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Jupyter Notebook Utility
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LICENSE.txt
MANIFEST
README.md
demo.tar
nbscan.py
setup.py

README.md

nbscan

nbscan.py is a Python script that will search for and print contents of cells in Jupyter notebooks. The script was written to search through notebooks managed by the nbgrader pipline (http://nbgrader.readthedocs.io) but will work for any Jupyter notebooks.

Cells can be filtered by type (code or markdown), by nbgrader tag ID, or by those that match a regular expression.
Specify files to scan by name or recursively search a directory to find notebooks.

Installation

pip3 install git+https://github.com/conery/nbscan.git

Usage

nbscan.py FILES [--dir D] [--submitted X] [--code | --markdown | --id X] [options]

FILES can be a list of 0 or more notebook file names; if names are given each file is scanned to find cells that match search critera.

If a directory is specified with --dir then that directory is recursively searched for notebooks (files with names ending in .ipynb) and those notebooks are added to the list of files to scan. --dir can be used more than once to search several directories.

The --submitted option is like --dir, except it searches below the submitted folder. Assuming the default project organization (submitted/student/project) specifying --submitted X can be used to search for all notebooks submitted for project X, across all students.

Use --code or --markdown to scan only code cells or markdown cells, or --id X to scan only cells that have X as their nbgrader ID. These three options are mutually exclusive.

Other options are:

  • --grep P will print only cells the match the pattern P; the pattern can be specified using regular expression syntax
  • --prompt is the same as --grep, but prompts the user to enter the pattern (avoiding messy shell escapes)
  • --tags asks the program to print the names of all the nbgrader IDs in notebooks
  • --random N prints cells from N notebooks selected at random instead of all the notebooks
  • --plain suppresses coloring of the parts of cells that match patterns
  • --nbformat N specifies an IPython notebook version (the default is 4)

Examples

These examples assume the script is being run in the top level directory of a course managed by nbgrader, i.e. there are subdirectories named source, release, submitted, etc.

Print the contents of all the code cells in hello.ipynb in the source folder:

$ nbscan.py source/hello/hello.ipynb --code

Print the markdown cells in hello.ipyb and oop.ipynb that contain the string "color:red" somewhere in the cell:

$ nbscan.py source/hello/hello.ipynb source/oop/oop.ipynb --markdown --grep color:red

If --tags is specified the script prints nbgrader cell IDs instead of cell contents.
This command prints the nbgrader cell IDs in all cells in all notebooks in the source folder:

$ nbscan.py --dir source --tags

Print the cell with nbgrader id hello in any notebooks submitted by students named 'harry' or 'hermione':

$ nbscan.py --dir submitted/harry --dir submitted/hermione --id hello

Print the level 1 or level 2 headers in all notebooks in the source folder:

$ nbscan.py --dir source --markdown --grep ^#\{1,2\}\\s

As above, but enter search pattern interactively, without shell quote characters; simply enter ^#{1,2}\s when prompted:

$ nbscan.py --dir source --markdown --prompt

Search all notebooks submitted for the hello project for code cells containing definitions of the hello function:

$ nbscan.py --submitted hello --code --grep 'def hello'

Print the contents of cells tagged hello_doc in the hello projects submitted by 3 random students:

$ nbscan.py --submitted hello --id hello_doc --random 3

Demo Project

The file named demo.tar contains a course folder that can be used to test the script using the commands in the examples above. The archive will expand into a course folder named demo, complete with a course database (demo.db) and source, release, submitted, autograded, and feedback folders. There are two projects, named hello and oop, and five students, with submitted notebooks for each student.

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