python-zpar 0.9.5

Description:

pythonzpar 0.9.5

Introduction
python-zpar is a python wrapper around the ZPar
parser.
ZPar was written by Yue Zhang
while he was at Oxford University. According to its home page: ZPar is
a statistical natural language parser, which performs syntactic analysis
tasks including word segmentation, part-of-speech tagging and parsing.
ZPar supports multiple languages and multiple grammar formalisms. ZPar
has been most heavily developed for Chinese and English, while it
provides generic support for other languages. ZPar is fast, processing
above 50 sentences per second using the standard Penn Teebank (Wall
Street Journal) data.
I wrote python-zpar since I needed a fast and efficient parser for my
NLP work which is primarily done in Python and not C++. I wanted to be
able to use this parser directly from Python without having to create a
bunch of files and running them through subprocesses. python-zpar not
only provides a simply python wrapper but also provides an XML-RPC ZPar
server to make batch-processing of large files easier.
python-zpar uses
ctypes, a very
cool foreign function library bundled with Python that allows calling
functions in C DLLs or shared libraries directly.


Installation
Currently, python-zpar only works on 64-bit linux and OS X systems.
Those are the two platforms I use everyday. I am happy to try to get
python-zpar working on other platforms over time. Pull requests are
welcome!
In order for python-zpar to work, it requires C functions that can be
called directly. Since the only user-exposed entry point in ZPar is the
command line client, I needed to write a shared library that would have
functions built on top of the ZPar functionality but expose them in a
way that ctypes could understand.
Therefore, in order to build python-zpar from scratch, we need to
download the ZPar source, patch it with new functionality and compile
the shared library. All of this happens automatically when you install
with pip:
pip install python-zpar
IMPORTANT: On OS X, the installation will only work with gcc
installed using either macports or
homebrew. The zpar source cannot be compiled with
clang. If you are having trouble compiling the code after cloning
the repository or installing the package using pip, you can try
to explicitly override the C++ compiler:
CXX=<path to c++ compiler> make -e
or
CXX=<path to c++ compiler> pip install python-zpar
If you are curious about what the C functions in the shared library
module look like, see src/zpar.lib.cpp.


Usage
To use python-zpar, you need the English models for ZPar. They can be
downloaded from the ZPar release page here.
There are three models: a part-of-speech tagger, a constituency parser, and a
dependency parser. For the purpose of the examples below, the models are
in the english-models directory in the current directory.
Here’s a small example of how to use python-zpar:
from six import print_
from zpar import ZPar

# use the zpar wrapper as a context manager
with ZPar('english-models') as z:

# get the parser and the dependency parser models
tagger = z.get_tagger()
depparser = z.get_depparser()

# tag a sentence
tagged_sent = tagger.tag_sentence("I am going to the market.")
print_(tagged_sent)

# tag an already tokenized sentence
tagged_sent = tagger.tag_sentence("Do n't you want to come with me to the market ?", tokenize=False)
print_(tagged_sent)

# get the dependency parse of an already tagged sentence
dep_parsed_sent = depparser.dep_parse_tagged_sentence("I/PRP am/VBP going/VBG to/TO the/DT market/NN ./.")
print_(dep_parsed_sent)

# get the dependency parse of an already tokenized sentence
dep_parsed_sent = depparser.dep_parse_sentence("Do n't you want to come with me to the market ?", tokenize=False)
print_(dep_parsed_sent)
The above code sample produces the following output:
I/PRP am/VBP going/VBG to/TO the/DT market/NN ./.

Do/VBP n't/RB you/PRP want/VBP to/TO come/VB with/IN me/PRP to/TO the/DT market/NN ?/.

I PRP 1 SUB
am VBP -1 ROOT
going VBG 1 VC
to TO 2 VMOD
the DT 5 NMOD
market NN 3 PMOD
. . 1 P

Do VBP -1 ROOT
n't RB 0 VMOD
you PRP 0 SUB
want VBP 0 VMOD
to TO 5 VMOD
come VB 3 VMOD
with IN 5 VMOD
me PRP 6 PMOD
to TO 5 VMOD
the DT 10 NMOD
market NN 8 PMOD
? . 0 P
Detailed usage with comments is shown in the included file
examples/zpar_example.py. Run python zpar_example.py -h to see a
list of all available options.


ZPar Server
The package also provides an python XML-RPC implementation of a ZPar
server that makes it easier to process multiple sentences and files by
loading the models just once (via the ctypes interface) and allowing
clients to connect and request analyses. The implementation is in the
executable zpar_server that is installed when you install the
package. The server is quite flexible and allows loading only the
models that you need. Here’s an example of how to start the server
with only the tagger and the dependency parser models loaded:
$> zpar_server --modeldir english-models --models tagger parser depparser
INFO:Initializing server ...
Loading tagger from english-models/tagger
Loading model... done.
Loading constituency parser from english-models/conparser
Loading scores... done. (65.9334s)
Loading dependency parser from english-models/depparser
Loading scores... done. (14.9623s)
INFO:Registering introspection ...
INFO:Starting server on port 8859...
Run zpar_server -h to see a list of all options.
Once the server is running, you can connect to it using a client. An
example client is included in the file examples/zpar_client.py which
can be run as follows (note that if you specified a custom host and port
when running the server, you’d need to specify the same here):
$> cd examples
$> python zpar_client.py

INFO:Attempting connection to http://localhost:8859
INFO:Tagging "Don't you want to come with me to the market?"
INFO:Output: Do/VBP n't/RB you/PRP want/VBP to/TO come/VB with/IN me/PRP to/TO the/DT market/NN ?/.
INFO:Tagging "Do n't you want to come to the market with me ?"
INFO:Output: Do/VBP n't/RB you/PRP want/VBP to/TO come/VB to/TO the/DT market/NN with/IN me/PRP ?/.
INFO:Parsing "Don't you want to come with me to the market?"
INFO:Output: (SQ (VBP Do) (RB n't) (NP (PRP you)) (VP (VBP want) (S (VP (TO to) (VP (VB come) (PP (IN with) (NP (PRP me))) (PP (TO to) (NP (DT the) (NN market))))))) (. ?))
INFO:Dep Parsing "Do n't you want to come to the market with me ?"
INFO:Output: Do VBP -1 ROOT
n't RB 0 VMOD
you PRP 0 SUB
want VBP 0 VMOD
to TO 5 VMOD
come VB 3 VMOD
to TO 5 VMOD
the DT 8 NMOD
market NN 6 PMOD
with IN 5 VMOD
me PRP 9 PMOD
? . 0 P

INFO:Tagging file /Users/nmadnani/work/python-zpar/examples/test.txt into test.tag
INFO:Parsing file /Users/nmadnani/work/python-zpar/examples/test_tokenized.txt into test.parse
Note that python-zpar and all of the example scripts should work with
both Python 2.7 and Python 3.4. I have tested python-zpar on both Linux
and Mac but not on Windows.


Node.js version
If you want to use ZPar in your node.js app, check out my other project
node-zpar.


License
Although python-zpar is licensed under the MIT license - which means
that you can do whatever you want with the wrapper code - ZPar itself is
licensed under GPL v3.


ToDo

Improve error handling on both the python and C side.
Expose more functionality, e.g., Chinese word segmentation, parsing
etc.
May be look into using CFFI
instead of ctypes.