Python for Analysts | Cambridge Spark

DURATION: 2-DAY COURSE

What you will learn

In this course you will learn everything from code quality and testing to creating virtual environments and type checking

Software:

Python 3

Anaconda

Prior general introductory programming experience (familiarity with basic concepts such as variable, loops, functions).

DAY ONE

Development Tools
- Jupyter Notebook
- Jupyter Lab
- VS Code and Python
- Running Python scripts and applications
Control, Flow, Data Structure and Strings
- Conditionals
- List: indexing, slicing, stepping
- Dict, Set, Tuple
- Iteration
- String Format, f-string
Code Quality
- Pep8
- Pylint
- Flake
- Cyclomatic Complexity
- Writing Pythonic Code
Testing
- Unit testing vs. Integration testing vs. System testing
- Using the unittest library
- Assertions and Diagnostics
- Given / When / Then pattern
- Testing Best Practices
Software Development Lifecycle
- Version controlling
- Continuous integration
- Continuous delivery

DAY TWO

Functional Programming constructs in Python
- Mutable and immutable objects
- zip, izip, partial
- List and Dict comprehensions
- Lambda expressions
Working with Regular Expressions
- Search, findall, finditer
- Groups
- Substitution
Organising Code
- Functions
- Classes
- Modules
- Packages
Packages, Modules and External Libraries
- Packages, sub-packages, modules, init.py
- Project structure, imports
- Installable packages, setup.py, command-line entry points
- Site-packages directory
Repeatable Configurations and Deployment
- Managing Packages with pip
- Creating Virtual Environments
- Conda environments
Type checking
- Dynamic vs. Static type checking
- Python Type declarations: typing (PEP 483, PEP 484, PEP 526)
- Mypy: Optional Static typing in Python

We will email you within the next 24 hours to arrange a quick call to help with any questions about the programme and recommend pre-course materials.

We look forward to speaking with you.

Director