When working with Jupyter Notebook, you will find yourself needing to distribute your Notebook as something other than a Notebook file. The most likely reason is that you want to share the content of your Notebook to non-technical users that don’t want to install Python or the other dependencies necessary to use your Notebook. The most popular solution for exporting your Notebook into other formats is the built-in nbconvert tool. You can use nbconvert to export to the following formats:
- HTML (–to html)
- LaTeX (–to latex)
- PDF (–to pdf)
- Reveal JS (–to slides)
- Markdown (md) (–to markdown)
- ReStructured Text (rst) (–to rst)
- executable script (–to script)
The nbconvert tool uses Jinja templates to convert your Notebook files (.ipynb) to these other static formats. Jinja is a template engine for Python. The nbconvert tool depends on Pandoc and TeX for some of the conversions that it does. You may need to install these separately on your machine. This is documented on ReadTheDocs. Continue reading How to Export Jupyter Notebooks into Other Formats
In this episode, you will learn the basics of Python decorators and what the are good for.
You can also read about decorators in a couple of other articles on my blog:
I don’t usually write about my book writing while the book is in progress on my blog, but I know some readers probably wonder why there are times where I am not writing blog posts as regularly as I usually do. The reason is usually because I am deep into writing chapters for a book and if the book’s chapters don’t translate into good blog articles, then the blog itself doesn’t get a lot of new content.
Anyway, as you may know, I am currently working on a book called Jupyter Notebook 101 which I am currently planning to release in November. I have 7 of the planned 11 chapters finished, although I plan to go over the entire book and check it for errors once it’s done. I am hoping to get the other chapters done early so I can write a few bonus chapters too, but we will see how the writing goes. On the plus side, these latter chapters will make good blog fodder, so you can expect to see some interesting articles on the Jupyter Notebook appearing on this blog in the near future.
If you’re interested in checking out the book, you can download a sample from Leanpub.
Learn the basics of Python’s built-in XML modules, minidom and ElementTree. You can read the chapter this is based on here: http://python101.pythonlibrary.org/chapter23_xml.html or get the book from Leanpub: https://leanpub.com/python_101
It’s the start of a new school year, so I am running a new sale this Fall. Feel free to check out my current sales:
- ReportLab: PDF Processing in Python
- Python 201: Intermediate Python
- Python 101
- Jupyter Noteboook 101 (Pre-order / Early Access) – Est. delivery November 2018
These sales will last until Sept. 1st. All my eBooks are available as PDF, mobi (Kindle) and epub format.
I recently released a new book entitled ReportLab: PDF Processing with Python. In celebration of a successful launch, I have decided to do a little contest.
- Post a comment telling me why you would want a copy
- The most clever or heartfelt commenter will be chosen by me
The contest will run starting now until Friday, August 17th @ 11:59 p.m. CST.
Runners up will receive a free copy of the eBook. The grand prize will be a signed paperback copy + the eBook version!