, x) Filter elements filter(bool, [0,1,"",2]) any(x) True if any truthy any([False, True]) → True all(x) True if all truthy all([True, True]) → True sorted(x) New sorted list sorted([3,1,2]) → [1,2,3] reversed(x) Reversed iterator list(reversed([1,2,3])) isinstance(x, type) Type check isinstance(42, int) → True type(x) Get type type(42) → <class 'int'> dir(x) List attributes dir([]) help(x) Show docs help(str.split) Virtual Environments python -m venv .venv # create source .venv/bin/activate # activate (macOS/Linux) .venv\Scripts\activate # activate (Windows) pip install requests # install package pip freeze > requirements.txt # save dependencies pip install -r requirements.txt # install from file deactivate # deactivate Common Mistakes Mutable default arguments — def add(item, items=[]) shares the same list across all calls. Use def add(item, items=None) and items = items or [] inside the function. ...

In Tutorial #5, we learned about remember and mutableStateOf. They work great for simple state. But they have a big problem — when your app needs to load data from a database or API, where does that logic go? Not in the Composable. Composables are for UI, not business logic. That is what ViewModel is for. What is ViewModel? ViewModel is a class that holds your screen’s data and logic. It survives things that destroy and recreate your Composable — like screen rotation or system theme changes. ...

One AI agent is powerful. But what if you had a team of AI agents — each specialized in a different job — working together on the same project? That is what multi-agent AI systems do. And they are changing how software gets built in 2026. What is a Multi-Agent System? Instead of one AI assistant that does everything, a multi-agent system splits the work between specialized agents: ┌──────────────┐ │ Architect │ Plans the solution, defines the structure └──────┬───────┘ ↓ ┌──────────────┐ ┌──────────────┐ │ Backend Dev │ │ Frontend Dev │ Build code in parallel └──────┬───────┘ └──────┬───────┘ ↓ ↓ ┌──────────────────────────────────┐ │ QA / Testing │ Runs tests, reports bugs └──────────────────────────────────┘ Each agent has: ...

Bookmark this page. Use Ctrl+F (or Cmd+F on Mac) to find what you need. This cheat sheet covers SQL from basic queries to window functions and performance. Try examples at db-fiddle.com. Last updated: March 2026 SELECT Basics SELECT * FROM users; -- all columns SELECT name, email FROM users; -- specific columns SELECT DISTINCT city FROM users; -- unique values SELECT name AS full_name FROM users; -- column alias SELECT * FROM users LIMIT 10; -- first 10 rows SELECT * FROM users LIMIT 10 OFFSET 20; -- rows 21-30 (pagination) WHERE — Filtering Rows SELECT * FROM users WHERE age > 18; SELECT * FROM users WHERE city = 'Berlin'; SELECT * FROM users WHERE age BETWEEN 18 AND 30; SELECT * FROM users WHERE city IN ('Berlin', 'Munich', 'Hamburg'); SELECT * FROM users WHERE name LIKE 'A%'; -- starts with A SELECT * FROM users WHERE name LIKE '%son'; -- ends with son SELECT * FROM users WHERE name LIKE '%alex%'; -- contains alex SELECT * FROM users WHERE email IS NULL; -- null check SELECT * FROM users WHERE email IS NOT NULL; SELECT * FROM users WHERE age > 18 AND city = 'Berlin'; SELECT * FROM users WHERE age > 65 OR age < 18; SELECT * FROM users WHERE NOT city = 'Berlin'; ORDER BY and LIMIT SELECT * FROM users ORDER BY name; -- ascending (default) SELECT * FROM users ORDER BY age DESC; -- descending SELECT * FROM users ORDER BY city, name; -- multiple columns SELECT * FROM users ORDER BY age DESC LIMIT 5; -- top 5 oldest INSERT, UPDATE, DELETE -- Insert one row INSERT INTO users (name, email, age) VALUES ('Alex', 'alex@example.com', 25); -- Insert multiple rows INSERT INTO users (name, email, age) VALUES ('Sam', 'sam@example.com', 30), ('Jordan', 'jordan@example.com', 22); -- Update UPDATE users SET age = 26 WHERE name = 'Alex'; -- Update multiple columns UPDATE users SET city = 'Munich', age = 27 WHERE id = 1; -- Delete DELETE FROM users WHERE id = 5; -- Delete all rows (use with caution!) DELETE FROM users; -- Faster delete all (resets table) TRUNCATE TABLE users; -- UPSERT — insert or update if exists (PostgreSQL) INSERT INTO users (email, name) VALUES ('alex@example.com', 'Alex') ON CONFLICT (email) DO UPDATE SET name = EXCLUDED.name; -- MySQL equivalent INSERT INTO users (email, name) VALUES ('alex@example.com', 'Alex') ON DUPLICATE KEY UPDATE name = VALUES(name); Warning: Always use WHERE with UPDATE and DELETE. Without it, every row is affected. ...

Welcome to Part 2 of the series. You can now build beautiful single-screen apps. But real apps have many screens — a home screen, a detail screen, a settings screen, a profile screen. Navigation is how you move between them. In this tutorial, you will learn everything about Compose navigation: Setting up navigation Creating screens and routes Type-safe navigation with Kotlin Serialization Passing data between screens Bottom navigation bar Nested navigation graphs Back stack management Best practices This is a long tutorial. Take your time. ...

Every AI coding tool has the same problem: it can read your code, but it can’t access your database. It can’t check your Jira tickets. It can’t read your Slack messages. It can’t query your production logs. Until now. MCP (Model Context Protocol) is a new standard that lets AI tools connect to anything — databases, APIs, file systems, project management tools, and more. It is like a USB-C port for AI. One standard connection that works with everything. ...

Bookmark this page. Use Ctrl+F (or Cmd+F on Mac) to find what you need. This cheat sheet covers Docker CLI commands, Dockerfile instructions, Docker Compose, volumes, networking, and production tips. Last updated: March 2026 How Docker Works ┌──────────────┐ docker build ┌──────────┐ docker run ┌────────────┐ │ Dockerfile │ ───────────────► │ Image │ ─────────────► │ Container │ │ (recipe) │ │ (template)│ │ (running) │ └──────────────┘ └──────────┘ └────────────┘ │ docker push │ ┌────▼───────┐ │ Registry │ │ (Docker Hub)│ └────────────┘ Container Commands Command Description docker run <image> Create and start a container docker run -d <image> Run in background (detached) docker run -it <image> bash Run interactively with shell (sh for Alpine) docker run -p 8080:80 <image> Map host port 8080 to container port 80 docker run --name myapp <image> Run with a custom name docker run --rm <image> Automatically remove container when it stops docker run -e KEY=value <image> Set environment variable docker run -v /host:/container <image> Mount a volume docker ps List running containers docker ps -a List all containers (including stopped) docker stop <container> Stop a running container docker start <container> Start a stopped container docker restart <container> Restart a container docker rm <container> Remove a stopped container docker rm -f <container> Force remove (even if running) docker exec -it <container> bash Open a shell inside a running container docker logs <container> View container logs docker logs -f <container> Follow logs in real-time docker inspect <container> Show detailed container info (JSON) docker stats Live resource usage for all containers docker cp <container>:/path ./local Copy file from container to host docker cp ./local <container>:/path Copy file from host to container docker container prune Remove all stopped containers docker kill <container> Force stop a container (SIGKILL) Image Commands Command Description docker images List all local images docker pull <image> Download an image from registry docker push <image> Upload an image to registry docker build -t myapp . Build image from Dockerfile in current dir docker build -t myapp:v1 . Build with a tag/version docker tag <image> <new-tag> Add a tag to an image docker rmi <image> Remove an image docker image prune Remove unused (dangling) images docker system prune -a Remove all unused images, containers, networks (not volumes) docker system prune -a --volumes Remove everything including volumes docker history <image> Show image layers and sizes docker login Log in to Docker Hub (required before push) docker logout Log out from registry docker save -o image.tar <image> Export image to tar file docker load -i image.tar Import image from tar file Dockerfile Reference # Base image FROM node:20-alpine # Set working directory WORKDIR /app # Copy dependency files first (for caching) COPY package.json package-lock.json ./ # Install dependencies RUN npm ci --production # Copy application code COPY . . # Expose a port (documentation only) EXPOSE 3000 # Default command when container starts CMD ["node", "server.js"] Dockerfile Instructions Instruction Description FROM <image> Base image (required, must be first) WORKDIR /app Set working directory for subsequent commands COPY <src> <dest> Copy files from host to image ADD <src> <dest> Like COPY but can extract tar and fetch URLs RUN <command> Execute command during build (creates a layer) ENV KEY=value Set environment variable ARG KEY=value Build-time variable (not available at runtime) EXPOSE <port> Document which port the app listens on CMD ["executable", "arg"] Default command (can be overridden) ENTRYPOINT ["executable"] Fixed command (CMD becomes arguments) VOLUME /data Create a mount point for persistent data USER <username> Switch to non-root user `HEALTHCHECK CMD curl -f http://localhost/ CMD vs ENTRYPOINT # CMD — default command, can be overridden CMD ["python", "app.py"] # docker run myapp → runs python app.py # docker run myapp bash → runs bash (overrides CMD) # ENTRYPOINT — fixed command, CMD becomes arguments ENTRYPOINT ["python"] CMD ["app.py"] # docker run myapp → runs python app.py # docker run myapp test.py → runs python test.py Multi-Stage Build # Stage 1: Build FROM node:20-alpine AS builder WORKDIR /app COPY package.json ./ RUN npm ci COPY . . RUN npm run build # Stage 2: Production (smaller image) FROM nginx:alpine COPY --from=builder /app/dist /usr/share/nginx/html EXPOSE 80 CMD ["nginx", "-g", "daemon off;"] Multi-stage builds produce smaller images — the final image only contains the production output, not the build tools. ...

Your app works. But it looks like every other default Compose app — same purple, same fonts, same everything. Theming is how you make your app look like YOUR app. Custom colors, custom fonts, dark mode support — all in one system that applies everywhere automatically. Material 3 (also called Material You) is the design system Google built for modern Android apps. Compose uses it by default. In this tutorial, you will learn how to customize it. ...

Two years ago, AI tools for developers meant one thing: autocomplete. Now they do everything — write code, review code, create designs, generate tests, manage databases, deploy apps, and even write documentation. Here are the 10 AI tools I actually use. Not tools I read about. Tools that are open on my computer right now. 1. Cursor — The Code Editor What it does: AI-powered code editor that writes, edits, and refactors code. ...