在swig/python目录里有一个readme，你参考着做一次编译就可以成生。
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#!/usr/bin/env python
import crfsuite
import sys
# Inherit crfsuite.Trainer to implement message() function, which receives
# progress messages from a training process.
class Trainer(crfsuite.Trainer):
def message(self, s):
# Simply output the progress messages to STDOUT.
sys.stdout.write(s)
def instances(fi):
xseq = crfsuite.ItemSequence()
yseq = crfsuite.StringList()
for line in fi:
line = line.strip(‘\n’)
if not line:
# An empty line presents an end of a sequence.
yield xseq, tuple(yseq)
xseq = crfsuite.ItemSequence()
yseq = crfsuite.StringList()
continue
# Split the line with TAB characters.
fields = line.split(‘\t’)
# Append attributes to the item.
item = crfsuite.Item()
for field in fields[1:]:
p = field.rfind(‘:’)
if p == -1:
# Unweighted (weight=1) attribute.
item.append(crfsuite.Attribute(field))
else:
# Weighted attribute
item.append(crfsuite.Attribute(field[:p], float(field[p+1:])))
# Append the item to the item sequence.
xseq.append(item)
# Append the label to the label sequence.
yseq.append(fields[0])
if __name__ == ‘__main__’:
# This demonstrates how to obtain the version string of CRFsuite.
print crfsuite.version()
# Create a Trainer object.
trainer = Trainer()
# Read training instances from STDIN, and set them to trainer.
for xseq, yseq in instances(sys.stdin):
trainer.append(xseq, yseq, 0)
# Use L2-regularized SGD and 1st-order dyad features.
trainer.select(‘l2sgd’, ‘crf1d’)
# This demonstrates how to list parameters and obtain their values.
for name in trainer.params():
print name, trainer.get(name), trainer.help(name)
# Set the coefficient for L2 regularization to 0.1
trainer.set(‘c2’, ‘0.1’)
# Start training; the training process will invoke trainer.message()
# to report the progress.
trainer.train(sys.argv[1], -1)
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