Python Bespoke Agenda NL - 2 days

Data types and Duck Typing

• Composite Data types ( List , Tuple , Dict , Set )
• The Python collections module
• Connecting algorithms and data via the data’s abilities (duck typing)

Sequences and Iterables

• Python comprehensions (List-, Dict- and Set-comprehensions)
• Generators (lazy vs eager) and generator expressions
• zip and enumerate
• The Python itertools module

Functions in Python

• Default-Arguments and the caveats of reference data types for default values
• Functional programming: functions as 1st class citizens
• map and reduce
• inner functions
• Currying
• Separation of aspects via decorators
• [Optional: the Python functools module and some aspects like caching or
• currying]

Files and IO in Python

• files as a byte-blob
• files as an iterable (files as a generator)
• the with-statement (the context-manager idiom)
• creating, reading, updating and deleting files
• creating and deleting directories, listing and searching for files
• Importing/Exporting data into Python via Pandas

Modularising code

• modules and packages in Python
• ways to import from libraries
• the import-guard idiom

Object Orientation in Python

• classes, objects and relationships in an OO-World
• magic methods and some protocol ideas (e.g. the iterator protocol)

Error-Handling

• separation of concerns. - handling and raising exceptions
• exceptions as an object-oriented concept

Misc

• some test ideas in Python (doc-test, unit-test, test frameworks)
• some profiling ideas in Python

Jupyter Notebooks for Scientific Computing

Pandas

• a use-case example with Pandas for exploration and number-crunching

Python with Matlab - (If time allows)

• call Python from Matlab
• call Matlab from Python
• passing Data