Analyze and manipulate your Anki collection using pandas!
Anki is one of the most popular flashcard system for spaced repetition learning, pandas is the most popular python package for data analysis and manipulation. So what could be better than to bring both together?
AnkiPandas you can use
pandas to easily analyze or manipulate
your Anki flashcards.
Manipulate & adding notes and cards: Apply fast bulk operations to the table (e.g. add tags, change decks, set field contents, suspend cards, ...) or iterate over the table and perform these manipulations step by step. This is still in alpha/beta! Proceed with care and please report bugs! (but ankipandas will always create a backup of your database before changing something).
Import and Export: Pandas can export to (and import from) csv, MS Excel, HTML, JSON, ... (io documentation)
Easy installation: Install via python package manager (independent of your Anki installation)
Simple: Just one line of code to get started
Fully documented: Documentation on readthedocs
Well tested: More than 100 unit tests to keep everything in check
Alternatives: If your main goal is to add new cards, models and more, you can also take a look at the genanki project.
pip3 install --user --upgrade ankipandas
For the latest development version you can also work from a cloned version of this repository:
git clone https://github.com/klieret/ankipandas/ cd ankipandas pip3 install --user --upgrade --editable .
pre-commit install gitmoji -i
🔥 Let’s get started!#
Starting up is as easy as this:
from ankipandas import Collection col = Collection()
col.notes will be dataframe containing all notes, with additional
methods that make many things easy. Similarly, you can access cards or
If called without any argument
Collection() tries to find your Anki
database by itself. However this might take some time. To make it
easier, simply supply (part of) the path to the database and (if you
have more than one user) your Anki user name, e.g.
Collection(".local/share/Anki2/", user="User 1") on many Linux
To get information about the interpretation of each column, use
Take a look at the documentation to find out more about more about the available methods!
Some basic examples:
Show a histogram of the number of reviews (repetitions) of each card for all decks:
Show the number of leeches per deck as pie chart:
cards = col.cards.merge_notes() selection = cards[cards.has_tag("leech")] selection["cdeck"].value_counts().plot.pie()
Find all notes of model
MnemoticModel with empty
notes = col.notes.fields_as_columns() notes.query("model=='MnemoticModel' and 'Mnemotic'==''")
Please be careful and test this well! Ankipandas will create a backup of your database before writing, so you can always restore the previous state. Please make sure that everything is working before continuing to use Anki normally!
marked tag to all notes that contain
notes = col.notes selection = notes[notes.has_tags(["Japanese", "leech"])] selection = selection.add_tag(["difficult-japanese", "marked"]) col.notes.update(selection) col.write(modify=True) # Overwrites your database after creating a backup!
language field to
English for all notes of model
LanguageModel that are tagged with
notes = col.notes selection = notes[notes.has_tag(["English"])].query("model=='LanguageModel'").copy() selection.fields_as_columns(inplace=True) selection["language"] = "English" col.notes.update(selection) col.write(modify=True)
Move all cards tagged
leech to the deck
cards = col.cards selection = cards[cards.has_tag("leech")] selection["cdeck"] = "Leeches Only" col.cards.update(selection) col.write(modify=True)
Your help is greatly appreciated! Suggestions, bug reports and feature requests are best opened as github issues. You could also first discuss in the gitter community. If you want to code something yourself, you are very welcome to submit a pull request!
Bug reports and pull requests are credited with the help of the allcontributors bot.
📃 License & Disclaimer#
This software is licenced under the MIT license and (despite best testing efforts) comes without any warranty. The logo is inspired by the Anki logo (license) and the logo of the pandas package (license2). This library and its author(s) are not affiliated/associated with the main Anki or pandas project in any way.
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!