Advanced Python: Python packaging. Pip install your scripts! from Udemy

By the end of this course you will be able to publish a python package that is robust and deployable, so that anyone can pip install your code. You will learn how to call these packages with any bash command that you choose. You will learn enough to bridge the gap between the quality of code that comes out of a beginner course and the quality of code that can be seen in industry.

As far as prerequisites go, this course is not for beginners. This is for strong python developers that are looking to take their skills to a highly advanced level. You should have a solid foundation in python and have worked on at least a few python projects of your own. You should have a proficient knowledge in the command line. You should have access to a terminal, either through a mac or a linux system (or bash on windows, not recommended). You should have proficient knowledge in git.

This course is specifically geared to college graduates, advanced developers who have just learned python and want to make their code ready for industry, and for python developers who want to learn how to install their packages.

These skills are highly useful and will no doubt impress any employer. This is widely regarded as the one of the hardest topics in python, if not the hardest, so if you can do this you will be among a select few.

I hope to see you in the course.

What's inside

Learning objective

In this course you will learn one of the most advanced topics in python: how to create a python package that can be pip installed.

Syllabus

Introduction

In this section we discuss what this course will go over and what you will learn

Many tips on how to make your code readable. Going over the basic python script that we will turn into a package.

How to use python with folders and a directory structure. How to import classes properly. __init__.py and __main__.py

How to make your directory structure into a python package. Setup.py and automatic dependency installation covered.

Fill your setup.py with anything you could ever need. Call your packages with any bash command you choose!

How to add a README.md file to your package. How to document your package to save you time!

Series Finale! pip install your script without any source code!

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches how to create deployable Python packages, bridging the gap between beginner-level code and industry-standard code, which is highly valuable for professional development

Assumes a solid foundation in Python, experience with personal Python projects, proficiency in the command line, and knowledge of Git, which may exclude some learners

Focuses on packaging and deploying Python code, which is a critical skill for collaboration and distribution in software development environments

Covers setup.py configuration and automatic dependency installation, which are essential for creating robust and maintainable Python packages

Explores how to call packages with bash commands, which allows for seamless integration with existing workflows and automation scripts

Requires access to a terminal through a Mac or Linux system (or bash on Windows), which may pose a barrier for some learners using other operating systems

Reviews summary

Advanced python packaging essentials

According to learners, this course provides a practical, step-by-step guide to the often-challenging topic of Python packaging. Students appreciate learning how to make their scripts pip installable, a crucial skill for industry and professional development. While the course is noted as being definitely not for beginners and requires strong prerequisites in Python, command line, and Git, those with the necessary background found it effectively demystified the packaging process using `setup.py`. Some reviews indicate it can be difficult to follow at times, potentially due to the complexity of the subject matter or pace. Overall, it's seen as a valuable resource for taking Python skills to an advanced level.

Could benefit from modern tooling.

"Wish there was more on modern packaging tools like Poetry or Hatch."

"Focuses heavily on setup.py, which feels a bit dated with newer tools available."

"While the foundation is good, modern practices have evolved slightly."

Focuses on setup.py, init/main files.

"Covered the essentials of setup.py and entry points."

"The __init__.py and __main__.py explanations were particularly helpful."

"Provides the necessary steps to package my scripts using standard tools like setup.py."

"Good dive into packaging basics like directory structure and dependencies."

Highly relevant for professional work.

"The skills learned here are highly relevant for professional work."

"Learning to package scripts is a crucial skill for any serious Python dev."

"This is the kind of advanced topic you won't easily find clear explanations for elsewhere. Crucial for my projects."

"My projects are now pip installable! This is directly applicable to my job."

Makes complex Python packaging clear.

"Finally, a course that demystifies Python packaging!"

"This course provides a step-by-step guide to make packaging click for me."

"Learning how to make my projects pip installable has been demystified."

"It helped clarify the process from script to installable package."

Pace and complexity can be difficult.

"Found this very difficult to follow. The pace is too fast for me even with prior Python experience."

"Some parts felt a bit rushed, making it hard to keep up."

"Struggled with some of the setup variations and examples."

"This feels more like a reference than a teaching course at times due to the difficulty."

Needs solid Python, CLI, Git background.

"This course is definitely not for beginners. Prerequisites are absolutely needed."

"Assumes quite a bit of prior knowledge beyond just Python basics."

"Requires a solid understanding of command line which was stressed but still hard for some."

"If you don't have strong Python and Git skills, you will struggle."

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 Advanced Python: Python packaging. Pip install your scripts! with these activities:

Review Git Fundamentals

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Strengthen your understanding of Git, as proficiency is a prerequisite for this course. Review branching, merging, and pull requests to ensure a smooth learning experience.

Browse courses on Git

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Review basic Git commands like commit, push, and pull.
Practice branching and merging workflows.
Familiarize yourself with Git best practices.

Brush Up on Command Line Basics

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Revisit essential command-line operations, as this course assumes a working knowledge of the terminal. Practice navigating directories, manipulating files, and executing commands.

Browse courses on Command Line

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Practice navigating the file system using commands like cd and ls.
Learn how to create, move, and delete files and directories.
Familiarize yourself with common command-line utilities.

Create a Simple Python Package

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Build a basic Python package with a simple module and setup.py file. This hands-on experience will solidify your understanding of package structure and installation.

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Create a directory structure for your package.
Write a simple Python module with a function or class.
Create a setup.py file to define your package metadata.
Install your package using pip install .

Four other activities

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Show all seven activities

Python Cookbook, 3rd Edition

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Consult the Python Cookbook for recipes related to packaging, deployment, and distribution. This will provide practical solutions to common challenges.

View Python Cookbook: Recipes for Mastering Python 3 on Amazon

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Browse the table of contents for relevant recipes.
Read the recipes and try out the code examples.
Adapt the recipes to your own packaging projects.

Explore Advanced setup.py Features

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Follow tutorials on incorporating advanced features into your setup.py file, such as entry points for command-line scripts and data file inclusion. This will expand your packaging capabilities.

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Find tutorials on adding entry points to your setup.py.
Learn how to include data files in your package.
Experiment with different setup.py options and configurations.

Document Your Package

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Write comprehensive documentation for your package using Sphinx or a similar tool. This will reinforce your understanding of the package's functionality and improve its usability for others.

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Choose a documentation tool like Sphinx or MkDocs.
Write docstrings for your modules, classes, and functions.
Generate documentation using the chosen tool.
Publish your documentation online.

Contribute to an Open-Source Python Package

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Contribute to an existing open-source Python package by fixing bugs, adding features, or improving documentation. This will provide valuable real-world experience in package development and collaboration.

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Find an open-source Python package that interests you.
Identify a bug to fix or a feature to add.
Submit a pull request with your changes.
Respond to feedback from the maintainers.

Career center

Learners who complete Advanced Python: Python packaging. Pip install your scripts! will develop knowledge and skills that may be useful to these careers:

Python Developer

A Python developer specializes in building and maintaining applications using the Python programming language, and this course on Python packaging is a perfect fit. This course teaches how to build and publish pip-installable Python packages, which is a critical skill for a professional Python developer. This role requires not only writing code but also making it easily reusable and deployable. The course syllabus teaches how to structure projects for maintainability with `__init__.py` and `__main__.py` files, as well as how to handle dependencies, document packages properly and call them with bash commands. A Python developer can use skills learned in this course to bridge the quality gap between beginner level code and industry standard code. This course will make you among the most advanced Python developers, since as it is widely regarded as one of the hardest topics to master in this language.

See salaries and explore the career path for Python Developer

Software Engineer

A software engineer often creates and maintains software applications, and this course on Python packaging directly aligns with key responsibilities. This specific course helps a software engineer understand how to craft robust, deployable Python packages, going beyond basic scripting, and making code ready for production. The ability to use `pip install` to deploy software is crucial in a software engineer's daily workflow. The course directly teaches you the setup, structure, documentation, and dependency management required for professional projects. The course syllabus, focused on transforming a simple script into a deployable package with a fully configured `setup.py` file is exactly the kind of expertise that is needed in this role. This elevates a software engineer's abilities to meet industry standards and contribute to more complex projects. The course also teaches proper use of `__init__.py` and `__main__.py` files, which are essential to writing maintainable code.

See salaries and explore the career path for Software Engineer

DevOps Engineer

A DevOps engineer focuses on automating and streamlining software development and deployment processes; this advanced Python course on packaging is highly relevant. This specific course will help a DevOps engineer ensure that Python applications can be easily deployed and managed using `pip install`. This role often involves creating and maintaining automated pipelines and infrastructures, and the ability to package Python projects for easy distribution is essential. The course content covers core topics that are routinely used including directory structures, `setup.py`, bash command integration and documentation. The course helps a DevOps engineer understand how to ensure high reliability and ease of use for deploying Python applications, allowing them to bridge the gap between development and operations.

See salaries and explore the career path for DevOps Engineer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models, which often involves custom code that needs to be shared and used across different environments. This Python packaging course can help them streamline the process of sharing their work. This course focus on making Python code installable through `pip install`, which is a common method of deployment. The skills learnt in this course, including configuring `setup.py`, managing dependencies, and incorporating documentation, will directly help a machine learning engineer to better manage and distribute their models. The course will also help them integrate their work with the command line, which is essential to many machine learning workflows. The course will allow them to create models that are easily deployable and maintainable.

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Backend Developer

A backend developer designs and implements the server side logic of applications, and this course on Python packaging can help them write professional, deployable code. As a backend developer, you will be expected to package code in such a way that it can be easily integrated into server environments, and this course will provide you the necessary skills. The course shows how to use `pip install` to deploy packages, which is widely used in back-end development. This means the course's syllabus on folders and directory structure, creating and managing `setup.py`, README documentation, dependency handling and command line calls is highly relevant to a backend developer. The ability to build and maintain robust packages is essential for anyone working on the backend of an application.

See salaries and explore the career path for Backend Developer

Software Architect

A software architect designs the high-level structure of software systems, and this Python packaging course will give them the knowledge to make key decisions about a project's architecture. This course provides insight into how Python projects are structured for deployment and maintenance, since it covers package creation, dependency management and documentation. This ensures that a software architect can effectively plan systems that are installable via `pip`. A deep understanding of packaging with `setup.py` and bash integration enables them to make informed decisions on how various components of a system can be designed for production environments. The course helps a software architect make sure that software systems are organized for scalability, maintainability, and ease of use.

See salaries and explore the career path for Software Architect

Data Engineer

A data engineer designs and builds systems for collecting, storing, and processing data; this advanced Python course on packaging can aid in their ability to deploy tools efficiently. This role requires a deep understanding of Python, and the course focuses on how to create distributable Python packages that can be easily deployed using `pip install`. Data engineers frequently write custom Python tools and libraries, so knowing how to properly package these for reuse and versioning is crucial. The course shows how to use `setup.py` to manage dependencies, how to make the code easy to use with bash commands, and how to structure project directories, which are all essential skills for a data engineer to have. The course will make them more knowledgeable on how to deploy and manage code for data pipelines and workflows.

See salaries and explore the career path for Data Engineer

Research Scientist

A research scientist conducts scientific studies and experiments, and they may find this course helpful to share their work with others. While not a core part of the work, they often develop custom scripts and tools as part of their research, and they may need to share these with colleagues. The course on Python packaging teaches how to package applications and make them installable with `pip install`. These packages can be used by others in the lab or shared more broadly. The course will show how to use `setup.py`, add a README for documentation, integrate with bash commands and manage dependencies. A research scientist can benefit from these skills when deploying custom tools and sharing them with the broader scientific community.

See salaries and explore the career path for Research Scientist

Computational Biologist

A computational biologist uses computational techniques to analyze biological data, and this advanced Python packaging course may be useful. This role involves the creation of custom tools and scripts, often written in Python, which other computational biologists may need to use. This course will guide them through how to create packages that can be shared through `pip install`. This course teaches how to structure package folders, manage dependencies with `setup.py`, add a README for documentation, and integrate packages with the command line. A computational biologist can use these skills to share tools in a more effective way, and it helps improve collaborations in the scientific community. This course may help a computational biologist expand the capabilities of their research.

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Data Scientist

A data scientist uses statistical methods and machine learning to analyze data; this Python packaging course may be helpful. Although they often work with pre-built tools, data scientists sometimes create custom tools that need to be shared and deployed, and this course would be useful in such cases. This course provides a process for packaging up custom libraries, so they are installable using `pip install`. The course syllabus, which covers how to use `setup.py`, manage dependencies, and document code, will aid in a data scientist's ability to manage and share their tools with others. It will also teach them how to integrate their code with bash commands. While not a core part of this role, it will help when creating and deploying tools for data analysis.

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Systems Administrator

A systems administrator manages computer systems and servers. This Python packaging course may be useful for a systems administrator that needs to make sure that applications are deployed reliably. Although they may not be writing python every day, the techniques in this course can help them maintain systems. The course covers how to use `pip install` to deploy Python packages, and how to manage dependencies. The course syllabus, which shows how to organize project folders, handle `setup.py`, and use `__init__.py` and `__main__.py` files, will help a systems administrator streamline deployments. This course may be useful to expand the knowledge base of a systems administrator.

See salaries and explore the career path for Systems Administrator

Embedded Systems Engineer

An embedded systems engineer designs and develops software for embedded systems, and this advanced Python packaging course may be useful as they sometimes use Python for tooling. Although their primary focus may not be Python, embedded systems engineers often use Python for testing, automation, and deployment of their code, so the skills taught in this course can be applicable. The course’s focus on packaging and deployment with `pip install` can streamline the process of managing and distributing tools. The course syllabus teaches how to structure project folders, manage dependencies with `setup.py`, and integrate packages with bash commands, which are helpful for working with many embedded tools. This course can help an embedded systems engineer improve the overall development process.

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Robotics Engineer

A robotics engineer develops and maintains all aspects of robots, and this Python packaging course may be useful to streamline deployment of code. Since this role often uses Python for various tasks, they will be able to utilize what they learn in the course. Many robotic systems use Python for control systems, data processing, and simulations, and this course helps with packaging code for such applications. The course discusses the use of `pip install` to deploy Python programs, and it teaches all the necessary elements of creating a package such as how to use `setup.py`, document packages with README files and integrate with the command line. While not a core skill, the course is applicable to a robotics engineer's workflow.

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Technical Consultant

A technical consultant provides expert advice and guidance to clients on technology-related issues; this course on Python packaging may be useful. Although a technical consultant might not write code every day, a thorough understanding of software deployment and maintenance can be very useful to provide well informed advise. This course ensures a technical consultant understands how to deploy applications via `pip install`. The course also teaches how to use `setup.py`, manage dependencies, create documentation and integrate with bash commands. This knowledge can help a technical consultant provide better recommendations to clients. While it may not be a core skill, this understanding can be beneficial for a technical consultant.

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Quantitative Analyst

A quantitative analyst develops and implements mathematical models for financial analysis; this course on Python packaging may be useful. A quantitative analyst may use Python to write scripts to process data and implement models, and this course will give them the ability to package their work effectively. The course teaches how to use `pip install` to deploy Python packages, and how to manage dependencies. The course syllabus, which explains how to use `setup.py`, how to document code, and how to integrate with the bash command line, can be useful to share tools and pipelines with others in finance. Although it's not a primary focus of a quantitative analyst, it may be a useful skill for collaboration and code sharing.

See salaries and explore the career path for Quantitative Analyst

Advanced Python

Python packaging. Pip install your scripts!

What's inside

Learning objective

Syllabus

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Reviews summary

Advanced python packaging essentials

Activities

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