From 32f58b19d149b2d97fe3ad5fbbee233ced293798 Mon Sep 17 00:00:00 2001 From: Matthew Honnibal Date: Sat, 24 Jan 2015 17:47:51 +1100 Subject: [PATCH] * Edits to quickstart --- docs/source/quickstart.rst | 29 +++++++++++------------------ 1 file changed, 11 insertions(+), 18 deletions(-) diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst index 4e750b6f5..a8c2fa0f3 100644 --- a/docs/source/quickstart.rst +++ b/docs/source/quickstart.rst @@ -12,9 +12,8 @@ Install $ pip install spacy $ python -m spacy.en.download -The download command fetches and installs the parser model and word representations, -which are too big to host on PyPi (about 100mb each). The data is installed within -the spacy.en package directory. +The download command fetches and installs about 200mb of data, which it installs +within the spacy.en package directory. Usage ----- @@ -37,18 +36,14 @@ e.g. `pizza.orth_` and `pizza.orth` provide the integer ID and the string of the original orthographic form of the word, with no string normalizations applied. - .. note:: - - en.English.__call__ is stateful --- it has an important **side-effect**: - spaCy maps strings to sequential integers, so when it processes a new - word, the mapping table is updated. + .. note:: en.English.__call__ is stateful --- it has an important **side-effect**. - Future releases will feature a way to reconcile :py:class:`strings.StringStore` - mappings, but for now, you should only work with one instance of the pipeline - at a time. - - This issue only affects rare words. spaCy's pre-compiled lexicon has 260,000 - words; the string IDs for these words will always be consistent. + When it processes a previously unseen word, it increments the ID counter, + assigns the ID to the string, and writes the mapping in + :py:data:`English.vocab.strings` (instance of + :py:class:`strings.StringStore`). + Future releases will feature a way to reconcile mappings, but for now, you + should only work with one instance of the pipeline at a time. (Most of the) API at a glance @@ -76,7 +71,7 @@ applied. **Get dict or numpy array:** - .. py:method:: tokens.Tokens.to_array(self, attr_ids: List[int]) --> numpy.ndarray[ndim=2, dtype=int32] + .. py:method:: tokens.Tokens.to_array(self, attr_ids: List[int]) --> ndarray[ndim=2, dtype=long] .. py:method:: tokens.Tokens.count_by(self, attr_id: int) --> Dict[int, int] @@ -93,7 +88,7 @@ applied. .. py:attribute:: lexeme.Lexeme.repvec -**Navigate dependency parse** +**Navigate to tree- or string-neighbor tokens** .. py:method:: nbor(self, i=1) --> Token @@ -115,8 +110,6 @@ applied. Length, in unicode code-points. Equal to len(self.orth_). - self.string[self.length:] gets whitespace. - .. py:attribute:: idx: int Starting offset of word in the original string.