topik.simple_run package


topik.simple_run.cli module module, source_type='auto', year_field=None, start_year=None, stop_year=None, content_field=None, tokenizer='simple', vectorizer='bag_of_words', ntopics=10, dir_path='./topic_model', model='lda', termite_plot=False, output_file=False, lda_vis=True, seed=42, **kwargs)[source]

Run your data through all topik functionality and save all results to a specified directory.


data_source : str

Input data (e.g. file or folder or solr/elasticsearch instance).

source_type : {‘json_stream’, ‘folder_files’, ‘json_large’, ‘solr’, ‘elastic’}.

The format of your data input. Currently available a json stream or a folder containing text files. Default is ‘json_stream’

year_field : str

The field name (if any) that contains the year associated with each document (for filtering).

start_year : int

For beginning of range filter on year_field values

stop_year : int

For beginning of range filter on year_field values

content_field : string

The primary text field to parse.

tokenizer : {‘simple’, ‘collocations’, ‘entities’, ‘mixed’}

The type of tokenizer to use. Default is ‘simple’.

vectorizer : {‘bag_of_words’, ‘tfidf’}

The type of vectorizer to use. Default is ‘bag_of_words’.

ntopics : int

Number of topics to find in your data

dir_path : str

Directory path to store all topic modeling results files. Default is ./topic_model.

model : {‘LDA’, ‘PLSA’}.

Statistical modeling algorithm to use. Default ‘LDA’.

termite_plot : bool

Generate termite plot of your model if True. Default is True.

ldavis : bool

Generate an interactive data visualization of your topics. Default is False.

seed : int

Set random number generator to seed, to be able to reproduce results. Default 42.

**kwargs : additional keyword arguments, passed through to each individual step

Module contents