Taking Python to Production: A Professional Onboarding Guide from Udemy

This is a course about transitioning from a "coder" to a "software engineer". It specifically covers the tools needed to develop and "ship" production-ready software with Python.

As an MLOps engineer, my role is to help enable data scientists, analysts, and junior engineers become more self-sufficient at bringing products to production.

This course covers a mix of foundational tools, engineering practices, and career advice that new engineers should be given during the onboarding process when they join a team (but they often don't get guidance. ).

By the end of this course, you should feel confident contributing to complex software projects in a team setting, whether open-source or at a company (or please request a refund within 30 days. ).

You will understand how closed- and open-source projects are run and how to run your own.

In the course, we write very little code and instead focus on the non-coding aspects of software engineering that make you an effective member of the software engineering community.

That said, you should have a solid grasp of Python fundamentals (loops, functions, classes, etc.) before taking this course.

Expect to learn

how to set up a professional Python development environment
how to set up a professional workflow for Python development with Visual Studio Code; extra emphasis on autocompletion
how to use git, GitHub, "branching strategies", and their integrations with VS Code and the terminal
how to write clean, maintainable code and ensure that all code contributed to your projects is good quality (testing, linting, formatting, type checking, documentation, etc.)
how to publish production-quality software for a wide audience with packaging, versioning, continuous integration, and continuous delivery (pre-commit, GitHub Actions, PyPI)
how to templatize all of the above points, so you can create new, high-quality projects in seconds

Before paying for this course, please sample the preview lectures so you can get a sense of whether it's right for you.

See you in the course.

- Eric

What's inside

Learning objectives

Set up a professional python development environment - visual studio code, pyenv, git, autocompletion
Learn the professional git workflow with github and ci/cd with github actions
Make the terminal more intuitive with zsh and plugins

Version and package python software and publish it for the community
Setup automated code quality checks (testing, linting, documentation, type checking, etc.)

Set up a professional python development environment - visual studio code, pyenv, git, autocompletion
Learn the professional git workflow with github and ci/cd with github actions
Make the terminal more intuitive with zsh and plugins
Version and package python software and publish it for the community
Setup automated code quality checks (testing, linting, documentation, type checking, etc.)

Syllabus

Preface to the course.

Expectations for the course.

IMPORTANT! Course Notes and Course Website

Linux and terminal crash course

Prepare your development environment by installing a text editor (VS Code) and setting up a Linux terminal so that you can follow along with the rest of the course.

Install VS Code

You can open VS Code using the `code` command in the terminal. It will be more difficult to follow along if you do not have the `code` command working on your machine. This assignment will help you install the `code` command.

If you are a Mac user, please complete this assignment to (1) Install Homebrew, which we will be using frequently to install commands needed for the course. (2) Install a iTerm2 or another Terminal application alternative.

Windows users only: Install the Windows Subsystem for Linux (WSL2)

Windows users only: Integrate VS Code with the WSL2

Resources: Installing git

Installing the git CLI tool

Improving the terminal with ZSH

Introduction

Installing OhMyZSH

Navigating using ZSH and installing ZSH plugins

The ~/.zshrc file and ZSH themes

Disabling/enabling ZSH plugins; All-in-one Markdown extension; web-search plugin

Typeahead auto-completion with zsh-autosuggestions

Syntax highlighting with zsh-syntax-highlighting

Cheat sheet: quick ZSH setup

Understand how software is versioned, why it's important to be able to switch between multiple Python versions, and how to do that with a tool called pyenv.

Introduction to Semantic Versioning (semver)

Semantic Versioning (continued)

Semantic Versioning

Why developers need to be able to switch between multiple Python versions

Resources for installing pyenv

Installation and overview of pyenv for managing multiple Python versions

History of Python changes; Overview of how Python evolves

Learn the layout of VS Code, some key shortcuts for productivity, and many tips for getting the most out of VS Code's Python auto-completion with Python virtual environments.

Resources for the next video.

VS Code: layout and key shortcuts

Python/Pylance: improve refactoring and syntax highlighting support

Step debugging in VS Code

Preview of virtual environments

Python virtual environments and the PATH variable

An overview of git starting from the basics, showing how to perform each git action in using the CLI and VS Code's graphical interface for git

Introducing git by comparing it to Google Docs

Git lens extension

Git command reference

git CLI and commits

Making a commit

Time traveling and best practices for making commits

git stash

(Part 1) git branching - visual intuition

(Part 2) git branching - hands-on in VS Code

Merging git branches

Resolving merge conflicts

[Extra] git branching game

git tags

Recap: the local git workflow

GitHub and Code Review

Preview of the rest of the course

What is GitHub?

Creating a repository in GitHub

Cloning and git remotes

Pull Requests and Code Review

Conducting Code Review with a Pull Request

Recap: the remote git workflow

Continuous Integration: clean code, formatters, linters and VS Code integrations

Section guide: resources, links, assignments, summary notes, etc.

Clean code and why it's important

Python style guides: Google and PEP 8

Refactoring for better readability

Introduction to Continuous Integration and best practices for PRs

"PR hell" and more discussion of Continuous Integration

Autoformatting with Black, VS Code's settings system, and "Holy Wars"

Pylint Part 1 - Introducing Linters

Pylint Part 2 - Integrating with VS Code

Pylint Part 3 - Configuring Pylint w/ a config file and CLI arguments

Flake8 Part 1 - Usage and background

Flake8 Part 2 - Flake8 plugins w/ Darglint as an example

isort: sorting import statements

"Code metrics" like "cyclomatic complexity" with Radon, Xenon, and McCabe

Typing Part 1 - type hints, autocompletion, static vs dynamic type checking

Typing Part 2 - Mypy and basic typing

Typing Part 3 - Simple and Complex Types

Typing Part 4 - Union and Optional

Typing Part 5 - TypedDict, dataclasses, NamedTuple, self-referential types

Typing Part 6 - Generic Types

Typing Part 7 - Type Stubs and incrementally adding types to existing codebases

Darker: incrementally lint legacy projects

Ruff: the last Python linter ever?

Continuous Integration - The pre-commit framework

A Continuous Integration workflow with code quality tools

CI Approach 1 - Writing a script that calls each tool

Git pre-commit hooks

CI Approach 2 - The pre-commit framework

Pre-commit hook roundup

Tour of an advanced pre-commit config file

GitHub Actions

Our first GitHub Actions "workflow"

GitHub Actions: running a workflow

Fixing the build and using pre-commit

Branch permissions, merge checks, and pull requests

Understanding GitHub Actions Pricing

Optimizing for cost by using GitHub Actions Triggers

Python Packaging

Section Intro - Python Packaging

PYTHONPATH and imports in Python

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Course walks you through industry-standard tools required for software development with Python

Examines best practices for developing production-ready code

In addition to software development with Python, explores foundational tools and engineering practices necessary for the role of an MLOps engineer

Taught by professionals in the field with experience at major companies like Eric Riddoch

Suitable for those transitioning from 'coder' to 'software engineer', especially if you have experience in data science, analysis, or as a junior engineer

Requires a solid grasp of Python fundamentals

Career center

Learners who complete Taking Python to Production: A Professional Onboarding Guide will develop knowledge and skills that may be useful to these careers:

Software Engineer

As a Software Engineer, you will be responsible for designing, developing, and maintaining software applications. This course will help you build a strong foundation in the tools and techniques used by professional software engineers, including Python, git, and GitHub. You will also learn about best practices for writing clean, maintainable code, and how to work effectively in a team environment.

See salaries and explore the career path for Software Engineer

DevOps Engineer

DevOps Engineers are responsible for bridging the gap between development and operations teams. This course will help you build a strong foundation in the tools and techniques used by DevOps Engineers, including Python, git, and GitHub. You will also learn about best practices for automating the software development and deployment process.

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Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that stores and processes data. This course will help you build a strong foundation in the tools and techniques used by Data Engineers, including Python, git, and GitHub. You will also learn best practices for managing data, and how to work effectively with other members of the data team.

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Software Quality Engineer

Software Quality Engineers are responsible for ensuring that software meets quality standards. This course will help you build a strong foundation in the tools and techniques used by Software Quality Engineers, including Python, git, and GitHub. You will also learn about best practices for testing software, and how to identify and fix defects.

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Data Scientist

Data Scientists are responsible for extracting insights from data. This course will help you build a strong foundation in the tools and techniques used by Data Scientists, including Python, git, and GitHub. You will also learn about the principles of data science, and how to use data to solve business problems.

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Machine Learning Engineer

Machine Learning Engineers are responsible for developing and deploying machine learning models. This course will help you build a strong foundation in the tools and techniques used by Machine Learning Engineers, including Python, git, and GitHub. You will also learn about the principles of machine learning, and how to build models that are accurate, reliable, and efficient.

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Cloud Engineer

Cloud Engineers are responsible for designing, developing, and maintaining cloud-based applications. This course will help you build a strong foundation in the tools and techniques used by Cloud Engineers, including Python, git, and GitHub. You will also learn about the principles of cloud computing, and how to design and develop applications that are scalable, reliable, and secure.

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Technical Writer

Technical Writers are responsible for creating documentation for software and hardware products. This course will help you build a strong foundation in the tools and techniques used by Technical Writers, including Python, git, and GitHub. You will also learn about the principles of technical writing, and how to communicate technical information clearly and effectively.

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Software Architect

Software Architects are responsible for designing and developing the architecture of software systems. This course will help you build a strong foundation in the tools and techniques used by Software Architects, including Python, git, and GitHub. You will also learn the principles of software architecture, and how to design systems that are scalable, reliable, and maintainable.

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Systems Engineer

Systems Engineers are responsible for designing, developing, and maintaining complex systems. This course will help you build a strong foundation in the tools and techniques used by Systems Engineers, including Python, git, and GitHub. You will also learn about the principles of systems engineering, and how to design and develop systems that are reliable, maintainable, and scalable.

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Quantitative Analyst

Quantitative Analysts are responsible for developing and using mathematical models to analyze financial data. This course will help you build a strong foundation in the tools and techniques used by Quantitative Analysts, including Python, git, and GitHub. You will also learn about the principles of quantitative analysis, and how to use models to make investment decisions.

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Product Manager

Product Managers are responsible for defining and managing the vision for software products. This course will give you a foundation in the tools and techniques used by Product Managers, including Python, git, and GitHub. You will also learn about the principles of product management, and how to develop and launch successful software products.

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IT Consultant

IT Consultants are responsible for providing advice and guidance to organizations on how to use technology to achieve their business goals. This course will give you a foundation in the tools and techniques used by IT Consultants, including Python, git, and GitHub. You will also learn about the principles of IT consulting, and how to develop and deliver effective consulting services.

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Project Manager

Project Managers are responsible for planning, executing, and closing software projects. This course will give you a foundation in the tools and techniques used by Project Managers, including Python, git, and GitHub. You will also learn the principles of project management, and how to manage software projects successfully.

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Business Analyst

Business Analysts are responsible for understanding the business needs of an organization and translating those needs into technical requirements. This course will give you a foundation in the tools and techniques used by Business Analysts, including Python, git, and GitHub. You will also learn about the principles of business analysis, and how to gather and analyze requirements.

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