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+(python-related-procedures)=
+# Python-related procedures
+
+In this section, we will show you a few things related specifically to running code reproducibly with Python and Jupyter notebooks. . For more general debugging tips for Python and other computer languages, see [our wiki](https://github.com/labordynamicsinstitute/replicability-training/wiki/Python-Tips).
+
+
+## Best practice to reproduce a Python paper (Python environments)
+
+You should create a Python environment that is dedicated to the project. See [Anaconda instructions](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) as one possible method, [venv](https://docs.python.org/3/library/venv.html) as another one, though others exist.
+
+Here's `venv` version in a nutshell ([full guide](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/#creating-a-virtual-environment))
+
+- Ensure `venv` exists:
+```
+pip3 install pyenv
+```
+- Create a new environment
+```
+python3 -m venv /path/to/new/virtual/environment
+```
+or if using relative paths
+```
+python3 -m venv env
+```
+
+which will create `/path/to/new/virtual/environment` or (relative to your current working directory) `env`. That directory will now contain all of your project-related Python packages.
+
+To activate:
+```
+source env/bin/activate
+```
+
+On Windows Bash (depends on install)
+
+```
+python -m venv env
+source env/Scripts/activate
+```
+
+To deactivate:
+```
+deactivate
+```
+
+
+## Making Python code dynamic
+
+In general, Python code should not have hard-coded paths. Python programs are aware of their own location, and other directories should be relative to that. However, some authors may still follow (econ-specific) norms, and hard-code paths. 
+
+In that case, do the following:
+
+
+Say the author has code like
+
+```python
+xlsread('C:\Users\me\submission\AEJMacro\yesterday\data.xlsx')
+```
+
+
+At the top of the program, add the following lines:
+
+```python
+import os
+rootdir = os.path.realpath(__file__)
+```
+
+Then, wherever the hard-coded path appears, replace it with:
+
+```python
+xlsread(os.path.join(rootdir,'data.xlsx'))
+```
+
+## Installing packages
+
+Sometimes, authors will list the packages they used. There are a few options:
+
+### They provide a `requirements.txt` file
+
+If the authors provide a `requirements.txt` file, you can install all the packages at once. From an appropriate terminal, run:
+
+```bash
+pip install -r requirements.txt
+```
+
+### They provide a `environment.yml` file
+
+If the authors provide an `environment.yml` file, they used Conda as the Python system manager. From an appropriate terminal, run:
+
+```bash
+conda env create -f environment.yml
+```
+
+### They provide a list of packages
+
+If the authors provide a list of packages, the easiest way is to create a simple `requirements.txt` file with a text editor (e.g., VS Code), then proceed as with the first option.
+
+
+
+### Using Anaconda Package manager
+
+This is known to work on  CISER (CCSS-Classic).
+
+:::{admonition}  This may not be the way it works on CCSS-Cloud. 
+:class: dropdown
+Needs an update
+:::
+
+If using the default "Jupyter" link in the Start Menu, the working directory won't be right. Assuming that you have set your Workspace to `L:\Documents\Workspace`, the following will create a Jupyter Notebook in the right location (thanks to Louis Liu for creating this Howto)
+
+#### Search "anaconda prompt" from the start menu. right click on the app when it appears and pin it to the taskbar.
+
+![Step 1](images/Jupyter_howto_step1.png)
+
+#### Right click on anaconda prompt in the taskbar (looks like a black window, similar to command line or terminal). Right click on "anaconda powershell prompt" in the tasks menu that pops up, and then properties.
+
+![Step 2](images/Jupyter_howto_step2.png)
+
+#### In the properties window, go to the shortcut tab and change the "Start in:" field to U:\Documents\Workspace or whichever directory you keep your bitbucket repos in. Click apply.
+
+![Step 3](images/Jupyter_howto_step3.png)
+
+#### Next, click on the anaconda prompt shortcut in the taskbar. When anaconda prompt opens, enter the command "`Jupyter notebook`"
+
+![Step 4](images/Jupyter_howto_step4.png)
+
+### Conda on BioHPC
+
+If a replication package uses `conda` for package management, rather than `pip`, follow instructions [at BioHPC](https://biohpc.cornell.edu/lab/userguide.aspx?a=software&i=574#c) on how to install `miniconda` in your home directory, then add the line
+
+```bash
+source $HOME/miniconda3/bin/activate
+```
+
+at an appropriate location in the code (for instance, replacing `module load conda`).
+
+
+## Running Jupyter Notebooks
+
+### Manually
+
+In order to run Jupyter notebooks, do the following, once you have opened the Jupyter Notebook or Jupyter Lab interface:
+
+- Navigate to the directory where the notebook is located
+- Open the notebook
+- Clear all the cells: `Cell` -> `All Output` -> `Clear`
+- Run all the cells: `Cell` -> `Run All`
+- Save the notebook: `File` -> `Save and Checkpoint`
+
+### From the command line
+
+You should also be able to do the following from the command line:
+
+::::{tab-set}
+
+:::{tab} Linux/macOS
+
+If you have a LaTeX installation, you can convert the notebook to a PDF using the following commands:
+
+```bash
+# requires a latex installation
+pip install nbconvert
+jupyter nbconvert --to notebook --execute mynotebook.ipynb
+juptyer nbconvert --to pdf                mynotebook.ipynb
+```
+
+Alternatively, you can convert the notebook to a PDF more closely resembling the HTML view using the following command:
+
+```bash
+pip install nbconvert
+pip install pyppeteer
+jupyter nbconvert --to notebook --execute mynotebook.ipynb
+jupyter nbconvert --to webpdf --allow-chromium-download mynotebook.ipynb
+```
+
+:::
+
+:::{tab} Windows
+
+Not sure yet. Needs augmentation.
+
+:::
+
+::::
+
+## Document the packages YOU used
+
+If you had to iteratively install packages, you should run the following command at the end of your whole process:
+
+```bash
+pip freeze > requirements.txt
+```
+
+and add that output (the contents of the `requirements.txt` file) to the repository, and to an appendix in the report. Take care to not overwrite author-provided `requirements.txt` files.
diff --git a/_toc.yml b/_toc.yml
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+++ b/_toc.yml
@@ -60,6 +60,7 @@ parts:
       - file: 96-11-using-config-r
       - file: 96-12-running-r-code
     - file: 96-20-using-matlab
+    - file: 96-30-running-python-jupyter
     - file: 96-50-using-docker
     - file: 96-70-using-mathematica
     - file: 96-80-using-ox
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