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Alfredo Deza

In this 2-hour long project-based course, you will learn how to:

- Describe the purpose of virtual environments in Python development

- Explain how to create and activate a virtual environment using the venv module

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In this 2-hour long project-based course, you will learn how to:

- Describe the purpose of virtual environments in Python development

- Explain how to create and activate a virtual environment using the venv module

- Install packages and dependencies into a virtual environment using pip and requirements.txt.

Completing this project on setting up Python environments will provide learners with essential skills for professional Python development. Learning to properly manage dependencies is crucial for any programmer. This project stands out by using current best practices for Python packaging, avoiding deprecated approaches. Learners will benefit from gaining hands-on experience with critical tools like virtual environments, pip, and pyproject.toml. Following the opinionated recommendations in this project will equip learners with a streamlined workflow for configuring reproducible and isolated Python environments. The project uniquely focuses on real-world developer needs, not just toy examples. Learners will complete the project knowing how to dependency manage projects of any size for both dev and production. These professional techniques will enable learners to use Python for building robust applications across many domains.

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What's inside

Syllabus

Project Overview
Learn how to work with Python and dependencies

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches essential skills for professional Python development
Provides hands-on experience with crucial tools like virtual environments, pip, and pyproject.toml
Focuses on practical aspects of working with Python and dependencies
Establishes a streamlined workflow for deploying Python projects in a variety of contexts
Taught by Alfredo Deza, an experienced instructor
Recommended for anyone seeking to strengthen their foundational Python skills

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Setup Python with these activities:
Review: Automate the Boring Stuff with Python
Provides a comprehensive overview of Python basics, reinforcing the fundamentals covered in the course.
Show steps
  • Read chapters related to virtual environments.
  • Practice exercises on creating and managing Python environments.
Create an isolated and virtual environment
Builds a foundation for managing Python dependencies and environments, avoiding common pitfalls and improving workflow.
Browse courses on Virtual Environments
Show steps
  • Set up a Python environment using virtualenv.
  • Install dependencies using pip.
  • Test the virtual environment by running a simple Python script.
Follow a Tutorial on Pipenv
Introduces Pipenv as a tool for managing Python dependencies, complementing the course's focus on venv.
Browse courses on Python Packaging
Show steps
  • Find a tutorial on using Pipenv.
  • Follow the tutorial to set up a virtual environment using Pipenv.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Code Challenge: Virtual Environment Management
Tests understanding of virtual environment creation, dependency management, and environment isolation.
Browse courses on Virtual Environments
Show steps
  • Solve coding exercises on virtual environment setup.
  • Troubleshoot common errors related to virtual environments.
Develop a Python Package
Applies knowledge to create a reusable Python package, reinforcing concepts of dependency management and environment isolation.
Browse courses on Python Packaging
Show steps
  • Design the package structure.
  • Write the Python code.
  • Create a setup.py file.
  • Test the package.
Contribute to an Open-Source Python Project
Enhances understanding of Python environment management by contributing to real-world projects that utilize virtual environments.
Browse courses on Python
Show steps
  • Find an open-source Python project that uses virtual environments.
  • Identify an area for improvement or contribution.
  • Submit a pull request with your changes.
Hackathon: Python Environment Optimization
Provides a challenging and collaborative environment to showcase skills in Python environment management.
Browse courses on Python Packaging
Show steps
  • Form a team and register for the hackathon.
  • Develop a solution to optimize Python environment setup and dependency management.
  • Present the solution to a panel of judges.

Career center

Learners who complete Setup Python will develop knowledge and skills that may be useful to these careers:
Research Scientist
Research Scientists can use their knowledge of Python and dependencies to develop and implement research projects. This course's coverage of virtual environments, pip, and requirements.txt will help Research Scientists create and manage the dependencies required for research. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large research projects.
IT Architect
IT Architects can use their knowledge of Python and dependencies to design and implement IT solutions. This course's coverage of virtual environments, pip, and requirements.txt will help IT Architects create and manage the dependencies required for IT architecture. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large IT projects.
Security Analyst
Security Analysts can use their knowledge of Python and dependencies to develop and implement security solutions. This course's coverage of virtual environments, pip, and requirements.txt will help Security Analysts create and manage the dependencies required for security analysis. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large security projects.
Project Manager
Project Managers can use their knowledge of Python and dependencies to develop and implement project solutions. This course's coverage of virtual environments, pip, and requirements.txt will help Project Managers create and manage the dependencies required for project management. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large projects.
Machine Learning Engineer
Machine Learning Engineers can use their knowledge of Python and dependencies to build and maintain machine learning models. This course's coverage of virtual environments, pip, and requirements.txt will help Machine Learning Engineers create and manage the dependencies required for machine learning. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large machine learning projects.
Business Analyst
Business Analysts can use their knowledge of Python and dependencies to develop and implement business solutions. This course's coverage of virtual environments, pip, and requirements.txt will help Business Analysts create and manage the dependencies required for business analysis. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large business projects.
Software Engineer
Software Engineers can use their knowledge of Python and dependencies to build and maintain software applications. This course's coverage of virtual environments, pip, and requirements.txt will help Software Engineers create and manage the dependencies required for software development. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large software projects.
Product Manager
Product Managers can use their knowledge of Python and dependencies to develop and implement product solutions. This course's coverage of virtual environments, pip, and requirements.txt will help Product Managers create and manage the dependencies required for product management. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large product projects.
Data Engineer
Data Engineers can use their expertise in Python and dependencies to build and maintain data pipelines. This course's coverage of virtual environments, pip, and requirements.txt will help Data Engineers create and manage the dependencies required for data engineering. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working with large data sets.
DevOps Engineer
DevOps Engineers can use their knowledge of Python and dependencies to build and maintain CI/CD pipelines. This course's coverage of virtual environments, pip, and requirements.txt will help DevOps Engineers create and manage the dependencies required for CI/CD. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large projects.
Cloud Engineer
Cloud Engineers can use their knowledge of Python and dependencies to build and maintain cloud infrastructure. This course's coverage of virtual environments, pip, and requirements.txt will help Cloud Engineers create and manage the dependencies required for cloud engineering. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large cloud projects.
Technical Writer
Technical Writers can use their knowledge of Python and dependencies to develop and implement technical solutions. This course's coverage of virtual environments, pip, and requirements.txt will help Technical Writers create and manage the dependencies required for technical writing. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working on large technical projects.
Data Scientist
Data Scientists can use their expertise in Python and dependencies to build and deploy machine learning models. This course's coverage of virtual environments, pip, and requirements.txt will help Data Scientists create and manage the dependencies required for machine learning. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working with sensitive data.
Quantitative Analyst
Quantitative Analysts can use their expertise in Python and dependencies to develop and implement quantitative models. This course's coverage of virtual environments, pip, and requirements.txt will help Quantitative Analysts create and manage the dependencies required for quantitative modeling. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working with sensitive data.
Data Analyst
Data Analysts can use their expertise in Python and dependencies to manage and analyze large datasets. This course's coverage of virtual environments, pip, and requirements.txt will help Data Analysts create and manage the dependencies required for data analysis. It will also provide them with the skills needed to configure reproducible and isolated Python environments, a critical skill for working with sensitive data.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Setup Python.
Provides a comprehensive introduction to Python, covering the basics of the language as well as more advanced topics such as object-oriented programming and data science. It great resource for beginners who want to learn Python quickly and effectively.
Teaches you how to use Python to automate tasks, such as sending emails, downloading files, and scraping data from websites. It great resource for beginners who want to learn how to use Python for practical applications.
Teaches you how to use Python for data analysis, including how to load, clean, and manipulate data. It great resource for beginners who want to learn how to use Python for data science.
Teaches you how to write better Python code, including how to write clean, efficient, and maintainable code. It great resource for beginners and experienced Python developers alike.
Is the official Python tutorial, written by the creator of the language. It great resource for beginners who want to learn Python from the source.
Provides a collection of recipes for solving common programming problems in Python. It great resource for Python developers who need help with specific tasks.
Provides a comprehensive introduction to Python, covering the basics of the language as well as more advanced topics such as object-oriented programming and data science. It great resource for beginners who want to learn Python in a structured way.
Provides a comprehensive reference to Python, including the syntax, standard library, and common idioms. It great resource for Python developers who need a quick reference to the language.
Teaches you how to use Python to develop enterprise applications, including how to work with databases, web services, and distributed systems. It great resource for Python developers who want to learn how to use Python in a professional setting.
Teaches you how to use Python for machine learning, including how to load, clean, and manipulate data, and how to train and evaluate machine learning models. It great resource for beginners and experienced machine learning practitioners alike.
Teaches you how to use Python for natural language processing, including how to tokenize and parse text, and how to perform sentiment analysis and other NLP tasks. It great resource for beginners and experienced NLP practitioners alike.
Teaches you how to use Python for data science, including how to load, clean, and manipulate data, and how to perform data analysis and visualization. It great resource for beginners and experienced data scientists alike.

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