Writing Production-Grade Python Code for Quant Developers

Name: Writing Production-Grade Python Code for Quant Developers
Rating: 4.2 (43 reviews)

Learn the tools needed to write high-quality Python code

Created byHudson and Thames Quantitative Research

Last updated 5/2024

English

What you'll learn

Learn to write production-grade Python code.
Learn how to build high quality Python libraries which will be used by quantitative researchers / algorithmic traders.
Crystallise your knowledge in quant developer best practices.
Understand the tools at your disposal for creating production-ready code and the processes surrounding them.

Course content

8 sections • 66 lectures • 14h 0m total length

The World of Quant Developers and Researchers12:27
In this video, we learn about two quant roles that have a great deal of skills overlap but with heavier emphasis on certain areas.
Demand for Good Quantitative Developers14:39
In this video, we look at the quantitative developer skill set in more detail.
What is Production-Grade code7:29
Here, we define production-grade code and see how to ensure our code is of sufficient quality for a production environment.
Course Objectives and Expectations6:24
Here, we run through the topics we'll cover in this course and that will expand your knowledge of the Python development ecosystem.
Additional Resources1:20

Introduction to Research15:13
In this lecture, we have a look at potential areas of research for quantitative developers and researchers, and see why research into financial markets needs to follow the scientific process.
Key Finance Journals and Other Platforms14:23
In this lecture, we take a look at some key finance journals, early-access platforms and other tools you can use for discovering research and academic literature.
Conducting Literature Reviews (1/2)13:24
In this lecture, we talk about the process of conducting a literature review and what techniques and tools are available for you to process and contain this information.
Conducting Literature Reviews (2/2) - Obsidian Demo & H&T's Second Brain14:35
This lecture carries on from the previous where we conclude with a demonstration of the note-taking application, Obsidian, and showcase Hudson & Thames second brain known as 'Mary's room'.
Introduction to Code Roadmaps9:59
This video serves as an introduction to simple code roadmaps and how you can use them to structure the implementation of code based on your research topic of interest. We also have a look at some past examples code roadmaps used at Hudson & Thames.
Resources0:37

Transition to Linux - Intro to Linux9:23
In this video we compare Linux and other popular operating systems, and make the case for Linux in quantitative development.
Transition to Linux - Ubuntu9:53
In this video we introduce Ubuntu and run through some generic installation steps to prepare you for your own Ubuntu installation!
Ubuntu installation assignment1:52
Transition to Linux - Terminal refresher11:32
In this video we head to the terminal and examine some commonly used Bash commands.
Terminal refresher
Transition to Linux - Package management and user privileges11:32
In this video we quickly introduce the Ubuntu desktop environment before looking at different ways one can install software on your Ubuntu machine. Following that, we look at user privileges and gaining administrative or 'root' privileges.
Package management and user privileges
Installing software
PyCharm and Jupyter Lab - Intro and IDEs8:04
In this video we discuss the tools we gain from using modern integrated development environments (IDEs).
PyCharm and Jupyter Lab - PyCharm installation and demo14:14
In this video we will install and introduce PyCharm, a very powerful Python IDE. In this video and the next two, we will run through some features of PyCharm including context-dependent actions, refactoring and debugging. We highly recommend you go through PyCharm learning tutorial, though!
PyCharm and Jupyter Lab - PyCharm refactoring demo19:18
In this video, we run through some basic refactoring functionality in PyCharm. Refactoring will be covered again in a later module, so if you want a bit more practice with refactoring, the PyCharm learning tutorial would be the place to do so!
PyCharm refactoring assignment
PyCharm and Jupyter Lab - PyCharm debugging demo16:09
In this video, we learn about debugging and get to grips with PyCharm's built-in debugger.
Debugging assignment
PyCharm and Jupyter Lab - Jupyter Intro26:26
In this video, we will show you how to install and start using Jupyter Lab.
Jupyter practical - Trend scanning

Introduction - The basics of version control10:11
In this video, you will be introduced to the topic of version control, why version control systems (VCS) are necessary, what VCSs are out there and the different types of VCSs.
Introduction - Git Essentials4:56
In this video, you will learn more about Git, including why it is so popular, and get a high-level overview of Git's fundamental concepts and features.
Introduction - Setting Up Git10:34
In this video, you will learn how to set basic configuration variables in Git and create your first Git repository.
Git workflow fundamentals - The Three States2:55
In this video, you will learn about the different states that your files may be in when tracking them using Git.
Git workflow fundamentals - Common Git Commands14:49
In this video, you will learn some common Git commands and see the states your files may be in in practice.
Git workflow fundamentals - Working with Remote Respositories16:29
In this video, you will learn about remote repositories, how to clone existing Git repositories and how to share changes with them.
Branching strategies - Branching in Git18:12
In this video, you will learn about branches, their associated commands, and how branching aids parallel and concurrent development.
Branching strategies - Popular Branching Strategies12:20
In this video, you will learn about the different types of workflows and branching strategies used in development.
Handling merge conflicts - Branch Management29:00
In this video, we'll see branching and merging commands on the command line, and learn how Git sets up our branches to track remote branches.
Handling merge conflicts - Merge Conflicts1:44
In this video, we will see when Git is able to handle the branch merging process automatically, and when it is not.
Handling merge conflicts - Resolving Conflicts9:19
In this video, you will learn about the two options for resolving merge conflicts, first on a code-hosting platform like GitHub, or on the command line.
Handling merge conflicts - Best Practices for Avoiding Conflicts2:21
In this video, we will run through some recommended best practices that will help limit the number and severity of merge conflicts.
Best practices - Types of Changes to Commit3:16
In this video, you will learn about the types of changes that you should be committing in Git.
Best practices - Writing Good Commit Messages2:47
In this section, you will learn about the structure of good commit messages.
Best practices - Organising Commits5:12
In this section, you will learn about techniques for organising your commits to maintain a coherent development history.
Advanced Git techniques - Stashing13:00
In this video, you will learn about stashing your work in progress before switching branches.
Advanced Git techniques - Tagging5:55
In this section, you will learn about a crucial part of version control, tagging version numbers!
Advanced Git techniques - Reverting3:50
In this video, we finish the module on Git with a demonstration on discarding changes with the 'git revert' command.

Introduction to Python Virtual Environments12:28
In this video, we will be introducing the concept of virtual environments and why they are so important for Python development.
Creating and Managing Virtual Environments31:58
In this video, we will show you how to create virtual environments using Python's builtin module venv as well as virtualenv, a third-party tool also used by default in PyCharm.
Creating a virtual environment with venv
Dependency management with pip16:29
In this video, we'll be introducing the basic usage of pip (of which you'll already likely be aware) and seeing how to use it alongside virtual environments.
Advanced dependency management with Poetry39:34
In this video, we will be looking at Poetry for managing your dependencies and virtual environments.
Reproducing environments with Poetry

Principles of clean code14:50
In this video, we run through some general, language-agnostic principles of creating clean code.
Clean Python Code & Style Guides (1/2)13:20
In this section, we speak about clean code in Python specifically and run through the Google Python Style Guide and how it enables us to write clean, good-looking code.
Clean Python Code & Style Guides (2/2)14:28
This is a continuation of the previous video where we conclude our run through the Google Python Style Guide.
Formatters and Linters (1/3) - Introduction5:48
In this video, we run through the basics of formatters and linters, and what they aim to achieve.
Formatters and Linters (2/3) - Black and Pylint CLI demo16:16
In this follow-up video, we run through the formatter Black and the linter Pylint on the command line using Poetry as the virtual environment manager.
Formatters and Linters (3/3) - Black, Pylint in PyCharm and Configurations14:44
In the last video of this section, we see how Black is integrated into PyCharm, how to set up Pylint in PyCharm and how to specify configurations for both tools.
Type Hints and Annotations22:07
In this video, we introduce Python type annotations as a language construct to improve readability and reemphasize how easy it is to use in PyCharm.

Introduction to Refactoring17:52
In this introductory video, we'll talk about what exactly is refactoring and what we aim to achieve by refactoring.
Inheriting Code13:53
Here, we look at common challenges that we'll face when inheriting code.
Code Smells10:18
In this video, we'll look at some commonly implemented code smells that can make their way into yours or others' code.
Common Refactoring Techniques15:58
In this video, we have another look at code smells by considering which common refactoring techniques we can apply to deal with them.
KCA Refactoring Assignment3:15
Read the assignment instructions and download kca_assignment.zip. See the attached solution once you are finished with your own attempt at refactoring the code.

The Importance of Good Documentation12:02
In this video, we cover the role and purpose of documentation, as well as the different types of documentation or may encounter or write.
Defining Good Documentation and its Objectives10:30
In this video, we cover some key characteristics of good documentation, considerations regarding the technical level of documentation and the main objectives of having documentation.
Best Practices13:30
In this video, we run through some best documentation practices such as achieving consistency through the use of style guides, using version control for your documentation and integrating your documentation into your development workflow.
Documentation in Python (1/3) - READMEs5:16
In this video, we outline the importance of README files and what is generally included in them.
Documentation in Python (2/3) - Docstrings31:47
We have already seen the Google specification for docstrings in the Clean Code section, now we will showcase docstrings with a toy example by creating a package which we will also use to create documentation with Sphinx.
Documentation in Python (3/3) - Introduction to reStructured Text25:00
In this video, we run through a reStructured Text primer, equipping you with the basics of this lightweight markup language used by Sphinx to generate documentation.
Introduction to Sphinx (1/2)21:58
In this video, we introduce Sphinx as a tool to automate the process of building documentation.
Introduction to Sphinx (2/2)26:21
In this video, we continue our introduction to Sphinx, covering more extensions, including how to build API references from already-documented source code.
Introduction to Read the Docs12:28
In this video, we introduce Read the Docs and demonstrate how to create external documentation from your repository hosted on GitHub.
Sphinx and Read the Docs references0:21
Changelogs12:33
In this video, we cover changelogs, including why they are an important piece of documentation and how to include them in your project's repository.

Requirements

Basic Programming Knowledge: Students should have a foundational understanding of programming, in Python, as the course heavily focuses on Python development. Knowledge of basic programming concepts like variables, loops, functions, classes and data structures (lists, dictionaries, etc.) is essential.
Understanding of Basic Finance Concepts: While an in-depth knowledge of finance isn't mandatory, familiarity with basic financial concepts and markets will be beneficial. This includes understanding stocks, and basic financial terminology.
Mathematics Proficiency: A solid grasp of basic mathematics, especially in areas like linear algebra and statistics, is important. The course will involve some level of mathematical computation and analysis.
Computer with Required Software: Access to a computer capable of running Python and related software tools (like IDEs, Git, etc.). This is crucial for participating in hands-on workshops and projects.

Description

Embark on a transformative journey into the world of Python programming tailored for the high-octane field of quantitative finance with our university-semester length course, Writing Production-Grade Code for Quantitative Developers. This course is meticulously designed to bridge the gap between academic learning and the dynamic requirements of the quantitative development sector, focusing on the nuances of coding that are vital for success in this challenging field.

Our curriculum is a deep dive into the universe of production-ready Python coding, where every module is an essential building block towards becoming an exceptional quantitative developer. We begin with an exploration of the roles and responsibilities of quantitative developers, delving into the specific skills and tools required in the industry, and how Python plays a pivotal role. You'll learn about the latest industry trends, the increasing demand for proficient quantitative developers, and the characteristics that make Python code production-ready.

The course covers a broad spectrum of topics, including using Linux in your Python development workflow, techniques in structuring and organizing projects, mastering Git for source control, and best practices in creating quality code and documentation. You'll gain hands-on experience in working with the wider Python ecosystem, including virtual environments and dependency management.

By the end of this course, you won't just learn Python; you will have honed a skill set that makes you an invaluable asset in the world of quantitative finance, ready to tackle the challenges faced by top hedge funds around the globe. Join us and transform your understanding of Python in quantitative finance, setting you on a path to career excellence.

Who this course is for:

Aspiring Quant Developers / Algorithmic Traders and Programmers
Quant Traders and Researchers
Data Analysts and Scientists
Tech-Savvy Finance Enthusiasts
Individuals Fascinated by Financial Markets

Writing Production-Grade Python Code for Quant Developers

What you'll learn

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Course content

Introduction to Quantitative Development5 lectures • 42min

Implementing Academic Research6 lectures • 1hr 8min

Setting up your workshop10 lectures • 2hr 8min

Mastering Git and Source Control18 lectures • 2hr 47min

Python Virtual Environments and Dependency Management4 lectures • 1hr 40min

Creating clean code7 lectures • 1hr 42min

Refactoring Code5 lectures • 1hr 1min

Documentation11 lectures • 2hr 52min

Requirements

Description

Who this course is for: