99 lines
3.4 KiB
Markdown
99 lines
3.4 KiB
Markdown
# Course Setup and Overview
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Welcome to Practical Python Programming! This page has some important information
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about course setup and logistics.
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## Course Duration and Time Requirements
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This course was originally given as an instructor-led in-person
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training that spanned 3 to 4 days. To complete the course in its
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entirety, you should minimally plan on committing 25-35 hours of work.
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Most participants find the material to be quite challenging without
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peeking at solution code (see below).
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## Setup and Python Installation
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You need nothing more than a basic Python 3.6 installation or newer.
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There is no dependency on any particular operating system, editor,
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IDE, or extra Python-related tooling. There are no third-party
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dependencies.
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That said, most of this course involves learning how to write scripts
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and small programs that involve data read from files. Therefore, you
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need to make sure you're in an environment where you can easily work
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with files. This includes using an editor to create Python programs
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and being able to run those programs from the shell/terminal.
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You might be inclined to work on this course using a more interactive
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environment such as Jupyter Notebooks. **I DO NOT ADVISE THIS!**
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Although notebooks are great for experimentation, many of the
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exercises in this course teach concepts related to program
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organization. This includes working with functions, modules, import
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statements, and refactoring of programs whose source code spans
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multiple files. In my experience, it is hard to replicate this kind
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of working environment in notebooks.
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## Forking/Cloning the Course Repository
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To prepare your environment for the course, I recommend creating your
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own fork of the course GitHub repo at
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[https://github.com/dabeaz-course/practical-python](https://github.com/dabeaz-course/practical-python).
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Once you are done, you can clone it to your local machine:
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```
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bash % git clone https://github.com/yourname/practical-python
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bash % cd practical-python
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bash %
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```
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Do all of your work within the `practical-python/` directory. If you
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commit your solution code back to your fork of the repository, it will
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keep all of your code together in one place and you'll have a nice
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historical record of your work when you're done.
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If you don't want to create a personal fork or don't have a GitHub account,
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you can still clone the course directory to your machine:
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```
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bash % git clone https://github.com/dabeaz-course/practical-python
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bash % cd practical-python
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bash %
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```
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With this option, you just won't be able to commit code changes except
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to the local copy on your machine.
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## Coursework Layout
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Do all of your coding work in the `Work/` directory. Within that
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directory, there is a `Data/` directory. The `Data/` directory
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contains a variety of datafiles and other scripts used during the
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course. You will frequently have to access files located in `Data/`.
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Course exercises are written with the assumption that you are creating
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programs in the `Work/` directory.
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## Course Order
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Course material should be completed in section order, starting with
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section 1. Course exercises in later sections build upon code written in
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earlier sections. Many of the later exercises involve minor refactoring
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of existing code.
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## Solution Code
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The `Solutions/` directory contains full solution code to selected
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exercises. Feel free to look at this if you need a hint. To get the
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most out of the course however, you should try to create your own
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solutions first.
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[Contents](Contents.md)
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