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A library for topic modeling and visualization

DARIAH Topics is an easy-to-use Python library for topic modeling and visualization. Getting started is really easy. All you have to do is import the library – you can train a model straightaway from raw textfiles.

It supports two implementations of latent Dirichlet allocation:

  • The lightweight, Cython-based package lda
  • The more robust, Java-based package MALLET


$ pip install dariah


>>> import dariah
>>> model, vis = dariah.topics(directory="british-fiction-corpus",
...                            stopwords=100,
...                            num_topics=10,
...                            num_iterations=1000)
>>> model.topics.iloc[:5, :5]
          word0   word1    word2    word3     word4
topic0  phineas    lord    laura   course     house
topic1    don't  mother     came       go    looked
topic2    jones   adams       am   indeed  answered
topic3      tom    adam   maggie     it's  tulliver
topic4  crawley  george  osborne  rebecca    amelia

With the vis object, you can visualize the model’s probability distributions, e.g. with vis.topic_document():


Poetry automatically creates a virtual environment, builds and publishes the project to PyPI. Install dependencies with:

$ poetry install

run tests:

$ poetry run pytest

format code:

$ poetry run black dariah

build the project:

$ poetry build

and publish it on PyPI:

$ poetry publish


DARIAH-DE supports research in the humanities and cultural sciences with digital methods and procedures. The research infrastructure of DARIAH-DE consists of four pillars: teaching, research, research data and technical components. As a partner in DARIAH-EU, DARIAH-DE helps to bundle and network state-of-the-art activities of the digital humanities. Scientists use DARIAH, for example, to make research data available across Europe. The exchange of knowledge and expertise is thus promoted across disciplines and the possibility of discovering new scientific discourses is encouraged.

This software library has been developed with support from the DARIAH-DE initiative, the German branch of DARIAH-EU, the European Digital Research Infrastructure for the Arts and Humanities consortium. Funding has been provided by the German Federal Ministry for Research and Education (BMBF) under the identifier 01UG1610J.


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  • Python 100.0%