Using Debuggingbook Code in your own Programs

This notebook has instructions on how to use the debuggingbook code in your own programs.

Can I import the code for my own Python projects?

Yes, you can! (If you like Python, that is.) Once the book is out of beta, we will provide a debuggingbook Python package that you can install using the pip package manager:

$ pip install debuggingbook

Once this is installed, you can import individual classes, constants, or functions from each notebook using

>>> from debuggingbook.<notebook> import <identifier>

where <identifier> is the name of the class, constant, or function to use, and <notebook> is the name of the respective notebook. (If you read this at debuggingbook.org, then the notebook name is the identifier preceding ".html" in the URL).

Here is an example importing Debugger from the chapter on debuggers, whose notebook name is Debugger:

>>> from debuggingbook.Debugger import Debugger
>>> with Debugger():
    function_to_be_observed()

The "Synopsis" section at the beginning of a chapter gives a short survey on useful code features you can use.

Can I use the code from within a Jupyter notebook?

Yes, you can! Once the book is out of beta, you would first install the debuggingbook package (as above); you can then access all code right from your notebook.

Another way to use the code is to import the notebooks directly. Download the notebooks from the menu. Then, add your own notebooks into the same folder. After importing bookutils, you can then simply import the code from other notebooks, just as our own notebooks do.

Here is again the above example, importing Debugger from the chapter on debuggers – but now from a notebook:

import bookutils
from Debugger import Debugger
with Debugger():
    x = 1 + 1

If you'd like to share your notebook, let us know; we can integrate it in the repository or even in the book.

Can I just run the Python code? I mean, without notebooks?

Yes, you can! (Although we'd always recommend executing the notebooks instead – they have all the text, and far richer inputs and outputs.) You can download the code as Python programs; simply select "Resources $\rightarrow$ Download Code" for one chapter or "Resources $\rightarrow$ All Code" for all chapters. These code files can be executed, yielding (hopefully) the same results as the notebooks.

The code files can also be edited if you wish, but (a) they are very obviously generated from notebooks, (b) therefore not much fun to work with, and (c) if you fix any errors, you'll have to back-propagate them to the notebook before you can make a pull request. Use code files only under severely constrained circumstances.

Which other packages do I need to use the Python modules?

We have attempted to limit the dependencies to a minimum (sometimes using ugly hacks). Generally speaking, if you encounter that a module X is not found, just do pip install X. Most notebooks only need modules that are part of the standard Python library.

For a full list of dependencies, see the configuration files within the binder folder in the project repository; these list all Linux and Python packages required.

Creative Commons License The content of this project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The source code that is part of the content, as well as the source code used to format and display that content is licensed under the MIT License. Last change: 2020-11-03 15:15:28+01:00CiteImprint