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January 11, 2018 08:41
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We have 3 main algorithms in our sourced.ml (https://github.com/src-d/ml). One can find a description in the README. Now algorithms don't use our new cool engine (https://github.com/src-d/engine). We need to understand how we can rearchitect our tool. At first, let's see how we can reproduce them.
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import re | |
import Stemmer | |
class TokenParser: | |
""" | |
Common utilities for splitting and stemming tokens. | |
""" | |
NAME_BREAKUP_RE = re.compile(r"[^a-zA-Z]+") #: Regexp to split source code identifiers. | |
STEM_THRESHOLD = 6 #: We do not stem splitted parts shorter than or equal to this size. | |
MAX_TOKEN_LENGTH = 256 #: We cut identifiers longer than thi value. | |
def __init__(self, stem_threshold=STEM_THRESHOLD, max_token_length=MAX_TOKEN_LENGTH): | |
self._stemmer = Stemmer.Stemmer("english") | |
self._stemmer.maxCacheSize = 0 | |
self._stem_threshold = stem_threshold | |
self._max_token_length = max_token_length | |
def __call__(self, token): | |
return self.process_token(token) | |
def process_token(self, token): | |
for word in self.split(token): | |
yield self.stem(word) | |
def stem(self, word): | |
if len(word) <= self._stem_threshold: | |
return word | |
return self._stemmer.stemWord(word) | |
def split(self, token): | |
token = token.strip()[:self._max_token_length] | |
prev_p = [""] | |
def ret(name): | |
r = name.lower() | |
if len(name) >= 3: | |
yield r | |
if prev_p[0]: | |
yield prev_p[0] + r | |
prev_p[0] = "" | |
else: | |
prev_p[0] = r | |
for part in self.NAME_BREAKUP_RE.split(token): | |
if not part: | |
continue | |
prev = part[0] | |
pos = 0 | |
for i in range(1, len(part)): | |
this = part[i] | |
if prev.islower() and this.isupper(): | |
yield from ret(part[pos:i]) | |
pos = i | |
elif prev.isupper() and this.islower(): | |
if 0 < i - 1 - pos <= 3: | |
yield from ret(part[pos:i - 1]) | |
pos = i - 1 | |
elif i - 1 > pos: | |
yield from ret(part[pos:i]) | |
pos = i | |
prev = this | |
last = part[pos:] | |
if last: | |
yield from ret(last) | |
def __getstate__(self): | |
state = self.__dict__.copy() | |
del state["_stemmer"] | |
return state | |
def __setstate__(self, state): | |
self.__dict__ = state | |
self._stemmer = Stemmer.Stemmer("english") | |
class NoTokenParser: | |
""" | |
One can use this class if he or she does not want to do any parsing. | |
""" | |
def process_token(self, token): | |
return [token] |
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s/soursed/sourced on the title @zurk