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corpora.malletcorpus – Corpus in Mallet format of List-Of-Words.

corpora.malletcorpus – Corpus in Mallet format of List-Of-Words.

Corpus in Mallet format of List-Of-Words.

class gensim.corpora.malletcorpus.MalletCorpus(fname, id2word=None, metadata=False)

Bases: gensim.corpora.lowcorpus.LowCorpus


One file, one instance per line Assume the data is in the following format:

[URL] [language] [text of the page…]

Or, more generally,
[document #1 id] [label] [text of the document…] [document #2 id] [label] [text of the document…] … [document #N id] [label] [text of the document…]

Note that language/label is not considered in Gensim.


Return the document stored at file position offset.

load(fname, mmap=None)

Load a previously saved object from file (also see save).

If the object was saved with large arrays stored separately, you can load these arrays via mmap (shared memory) using mmap=’r’. Default: don’t use mmap, load large arrays as normal objects.

If the file being loaded is compressed (either ‘.gz’ or ‘.bz2’), then mmap=None must be set. Load will raise an IOError if this condition is encountered.

save(*args, **kwargs)
static save_corpus(fname, corpus, id2word=None, metadata=False)

Save a corpus in the Mallet format.

The document id will be generated by enumerating the corpus. That is, it will range between 0 and number of documents in the corpus.

Since Mallet has a language field in the format, this defaults to the string ‘__unknown__’. If the language needs to be saved, post-processing will be required.

This function is automatically called by MalletCorpus.serialize; don’t call it directly, call serialize instead.

serialize(serializer, fname, corpus, id2word=None, index_fname=None, progress_cnt=None, labels=None, metadata=False)

Iterate through the document stream corpus, saving the documents to fname and recording byte offset of each document. Save the resulting index structure to file index_fname (or fname.index is not set).

This relies on the underlying corpus class serializer providing (in addition to standard iteration):

  • save_corpus method that returns a sequence of byte offsets, one for
    each saved document,
  • the docbyoffset(offset) method, which returns a document positioned at offset bytes within the persistent storage (file).
  • metadata if set to true will ensure that serialize will write out article titles to a pickle file.


>>> MmCorpus.serialize('', corpus)
>>> mm = MmCorpus('') # `mm` document stream now has random access
>>> print(mm[42]) # retrieve document no. 42, etc.