pixegami
Build an AI Pokemon Generator with Python and Midjourney
updated
π Links
π Official Guide: https://ai.google.dev/gemini-api/docs/image-generation
π Code Examples: github.com/pixegami/nano-banana-prompt-guide
π₯ Nano Banana API: youtu.be/rV8NqpkklNU
π Chapters
00:00 Nano Banana Guide
01:07 Generate Realistic Images
02:41 Generate Illustrations and Anime
04:01 Generate Product Photos
04:59 Editing Images with Text
06:03 Combining Multiple Images
07:26 6x Best Practices for Nano Banana
#pixegami #nanobanana
It's also known as "Gemini 2.5 Flash Image", and is available via API. In this project, I'll show you how to use the API in Python, to create your own image generation app.
π Links
π Project Code: github.com/pixegami/nano-banana-python
π Google AI Studio: aistudio.google.com
π Google Cloud: console.cloud.google.com
π Chapters
00:00 What is Nano Banana?
01:29 Gemini API Key
02:54 Project Setup
03:45 Nano Banana API Code
07:05 Edit and Merge Image
π Links
π UV GitHub: github.com/astral-sh/uv
π How To Install: https://docs.astral.sh/uv/getting-started/installation
π Chapters
00:00 What is UV?
01:14 Project and Environment Setup
05:44 Package Management
08:59 Run Tools with uvx
11:03 UV Speed
It is a general purpose AI agent that runs from your terminal, and can autonomously work on your project for you. It is extremely powerful, it can connect to external tools via MCP, and it is free to use. But it is also new, so let's take a quick first look at how to use Gemini CLI, and some example use cases.
π Gemini CLI: github.com/google-gemini/gemini-cli
π₯ Claude Code: youtu.be/9cM-0Jy0lJ0
π Chapters
00:00 What is Gemini CLI?
03:36 Setting Up Gemini CLI
05:05 Configuring GEMINI.md
06:27 Example Use Cases
09:32 Connecting External Tools
12:47 Pricing and Models
#pixegami #ai
Learn how to install Claude Code, how to configure it, and how to get started using it effectively.
π Chapters
00:00 Introduction
02:20 What Is Claude Code?
04:58 Install Claude Code
07:02 Example Use Cases
11:54 Configuring Claude
13:41 Custom Workflows
15:31 Using External Tools
19:59 Model and Pricing
#pixegami
This is a great project for any Python developers that want to get started with MCP server development, and automation with AI agents!
π Links
π Code: github.com/pixegami/mcp-python-weather
π MCP Servers: github.com/modelcontextprotocol/servers
π₯ What is MCP? youtu.be/AdODsQdGHz0
π Chapters
00:00 Introduction
02:33 MCP Server Overview
04:31 Create an MCP Server
08:58 Google Sheets MCP
13:29 Using MCP tools in Claude Desktop
#pixegami #ai
It is an open standard that lets AI agents (LLMs) interact with the outside world β sort of a universal API (or a USB-C) for LLMs. Let's take a look at the problem it solves, how it works, and some examples.
With MCP servers, you will be able to enable AI agents to do anything that you could do with an external API: update spreadsheets, make a phone call, crawl the web, play a game (and probably thousands of other things).
π Links
π MCP Docs: modelcontextprotocol.io/introduction
π MCP Servers: github.com/modelcontextprotocol/servers
π Claude Desktop: claude.ai/download
π Chapters
00:00 What Is MCP?
01:21 The Problem MCP Solves
04:36 How MCP Works
08:55 An Example Agent
#pixegami #ai
We'll be using FastAPI (Python), and Gemini as our AI LLM model. Then we'll take a look at how to secure the endpoint with rate limiting, and with JWT tokens for authentication.
π Links
π Code: github.com/pixegami/fastapi-gemini-ai
π Get Your Gemini Key: aistudio.google.com/app/apikey
π₯ FastAPI on AWS Lambda: youtu.be/RGIM4JfsSk0
π Chapters
00:00 - Introduction
01:29 - Project Overview
02:34 - Setting Up
04:13 - Create a FastAPI App
06:46 - AI Integration (Gemini)
08:11 - Custom System Prompt
11:16 - Run the Server
12:51 - Rate Limiting
16:03 - Authentication with JWT
22:38 - Finished Project
#pixegami
π Code: github.com/pixegami/simple-rag-pipeline
π Chapters
00:00 - Introduction
02:01 - Pipeline Architecture
04:43 - Set Up the Database
09:05 - Set Up Core Components
13:14 - Evaluation
18:04 - Connect the Pipeline
20:35 - Run the Pipeline
23:39 - Upgrade and Run Again!
#pixegami
π Links
π Code: github.com/pixegami/run-deepseek-local
π LM Studio: lmstudio.ai
π Ollama: ollama.com
π Ollama Model Library: ollama.com/library/deepseek-r1
π Chapters
00:00 How To Run Deepseek Locally
00:52 Run Deepseek-R1 with LM Studio
02:20 Run Deepseek-R1 with Ollama
04:01 Run Deepseek-R1 with Python
In this video I'll show you how Supabase works, walk you through how to apply its awesome features (databases, auth, storage) to a SaaS project. The code is free for you to download and clone from GitHub. Enjoy!
π Links
π Project Code: github.com/pixegami/task-app
π Supabase: supabase.com
π Google Cloud: console.cloud.google.com
π OpenAI: platform.openai.com
π Stripe: stripe.com
π Chapters
00:00 Introduction and Demo
02:19 Supabase Project Overview
05:11 Setting Up
08:03 Create Supabase Project
10:10 Supabase CLI
11:54 Google OAuth
14:38 OpenAI API Key
15:32 Stripe Integration
22:12 Add Database
27:28 Add Storage
28:49 Deploy Edge Functions
32:15 Run the Project
34:03 Run Integration Tests
35:02 Wrapping Up
π Links
π Download Cursor: cursor.com
π Project Code: github.com/pixegami/cursor-ai-map-project
π¨ Theme: Noctis Minimus
π Chapters
00:00 Introduction
00:43 How Cursor Works
02:17 Project Overview
02:50 Starting a Project
06:28 Adding New Features
10:33 Refine Map Results
13:08 Expanding Scope
14:46 Difficult Bug
17:57 Build a Flask Server
20:08 Adding CSS Style
23:37 Optimize Performance
26:03 Project Retrospective
28:35 Cursor Pros and Cons
31:38 Verdict
π Links
π Code: github.com/pixegami/claude-booking-bot
π Anthropic Console: console.anthropic.com
π Tools Library: github.com/anthropics/anthropic-tools
π Chapters
00:00 Introduction
01:18 Project Demo
03:45 Tool-Use Concepts
06:33 Project Setup
09:11 Creating Tools
13:34 Tool Schemas
16:48 Tool Helper Functions
17:58 Integrate Tools with AI
23:15 Project Code Walkthrough
26:34 Demo (With Broken Edge Case)
27:59 Final Project Demo
29:21 Wrapping Up
π Links
π Code: github.com/pixegami/claude-3.5-api-tutorial
π Claude: claude.ai
π Anthropic: anthropic.com
π Chapters
00:00 - Introduction
03:07 - Setting Up
04:42 - Chat Example
06:53 - Tool-Use (Function Calling)
09:20 - Creating Tools
11:04 - Using Tools
16:23 - Vision API
19:18 - Wrapping Up
The AI app is a RAG (Retrieval Augmented Generation) app, built using Python and FastAPI, and hosted on AWS. The frontend will be using NextJS, TailwindCSS, and shadcn/ui components. The site will be fully static (free/cheap to host, without a dedicated server) and can generally be adapted to any kind of API backend.
π Links
π Project: github.com/pixegami/deploy-rag-to-aws/tree/frontend-tutorial
π Demo: rag.pixegami.io
π API: api.rag.pixegami.io
π UI Library: ui.shadcn.com
π Previous RAG Tutorials
π‘ youtu.be/tcqEUSNCn8I
π‘ youtu.be/2TJxpyO3ei4
π‘ youtu.be/ldFONBo2CR0
π Chapters
00:00 - Introduction
02:43 - Architecture Overview
06:24 - Generate an API Client
09:32 - Implement "ViewQuery" Page
15:27 - Rendering Components
19:31 - Implement "SubmitQuery" Form
25:07 - Implement "QueryList" Component
28:26 - Final Layout
π Code: github.com/pixegami/deploy-rag-to-aws
π Related Videos (in case you need it)
RAG Project Basic Tutorial: youtu.be/tcqEUSNCn8I
RAG Project Advanced Tutorial: youtu.be/2TJxpyO3ei4
FastAPI Tutorial: youtu.be/iWS9ogMPOI0
Get Started with AWS: youtu.be/LFCTFzcMQuA
AWS Bedrock (AI): youtu.be/kwkaBrK_-Bs
Using Docker on Lambda: youtu.be/wbsbXfkv47A
π Chapters
00:00 - Introduction
04:12 - RAG Recap
11:25 - Project Architecture
13:57 - Adding FastAPI
18:44 - Building a Docker Image
20:54 - Deployment Hacks
25:53 - Local Testing With Docker
29:17 - Build AWS Infrastructure with CDK
42:12 - Creating an Async API
54:11 - Wrapping Up
This project contains some more advanced topics, like how to run RAG apps locally (with Ollama), how to update a vector DB with new items, how to use RAG with PDFs (or any other files), and how to test the quality of AI generated responses.
π Links
π GitHub: github.com/pixegami/rag-tutorial-v2
π Basic RAG Tutorial: youtu.be/tcqEUSNCn8I
π PyTest Video: youtu.be/YbpKMIUjvK8
π Resources
π Document loaders: python.langchain.com/docs/modules/data_connection/document_loaders
π PDF Loader: python.langchain.com/docs/modules/data_connection/document_loaders/pdf
π Ollama: ollama.com
π Chapters
00:00 Introduction
01:06 RAG Recap
03:22 Loading PDF Data
05:08 Generate Embeddings
07:16 How To Store and Update Data
10:46 Updating Database
11:45 Running RAG Locally
15:12 Unit Testing AI Output
20:29 Wrapping Up
π Links
π Ollama GitHub: github.com/ollama
π LLM Library: ollama.com/library
π RAG + Langchain Python Project: youtu.be/tcqEUSNCn8I
π Chapters
00:00 How To Run LLMs Locally
01:07 Install Ollama
02:45 Ollama Server and API
04:15 Using Ollama Via Langchain
In this video I'll show all the steps I take as I make these videos, the equipment I use, and some of the custom AI and automation tooling I've created to help make the process go faster (originally it was 1-2 months, now it's down to about 7 days).
I use a lot of automation (with Python and AI tools) to do a lot of the time-consuming work, such slide generation, editing, translation, and generating video meta-data.
π Chapters
00:00 - Introduction
00:45 - Video Production Process
01:59 - Project Idea
02:52 - Coding
04:21 - Writing
04:55 - Generating Slides
08:44 - Recording
09:44 - Editing
10:20 - Automated First Edit
14:05 - Translation Process
14:55 - Chapter Labelling
15:45 - Process Demo
Or if none of these suit your needs, you can also implement your own interface.
π Chapters
00:00 Introduction
01:43 Getting Started
03:18 Creating the Base App
05:33 How To Use OpenAI GPT-4
07:42 How To Use Claude/Llama2 (via AWS)
09:33 How To Use Google Gemini Pro
10:27 Custom LLMs
π Links
π Code: github.com/pixegami/langchain-custom-llms
π Langchain LLMs: python.langchain.com/docs/integrations/llms
π Custom LLM: python.langchain.com/docs/modules/model_io/llms/custom_llm
π AWS Bedrock: aws.amazon.com/bedrock
π Google AI API: makersuite.google.com/app/apikey
π How to Get Started with AWS: youtu.be/LFCTFzcMQuA
In this video, I'll share what I think are the top 5 skills to invest time into this year if you want to get a high-paying role in tech, or to advance your career.
This is based on various data and trends I've observed in 2023, and some of my own gut feeling.
Salary Data: https://www.levels.fyi/
State of AI: mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
CrowdStrike Global Threat Report: go.crowdstrike.com/2023-global-threat-report.html
Cloud Market Growth: gartner.com/en/newsroom/press-releases/11-13-2023-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-reach-679-billion-in-20240
Bloomberg Job Skills Report: bloomberg.com/graphics/2015-job-skills-report
π Chapters
00:00 Tech Skills in 2024
01:09 Generative AI
05:05 Productivity Automation (RPA)
07:27 Cybersecurity
09:16 Cloud Computing
11:57 Leadership and Soft-Skills
#pixegami
π Links
π Code: github.com/pixegami/openai-assistants-api-demo
π Documentation: platform.openai.com/docs/assistants/overview
π OpenAI Assistants: platform.openai.com/assistants
π Data (PDF): eiu.com/n/campaigns/global-liveability-index-2023
π Chapters
00:00 OpenAI Assistants API
00:58 Create an OpenAI Assistant
02:07 Adding Custom Data
04:03 Function Calling
05:58 Code Interpreter
06:57 Using an API Endpoint
10:03 Wrapping Up
#pixegami #ai
π ChatGPT Custom GPT: chat.openai.com/gpts/discovery
π OpenAI Assistants API: platform.openai.com/assistants
π DnD "Wealthy Merchant" Campaign: dmsguild.com/product/194450/An-Introduction-to-DD--The-Wealthy-Merchant
π Chapters
00:00 Introduction
01:06 Project Demo
03:46 Creating a Custom GPT
05:40 Loading Custom Data
08:00 AI Prompt Engineering
09:41 AI Image Generation
10:51 Adding Conversation Starters
12:09 Deploy the Custom GPT
12:48 Deploy as an API
#pixegami #openai
π docs.python.org/3/library/dataclasses.html
π Chapters
00:00 Introduction
00:25 What is a Dataclass?
01:06 Create Data Structures with Less Code
02:34 Descriptive REPR
03:30 Built-in Equality Check
04:11 Fields and Default Values
06:19 Frozen Objects
07:16 Ordered Objects
08:21 Convert To and From Dict
#pixegami #python
Streamlit turns data scripts into shareable web apps in minutes.
All in pure Python. No frontβend experience required.
π Links
π Code: github.com/pixegami/streamlit-demo-app
π Streamlit: docs.streamlit.io
π Chapters
00:00 Introduction
00:41 What is Streamlit?
01:49 Using Input Elements
03:22 Working with Data
04:47 Multipage Apps
06:43 Loan Repayments App
10:03 Deploying to Streamlit Cloud
#pixegami #streamlit
You can use this to create chat-bots for your documents, books or files. You can also use it to build rich, interactive AI applications that use your data as a source.
π Links
π Code: github.com/pixegami/langchain-rag-tutorial
π (Sample Data) AWS Docs: github.com/awsdocs/aws-lambda-developer-guide
π (Sample Data) Alice in Wonderland: gutenberg.org/ebooks/11
π Chapters
00:00 What is RAG?
01:36 Preparing the Data
05:05 Creating Chroma Database
06:36 What are Vector Embeddings?
09:38 Querying for Relevant Data
12:47 Crafting a Great Response
16:18 Wrapping Up
#pixegami #python
π Links
π Code: github.com/pixegami/basic-langchain-examples
π Langchain: langchain.com
π OpenAI Platform: platform.openai.com
π Chapters
00:00 Introduction to Langchain
00:52 Setting Up Langchain and OpenAI
02:36 Generate Predictions
03:40 Getting Structured Output
05:52 Sequential Chains
07:03 Building an AI Agent
10:32 Other Langchain Features
#pixegami #langchain
This tutorial covers setting up the project, configuring the setup.py file, building and testing the package, adding CLI functionality, publishing to PyPI, and installing using pip. Watch this video if you want to share your code and make it easily installable for others.
π Chapters
00:00 Introduction
00:34 Project Setup
02:06 Configure and Build Package
04:14 Local Testing
05:53 Adding a CLI Entry Point
07:36 Publish to PyPI
10:01 Wrapping Up
#pixegami #python
This tutorial will guide you through the setup process, showing you how to generate text and images via code. You'll learn how to generate text with the Anthropic Claude model, and images with the Stable Diffusion model. All you need is an AWS account and the AWS CLI installed and configured.
π Code: github.com/pixegami/aws-bedrock-demo
π Get Started on AWS: youtu.be/LFCTFzcMQuA
π Amazon Bedrock: aws.amazon.com/bedrock
π Chapters
00:00 Introduction to Amazon Bedrock
01:12 Setting Up Amazon Bedrock
02:54 Text Playground
03:41 Image Playground
04:47 Generating Text with Code
07:43 Generating Images with Code
09:40 Amazon Bedrock Pricing
12:13 Amazon Bedrock vs OpenAI
#pixegami #aws
This step-by-step guide covers installation, making HTTP GET/POST requests, handling errors and timeouts, and scraping data from websites. It is important for Python developers who want to integrate their applications with external services and retrieve data from websites.
π Links
π Requests: requests.readthedocs.io/en/latest
π Example Domain: example.com
π httpbin.org: httpbin.org
π Chapters
00:00 Introduction
00:36 GET Request
01:49 HTTP Status Codes
02:33 Request Content
03:22 POST Request
04:54 Handling Errors
07:17 Setting a Timeout
09:27 HTTP Request Headers
10:22 Web Scraping with BeautifulSoup
12:38 Requests vs urllib
#pixegami #python
You'll learn how to create an AWS account, configure IAM users, and use the AWS CLI and SDK. We'll also look at AWS CDK and see how we can use it to manage cloud infrastructure.
π Links
π Project: github.com/pixegami/todo-list-api
π AWS Console: aws.amazon.com
π AWS Free Tier: aws.amazon.com/free
π AWS CLI: aws.amazon.com/cli
π Credential Provider Chain: docs.aws.amazon.com/sdkref/latest/guide/standardized-credentials.html#credentialProviderChain
π IAM Best Practices: docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html
π Node.js: nodejs.org/en
π AWS CDK: docs.aws.amazon.com/cdk/v2/guide/home.html
π Chapters
00:00 Introduction to AWS
00:57 Example AWS Services
05:51 AWS Pricing
07:32 AWS Free Tier
09:30 4 Ways to Use AWS
10:26 Create an AWS Account
11:40 How AWS Regions Work
13:08 Creating an IAM User
16:21 Using the AWS CLI
19:11 Using the AWS SDK for Python
20:47 Using AWS CDK
25:37 Deploying a Serverless To-Do List
27:16 Reference Architecture Diagrams
#pixegami #aws
Pydantic is the most widely used data validation library for Python. It lets you structure your data, gives you type-hints and auto-complete in your IDE, and helps to serialize to and from JSON. Learn how to use it in just 10 minutes!
π Links
π Pydantic Docs: https://docs.pydantic.dev/
π Pydantic GitHub: github.com/samuelcolvin/pydantic
π Chapters
00:00 Python's Dynamic Typing Problem
02:11 How To Use Pydantic
05:04 Validating Data with Pydantic
06:36 Custom Field Validation
07:58 JSON Serialization
08:49 Pydantic vs Dataclasses
#pixegami #python
In this tutorial, you'll learn how to instal FastAPI, and use it to create a new app. Learn how to define routes, handle errors, use request and path parameters, validating data with Pydantic models, modelling responses, and how to use the interactive documentation.
π Code: github.com/pixegami/simple-fastapi-example
π FastAPI: fastapi.tiangolo.com
π Chapters
00:00 Why Use FastAPI?
00:49 Install and Get Started with FastAPI
02:22 GET and POST Routes
05:27 Handling HTTP Errors
06:48 JSON Request and Path Parameters
10:38 Response Models
11:42 Interactive Documentation
13:31 FastAPI vs Flask
#pixegami #fastapi
In this tutorial, you'll learn how to create a Discord Bot using Discord's Interaction HTTP endpoints β and then host it for FREE on AWS Lambda. This is a super easy, cost-effective, and scalable way to host Discord bots.
We'll be using Flask and Python for the Discord bot, and AWS CDK to deploy our Lambda infrastructure.
π οΈ Code: github.com/pixegami/discord-bot-lambda
π Links
π Discord Developer Portal: discord.com/developers/applications
π AWS CDK: docs.aws.amazon.com/cdk/v2/guide/home.html
π Running Docker on Lambda: youtu.be/wbsbXfkv47A
π Chapters
00:00 Introduction
02:40 Set Up Discord Bot
04:13 Register Bot Commands
07:21 Creating Bot Endpoints
10:38 Token Validation
13:02 Create Docker Image
16:04 Deploying with AWS CDK
21:15 Wrapping Up
Starship enhances your prompt bar, Fish provides auto suggestions and syntax highlighting, and Warp offers an enhanced editing experience.
π GitHub: github.com/pixegami/mac-terminal
π Starship: https://starship.rs
π Nerd Fonts: nerdfonts.com
π Fish Shell: fishshell.com
π Warp: https://warp.dev
π Chapters
00:00 Custom Terminal Overview
02:15 Starship Prompt
04:30 Fish Shell
06:07 Warp Terminal
Using Docker containers for your Python app on AWS Lambda means you can create a special environment for your app with its own tools and settings, making sure it works everywhere, and also making it easy to include all the things (libraries and packages)your app needs to run correctly.
π οΈ Project Code: github.com/pixegami/aws-lambda-docker
π Links
Lambda Base Images: docs.aws.amazon.com/lambda/latest/dg/images-create.html#runtimes-images-lp
AWS CLI: aws.amazon.com/cli
AWS CDK: docs.aws.amazon.com/cdk/v2/guide/home.html
Docker: docker.com
π Chapters
00:00 Why run Docker on AWS Lambda?
01:04 Create CDK Project
01:45 Create a Python handler app
04:07 Create Dockerfile for Lambda
06:23 Test the Docker image locally
07:11 Create AWS Docker Lambda with CDK
09:44 Deploying to AWS
11:59 Wrapping up
#pixegami #aws
In this project, I'll show you how to use GitHub actions to automate the deployment (CI/CD) of an AWS project. The project is a simple Python API hosted on AWS Lambda (managed with AWS CDK).
We'll learn how to set up a simple GitHub action workflow to deploy the project to our AWS account on each commit. We'll also look at how to add a version number that increments automatically with each commit, and how to cache workflow steps (so we don't have to do the same things over and over again).
π Links
Project Code: github.com/pixegami/aws-cicd-tutorial
GitHub Actions: github.com/features/actions
AWS CLI: aws.amazon.com/cli
AWS CDK: docs.aws.amazon.com/cdk/v2/guide/home.html
π Chapters
00:00 Introduction
00:38 What is CICD?
01:51 Create an AWS CDK Project
05:46 Create GitHub Actions Workflow for CDK Deploy
10:18 Automate Version Bump with Git Hooks
12:42 Caching Workflow Steps
14:35 Deploy a Major Infrastructure Update
In this project, we will implement a monthly subscription payment system for our NextJS web app. We'll be using Stripe as our payment processor, and integrate it with Google Firebase for user authentication.
π οΈ GitHub/Code: github.com/pixegami/stripe-firebase-app
π Tech Stack
π Firebase: firebase.google.com
π Stripe: stripe.com
π NextJS: nextjs.org
π¬ Chapters
00:00 Introduction
01:52 Project Architecture
04:04 Authentication With Firebase
12:27 Setting Up Stripe For Payments
21:51 Adding a Checkout Session
29:17 How To Check Subscription Status
32:18 Adding Stripe Account Management
34:47 Wrapping Up
With this app, you'll learn how to get expense data from a user (via the terminal), save and categorize that expense into a spreadsheet. This project will take about an hour, and will test all of the Python skills you've learnt so far.
You'll learn how to plan, structure and implement a project all the way from an idea to a finished product β as well as seeing how you can solve new and unexpected problems.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Introduction
02:55 - Project Specs: Expense Tracker
06:30 - Create an "Expense" Class
07:55 - Main Project Structure
13:27 - Getting User Expenses
30:58 - Saving Expenses to a File
36:14 - Summarise All Expenses
43:54 - Group Expense By Category
49:07 - Track Remaining Budget
56:46 - Wrapping Up
They allow you to define your own custom data types, with properties and methods that can be accessed and manipulated from other parts of your code.
In this video, you'll learn the basics of creating and using classes in Python. We'll cover why classes are useful, how to define them, and how to create instances of classes.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Soon!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Introduction to Classes in Python
01:33 - How to Create a Class
04:53 - Creating an "Instance" of a Class
08:40 - Instance Methods
10:49 - Method Arguments
12:38 - Static Variables
15:30 - Static Methods
19:15 - Example Uses of Classes
20:53 - Coding Exercise: Classes
In this video, you'll learn 4 different ways your Python app can get input from the outside world β directly from the terminal, from a command line, from a file on your computer, and over the internet.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Soon!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Different Ways to Get User Input
02:24 - Using the input() Function
05:25 - Getting CLI Input
08:20 - Reading and Writing from Files
11:35 - Rest APIs (Talking To Other Apps)
14:20 - Coding Exercise: User Input
They allow you to package code into a named, reusable unit that can be called from other parts of your program. In this video, you'll learn how to define a function, pass in arguments, and return values.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Introduction to Functions in Python
01:01 - Creating a Function
03:28 - Input Arguments
08:57 - Multiple Arguments
10:43 - Positional Arguments
11:40 - Keyword Arguments
13:34 - Optional Arguments
15:46 - Common Mistakes With Functions
21:03 - What is "Abstraction"?
23:42 - Coding Exercise: Functions
Tuples are immutable sequences of elements, typically used for grouping related data.
Sets, on the other hand, are mutable collections of unique elements. With Sets, it's easy to check if an item is inside that collection. It's also easy to do mathematical operations like "intersection" (finding common elements between two sets) and "union" (finding all elements of two combined sets).
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Tuples vs Lists
01:58 - Tuple Syntax in Python
03:36 - Hands-on Coding with Tuples
05:45 - Using Tuples as a Dict Key
08:02 - Sets in Python
14:28 - Coding Exercise: Tuples and Sets
Dictionaries allowing for fast and efficient data retrieval. We'll cover how to create and manipulate dictionaries, as well as common methods for iterating through them.
You'll also learn how you can use dictionaries to represent real objects (e.g. like a shoe), and how to turn that data into a format that you can send over the internet to other apps (JSON serialization).
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Dictionaries vs List
03:42 - How to Use a Dictionary
05:03 - Adding, Updating and Removing items
12:03 - Dictionary Built-In Methods
13:15 - Looping Through a Dictionary
14:58 - Dictionary as Objects
16:45 - JSON Serialization
19:12 - Coding Exercise: Dictionaries
This is useful when working with lists, or if you have something that you want to execute for a certain number of times. In this tutorial, you'll learn why loops are such an important programming concept, and how you can use them in Python.
You'll learn how to loop through every item in a list, or loop for a fixed number of times. You'll also learn how to break early out of a loop, or how to short-circuit a loop execution to "continue" to the next iteration of a loop.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Introduction to Loops in Python
00:40 - Using "for" Loops
04:00 - Using enumerate()
04:58 - Looping X Times ("for in range")
07:13 - Using "while Loops
09:00 - How to "break" a loop
10:53 - How to "continue" a loop
13:17 - List Comprehensions
15:00 - Coding Exercise: Loops
You can add/remove items from a list, check if items are in a list, or even sort and reverse a list. The "list" (also known as an array or a vector in some other coding languages) is the first data structure you'll learn about in this seriesβyet it will remain one of the most useful and important concepts you'll rely on throughout your coding journey.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: youtu.be/ZPSES_gtm5U
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Introduction to Lists
02:35 - Hands-on Coding with Lists
04:41 - 2D Lists
06:42 - Add / Remove Items from Lists
13:08 - Other Lists Methods
18:43 - Coding Exercise: Lists
By using if/else statements, you can create decision-making processes in your code that allow it to do different things depending on whether certain conditions are true or false. This is how you can create programs that can respond to user input and other dynamic situations.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - "if" in Python
03:05 - "else" in Python
04:43 - "elif" in Python
06:52 - Inline Boolean Expressions
09:01 - Coding Exercise: Conditions
You can use them to add, subtract, multiply and divide numbers. You can also use logical operators, like "and, or, not" with boolean (True/False) values to create more complex logic in your application.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - What are operators?
00:29 - Arithmetic Operators
04:29 - Assignment Operators
06:50 - Comparison Operators
09:25 - Logical Operators
14:48 - Coding Exercise: Operators
They will let you store any type of data, and allow you to refer to it later on when you need to do something with it. Learn all about them in this quick tutorial.
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Using Variables in Python
05:20 - Good vs Bad Variable Names
08:48 - Data Types in Python
11:08 - Using print() in Python
14:38 - Coding Exercise: Variables
This video is part of a beginner tutorial series for anyone who wants to learn Python from scratch, and get to a point where you can start coding your own projects.
π Download Python: python.org/downloads
π Project Code (GitHub): github.com/pixegami/python-for-beginners
π Full Playlist: youtube.com/playlist?list=PLZJBfja3V3Rsbiz84Z63IXnTQZH_Rnfuo
π Next Chapter: Coming Tomorrow!
π Follow me on Twitter: @pixegami
π Chapters
00:00 - Install Python
01:42 - Run the Python Interpreter
03:34 - Install VSCode
04:20 - Write and Run a Python Script
07:46 - How To Get Help


