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corpora.bleicorpus – Corpus in Blei’s LDA-C format

corpora.bleicorpus – Corpus in Blei’s LDA-C format

Blei’s LDA-C format.

class gensim.corpora.bleicorpus.BleiCorpus(fname, fname_vocab=None)

Bases: gensim.corpora.indexedcorpus.IndexedCorpus

Corpus in Blei’s LDA-C format.

The corpus is represented as two files: one describing the documents, and another describing the mapping between words and their ids.

Each document is one line:

N fieldId1:fieldValue1 fieldId2:fieldValue2 ... fieldIdN:fieldValueN

The vocabulary is a file with words, one word per line; word at line K has an implicit id=K.

Initialize the corpus from a file.

fname_vocab is the file with vocabulary; if not specified, it defaults to fname.vocab.


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 LDA-C format.

There are actually two files saved: fname and fname.vocab, where fname.vocab is the vocabulary file.

This function is automatically called by BleiCorpus.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.