Python Advanced (7.9.2020 - 10.9.2020)¶

This is a training for a team which is already experienced in Python programming. There were some special requirements for the training, such as to loose a couple of words about AI/machinelearning and other topics, as well as a fuzzy “bring us advanced stuff”.

The training was accompanied by a lot of improvised live hacking.

Preparation ¶

Workspace Setup ¶

Github for Exercises ¶

Please create Github accounts and send them to training@faschingbauer.co.at. We will do exercises via a private repository on Github. (See the privacy statement.)

Agenda ¶

Advanced Core Python Topics ¶

Python is easy; one can solve nontrivial problems in only a few lines of code, in no time. This does not mean that you have to fully understand the language - which is good because this is what makes the language easy.

On the other hand, there’s always a line to cross where you wish you knew more. Here the more advanced core Python topics that shall be covered.

Special Topics ¶

Machine Learning, Artificial Intelligence
Unit Testing, Test Driven Development, Design Patterns
- Excerpt from Unittesting and Test Driven Development (/trainings/material/pdf/060-design-patterns-unittests.pdf)
- The unittest Module
Web programming with Jango and/or Flask

Log ¶

Following is a recap of what has happened. File names are relative to the root of the Github repository we were working from.

Day 1 ¶

Rushed through basics,

Put a strong focus on Python features,

References, (Im)mutability
Sequential Datatypes
Indexing and Slicing
while Loops. The else clause, mainly - everyone was supposed to know what a while loop is.
for Loops.
- else clause
- The range Function. Whetting appetite for the Iteration livehacking session on day 2.

Day 2 ¶

Livehacking: Iteration, Comprehensions, and Generators, covering
- List comprehensions
- The range function
- Writing generators using yield
- Generator expressions
Livehacking OO
- joerg-livehacking/oo.py
  - initially: Thermometer, ctor, get_temperature()
  - __init__, self, etc. (self can also read this)
  - th.__dict__
  - private, pros and cons
  - properties (r/w)
- inheritance
  - joerg-livehacking/abstract-base-class.py, joerg-livehacking/abstract-base-class.cpp
  - Insert one step without abc before it, and then show what abc can do
  - explain “check errors as early as can” ⟶ at ctor time, rather than at method call time.
Livehacking design patterns
- joerg-livehacking/composite.py. Using the thermometer hierarchy, a “composite” thermometer was created. That thermometer uses (has) a set of concrete thermometers to calculate the average room temperature.
- joerg-livehacking/adapter.py. Fictional scenario …
  - The Unser thermometer framework contains a number of thermometer implementations which all support the get_temperature_celsius() method.
  - A collaboration with a competitor is launched. That competitor has a similar set of thermometer implementations. The difference between Eana and Unser is that Eana thermometers do not support get_temperature_celsius(), but rather only get_temperature_fahrenheit().
  - We employ the adapter pattern and create one special thermometer in the Unser hierarchy
    class EanaAdapter(UnserThermometer): ...

Day 3 ¶

Revisit abstract base classes
- Discuss duck typing.
- Morph joerg-livehacking/abstract-base-class.py into joerg-livehacking/duck-typing.py.
- Explaining how abc shifts duck errors from call to initialization
Visitor pattern. Not every pattern in the “Gang of Four” book should be considered a real pattern. For example, the Visitor pattern turn into an idiom for languages that don’t support generators.
- joerg-livehacking/visitor.py. Classic OO implementation of the visitor pattern as a DFS traversal. Together with callbacks and all convolutions. Took sideways like,
  - show how __call__ makes a class callable.
  - show how __str__ and __repr__ work together in print()
- joerg-livehacking/visitor-generator.py. “I don’t want to implement a visitor!”, poor user says. “I only want to iterate over the tree in DFS order!”
  
  Implement DFS iteration using yield from which delegates iteration into recursion.
TDD and Unit Testing theory; using excerpts from the Design Patterns deck of slides. Explain terminology; fixtures and such.
Start hacking on project. Agreed upon myself doing live hacking. Doing TDD.
- Project/sensor/sensordata.py, and Project/tests/sensordata_tests.py. Prepare TDD; explain suites, cases, fixture, assertions.
- While writing data classes (holding only attributes and no functionality), explain namedtuple. Use that to implement sensor.sensordata.HistoryData.
- Slowly fix things, in a test driven way. Discuss, team giving input, all really fine.

Day 4 ¶

Decorators theory, and livehacking. Mainly to see how flask routes work.

Positional and Keyword Arguments

Closures

Decorators

Continue project; add CSV import.

Project/programs/csvreport.py

sqlite3 export, trying out the DBAPI 2.0 interface.

Project/programs/csv2sqlite3.py

Flask frontend, reading sqlite3 db.

Project/programs/flaskerl.py

After Work Party ¶

From my point of view, the training went really fine. Not everyone is equally satisfied with the outcome (we didn’t get to the AI topics, for example), but I have the impression that I brought it over.

As a gift to myself, I had reserved Thursday night at Gmundner Hütte. After the training I went back to Hoisn Wirt (which is where I stayed during the training - really fine), changed clothes, and started to climb the Traunstein via Zierlersteig.

See here for the description and pictures from this extraordinary hike.

Python material	Python Programming: From Absolute Beginner to Advanced Productivity
PDF Slides (Design Patterns)	`Design Patterns`

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