Integrated Development Environments (IDEs)#

The teaching contents of this eBook build on so-called Application Programming Interfaces APIs) and Integrated Development Environments (IDEs).

An API represents a computing interface that enables interactions between multiple software intermediaries. Modular programming becomes easy with an API because it systematically hides complex information that is not necessarily needed to write code according to industry standards. For instance, an API can define the interface between an application (such as Python or Word) and an Operating System (OS) such as Windows, Linux, or macOS (also referred to as platform).

An IDE enables the definition of a project to use, for example, a specific Python environment, and it enables robust coding by pointing out issues directly in the code, even before it ran for the first time. Powerful IDEs go even further and assist in documenting code with markdown (.md files) and directly pipe into git (see the Version Control : git).

Which IDE to choose?

The answer to this question depends on the platform you are using (e.g., Windows or Linux), your personal preferences, and your goals.

For writing Python software itself, the Author’s preference is in general Atom (optionally and on Windows only: PyCharm). To test and run Python code (software) locally, for Windows users, the installation of Anaconda is almost indispensable. Linux users will be mostly fine with their system setup without the need to install Anaconda or PyCharm.

For code documentation, examples, and the best learning experience in the Python courses featured in this eBook, consider installing JupyterLab locally. Windows users find instructions in the Jupyter on Windows section. Linux users find instructions in the Jupyter on Linux section.

Once you have an IDE installed, carefully read the instructions for installing Python.


Anaconda is the favorite solution for working with the Python tutorials in this eBook on Windows. Linux users may want to install the text and code editor Atom and optionally Jupyter on Linux.

Anaconda Navigator#

Use Anaconda on Windows

Anaconda works well on Windows, but Linux (or also macOS) users will have a better experience with advanced text editors such as Atom.

Anaconda is a Python and R distribution that enables the usage of a couple of IDEs such as PyCharm, Spyder, or JupyterLab (Notebook).

The very first step to getting started with Anaconda consists in downloading and installing Anaconda where students may use the individual license for educational training purposes (note that a commercial license needs to be purchased for for-profit organizations). On Windows, Anaconda should be installed in the LOCAL user folder (e.g., C:\users<your-user-name>\AppData\Local). Linux or macOS users find download and installation instructions directly at the developer’s website, tailored for their specific distribution, even though they might be better of with Atom.

After the successful installation of Anaconda, IDEs for Python programming or markdown editing can be directly installed by launching the Anaconda navigator. conda environments can be created later, following the instructions in the conda env (Windows Preference) section.

Learn more about installing Anaconda (with Python) and this eBook’s support package called flusstools in the Python conda quick guide section and in the video below.


Anaconda may create large environments that require several gigabytes of storage. To install lightweight environments, use Miniconda. Miniconda does not include Anaconda Navigator and to enable working with Jupyter notebooks (in Windows):

  1. Click on Start.

  2. Type Anaconda Prompt and hit enter (use Miniconda3). A Terminal window (black background) opens.

  3. In Anaconda prompt type conda install jupyter and confirm with y when the Terminal asks Proceed ([y]/n)?.

To work with Jupyter notebooks (open, create, or modify), type jupyter lab (or jupyter notebook) in Anaconda Prompt (Miniconda3) and hit Enter. The JupyterLab application will open in the default web browser.

PyCharm with Anaconda#

Jetbrains PyCharm (Community Edition) is an open-access IDE for non-commercial use. Alternatives are Spyder IDE (for Python) or RStudio (R and Python). However, before launching any project in an IDE, the installation of an interpreter (e.g., Python or R) is necessary (we already installed an interpreter with Anaconda).

PyCharm is available as a module within Anaconda Navigator (i.e., Anaconda’s graphical user interface). To enable PyCharm in Anaconda, download PyCharm from the developer’s website and install PyCharm. A reboot may be required after the installation.

After the installation of PyCharm for Anaconda, open Anaconda Navigator:

  1. Open Anaconda Navigator and make sure to be in the Home tab.

  2. If the installation of PyCharm was successful, click on the Launch button to open PyCharm.

  3. In PyCharm click on + Create New Project

  4. Option 1 (preferred): Use the developer’s up-to-date documentation for setting up PyCharm with Anaconda.

  5. Option 2 (quick to read, but may fail): A window will open - enter:

  • Location - Select a local directory for the project (e.g., C:/hydro/project)

  • Project Interpreter - Check the Existing interpreter box and select an existing interpreter.

  • Click on the Create button.

All set - you are ready to edit Python (.py), markdown (.md for documentation), and other file types.

Finalize the Installation of Python

Carefully read the instructions for installing Python on your platform.


Jupyter is a spin-off of IPython, which is “a rich architecture for interactive computing”. JupyterLab is a product of the nonprofit organization Project Jupyter, which develops “open-source software, open-standards, and services for interactive computing across dozens of programming languages”. A Jupyter notebook (.ipynb file) enables the combination of markdown text blocks with executable code blocks. Essentially, a Jupyter Notebook is a JavaScript Object Notation (JSON file. The structure of JSON files enables the easy export of .ipynb notebooks to many other open standard output formats such as HTML, LaTeX, Markdown, Python, presentation slides, or PDF. The Jupyter kernels support the three core programming languages Julia, Python and R, and many more Jupyter kernels (currently 49) for other programming languages exist.

Working with Jupyter

Get familiar with JupyterLab, by creating files, adding new Markdown or Python cells, and running cells. The essentials of markdown are explained in the Markdown section (short read). Learning Python is more than a short read and the Python Basics chapter provides some insights (takes time).

Jupyter on Windows#

Anaconda Navigator alternatively provides the application Jupyter Notebook. However, JupyterLab is the Project Jupyter’s next-generation user interface, which is more flexible and powerful. This is why this website refers to JupyterLab rather than the Jupyter Notebook app. The following sections explain how to install it on your Windows computer, either by using the graphical user interface of Anaconda Navigator, or the conda prompt command line (recommended).

Via Anaconda Navigator#

  1. Open Anaconda Navigator and make sure to be in the Home tab.

  2. Look for JupyterLab and click on the Install button (if already installed, there is only a Launch button visible).

  3. After successful installation, open JupyterLab, by clicking on the Launch button.

  4. JupyterLab opens in the default web browser, where Jupyter notebooks (.ipynb) or Python files can be created and edited.

Extensions and Spellchecker#

Many additional features for JupyterLab are available through nbextensions, which can be installed through Anaconda Prompt:

conda install -c conda-forge jupyter_contrib_nbextensions

When reading through the Python tutorials on this website, you will probably find one or another spelling mistake (please report mistakes!). In particular, the Python sections may be affected because they were created with JupyterLab, where there is no spell checker pre-installed. To avoid at least the most unpleasant errors you can install a spellchecker in Jupyter. One solution is to install @ijmbbarrs spellchecker, which requires installing nodejs (through Anaconda Prompt and in addition to nbextensions):

conda install -c conda-forge nodejs
jupyter labextension install @ijmbarr/jupyterlab_spellchecker

The spellchecker uses Typo.js as a dictionary and only identifies misspelled words without proposing corrections. More details on spellchecking are available at the developer’s website.

In the case that several warning messages occur when starting JupyterLab (such as [W 18:49:22.283 NotebookApp] Config option template_path not recognized by LenvsHTMLExporter. Did you mean one of: template_file, template_name, template_paths?), downgrade Jupyter Notebook from version 6.x to 5.6.1 (there is currently an issue with the temp_path variable):

conda install "nbconvert=5.6.1"

Jupyter on Linux#

To install JupyterLab on Linux, open Terminal and make sure that pip/pip3 is installed:

sudo apt install python3 python3-pip python3-venv

Export the user-level bin to the PATH environment and install JupyterLab in the user space with the following commands:

export PATH="$HOME/.local/bin:$PATH"
pip install --user jupyterlab


It might be necessary to replace pip with pip3 (depending on the Linux distribution).

To start JupyterLab tap:


The command jupyter-lab starts a localhost server that runs JupyterLab, which will open up in a web browser like an interactive website.


Closing Terminal will also terminate the localhost that runs JupyterLab. Thus, do not close Terminal as long as you are working with JupyterLab, in particular, when there are unsaved books.

A Debugger for Jupyter#

To better understand and troubleshoot code crashes, a debugger represents a great relief. Unfortunately, debugging in Jupyter can cause some headache in the absence of an inherent debugging tool. To get a debugger working with Jupyter, check out this blog entry from Jupyter Project.


Sublime is one of the most popular editors for multiple (computer) languages. However, it is commercial software that is only free to use during an evaluation period without time limit. Read more about it at

To install it on Debian Linux platforms, open Terminal and tap (source:

wget -qO - | gpg --dearmor | sudo tee /etc/apt/trusted.gpg.d/sublimehq-archive.gpg

Then select the stable channel (the dev channel has more features but also more bugs):

echo "deb apt/stable/" | sudo tee /etc/apt/sources.list.d/sublime-text.list

Finally, update apt and install Sublime:

sudo apt update
sudo apt install sublime-text

If an error message occurs, make sure apt works with https sources:

sudo apt install apt-transport-https

When working with sublime, consider using an advanced spell check package, such as LanguageTool. More useful packages for sublime can be found at Packages can also be found by hitting the CTRL + Shift + P keys (in Sublime) to open Package Control. Then, type install and enter the name of the package you are looking for in the box.

To enable modification of user settings, go to Preferences (top menu bar) > Settings and save the opening settings file either as ~./config/sublime-text/Packages/Default/Preferences.sublime-settings (recommended for first-time saving) or ~./config/sublime-text/Packages/User/Preferences.sublime-settings. Then, edit the desired settings: for instance, look for spell_check and set it to true to default-enable spell checking. Save the .sublime-settings file to apply changes.


Atom is a hackable text editor that is compatible with almost any programming language. While its bare installation has little functionality, the omni-compatibility can be enabled by installing desired packages (e.g., for Python, Markdown, or LaTex). Another big advantage of Atom is the availability of powerful spell checker packages.

Atom will sunset on December 15, 2022

The Atom developers at GitHub (i.e., Microsoft) announced that they sunset (archive) Atom on December 15, 2022 read more. That means, no updates and no maintenance are available as of December 15, 2022, but Atom can still be downloaded. It is not yet clear if Atom will reach its end of life or if some one will take up the maintenance and development of Atom.


Linux users find installers for various distributions at Debian (Ubuntu), Red Hat / CentOS, Fedora, and SUSE find easy installation guides at

The short version for Debian (Ubuntu) is:

  • Add the Atom package repository to the system:

wget -qO - | sudo apt-key add -
sudo sh -c 'echo "deb [arch=amd64] any main" > /etc/apt/sources.list.d/atom.list'
sudo apt update
  • Then install Atom:

sudo apt install atom

Windows users can download Atom from and install the executable.

Atom Packages#

Get Useful Atom Packages#

To install packages:

  • Windows users go to File > Settings > + Install

  • Linux users go to Edit > Preferences > + Install

The following (additional) packages are useful for working with the contents of this eBook:

  • ide-python provides language support for Python code

  • language-markdown (optional) for writing documentations with Markdown.

  • language-restructuredtext (optional) for writing documentations with reStructuredText.

  • language-tex (optional) to write reports or presentations with LaTex

  • platformio-ide-terminal (platformio-ide) adds a terminal window to Atom

  • python-debugger enables debugging of Python code

  • python-docstring facilitates inline documentation of Python code

  • python-indent facilitates indentation of code blocks

  • python-requirements enables to install required packages for running Python code

  • for Python code formatting, definitions, refactoring (renaming), and many more, ONE of the following options may be used (avoid installing multiple packages that do the same job):

    • python-tools

    • python-black

    • atom-beautify - make sure to also pip install yapf, and pip install --upgrade autopep8 and define the autopep8 script directory as autopep8 interpreter of the package settings (e.g., on Linux set /home/user/venv/vflussenv/bin/autopep8 in Atom > Edit > Preferences > Packages > Atom Beautify > Settings > Executables > autopep8 > Binary/Script Path)

  • script enables to run Python and many other code types (read the docs); after the installation, running a code (Python) file can be triggered by clicking on the Packages top menu > Script > Run Script.

Spell Checking#

The default-installed spell-check package runs basic spellcheck for plain text, GitHub Markdown, AsciiDoc, and reStructuredText by using the system’s default dictionaries.

If spell-check is not revising the current document, click on the document in question in Atom and open the Command Palette (Windows: press CTRL + Shift + P). In the Command Palette type Editor: Log Cursor Scope. A pop-up window will show the current scope. To make sure that the current scope is checked by spell-check, open the Atom Settings (on Windows) or Preferences (on Linux) and find the spell-check package. Click on Settings and find the Grammars field. Click in the Grammars field and add the current scope here. Restart Atom to make sure that the changes are implemented.

Debian Linux users can install the hunspell package with support for many languages:

sudo apt install hunspell-en-gb
sudo apt install myspell-en-gb

Other packages enable spell checking for particular file formats:

  • linter basic package for spell checkers

  • linter-spell grammar and spell checking basis

  • linter-markdown spell checks Markdown files

  • linter-spell-rst spell checks reStructuredText


linter * packages might conflict with spell-check. If your files are not spell-checked anymore after installing linter * , roll back the installation of linter and reset spell-check.

Read more at for more information on other distributions and dictionaries.

Usage with Python#


To enable Python compatibility, first, visit the Python (Installation) section and install flusstools for your system (i.e., either in a virtual or conda environment).

Open Terminal and activate the environment where flusstools is installed. For instance, if flusstools is installed in a virtual environment called vflussenv that lives in the user home directory (/home/USER/) according to the Python installation instructions in this eBook (see pip quick guide), activate the environment as follows:

cd ~
source vflussenv/bin/activate

Open Anaconda Prompt and activate flussenv (given that flusstools is installed according to the conda quick guide):

conda activate flussenv

Then, start Atom in the (pip or conda) environment through Terminal (Linux) or Anaconda Prompt (Windows):


Atom should open and provide the option to select a folder where a Python project will live or is already living. After selecting a folder, start editing your Python (.py) files. For running Python scripts, there are two options:

first set up the Script package:

  • Make sure that the script package is installed.

  • Configure the Srcipt packge in Atom by clicking on Packages > Configure Script (Alt + Ctrl + Shift + O):

    • In the Command field enter python (or python3).

    • Click on Save as profile and enter a prilfe name (e.g. flussprofile).

To run a Python script:

  • Either go to Packages > Script > Run with profile and select flussprofile

  • Or press Alt + Ctrl + Shift + B

Make sure to install the atom-python-virtualenv package (see the section on installing Atom packages) and select vflussenv from the status bar at the bottom of the window as indicated in the below figure.


To run a Python script press cdCtrl + Shift + B

More Console Options#

While the script package enables running a Python script, it may be desirable to have a built-in Python console window running in Atom. To this end, the platformio-ide-terminal package tweaks into the system’s default terminal (Terminal on Linux or PowerShell on Windows 10), which can run an existing installation of Python (i.e., Python must be installed on the system in some form). Depending on your platform, follow the instructions in the Atom and Python section.