Merge pull request #138 from michelole/cleanup

Cleanup

.travis.yml

@@ -7,7 +7,6 @@ matrix:
     - python: "3.8"
 before_install:
   - export BOTO_CONFIG=/dev/null  # See https://github.com/travis-ci/travis-ci/issues/7940
-  - export BING_SEARCH_API_KEY=${BING_SEARCH_API_KEY:=secret} # Fallback to 'secret' to avoid empty value
   - export PYTHONHASHSEED=500  # Make word2vec deterministic
 script:
   - pylint -E acres && py.test --cov=acres

acres/evaluation/__init__.py

@@ -1,6 +1,6 @@
 """
 Package containing evaluation modules.
 """
-from acres.evaluation import corpus, evaluation, metrics
+from acres.evaluation import evaluation, metrics
 
-__all__ = ['corpus', 'evaluation', 'metrics']
+__all__ = ['evaluation', 'metrics']

acres/evaluation/evaluation.py

@@ -9,7 +9,6 @@
 from itertools import islice
 from typing import Dict, Tuple, List, Set
 
-import acres.util.acronym
 from acres.evaluation import metrics
 from acres.model import expansion_standard, detection_standard, topic_list
 from acres.resolution import resolver
@@ -52,7 +51,7 @@ def test_input(true_expansions: Set[str], possible_expansions: List[str],
     return False
 
 
-def analyze(contextualized_acronym: acres.util.acronym.Acronym, true_expansions: Set[str],
+def analyze(contextualized_acronym: Acronym, true_expansions: Set[str],
             strategy: resolver.Strategy, max_tries: int) -> Dict[str, bool]:
     """
     Analyze a given row of the gold standard.
@@ -75,7 +74,7 @@ def analyze(contextualized_acronym: acres.util.acronym.Acronym, true_expansions:
 
     # Remove context to improve cache hit
     # XXX We currently support context only for n-grams
-    if strategy not in [resolver.Strategy.NGRAM, resolver.Strategy.FASTNGRAM]:
+    if strategy != resolver.Strategy.FASTNGRAM:
         left_context = ""
         right_context = ""
 

acres/fastngram/fastngram.py

@@ -7,11 +7,10 @@
 from collections import OrderedDict
 from typing import Dict, Set, Tuple, Iterator, List, Union
 
-import acres.util.acronym
-from acres.model import topic_list
 from acres.preprocess import resource_factory
 from acres.util import functions
 from acres.util.functions import import_conf
+from acres.util.acronym import Acronym
 
 logger = logging.getLogger(__name__)
 
@@ -118,7 +117,7 @@ def fastngram(acronym: str, left_context: str = "", right_context: str = "",
     :param max_rank:
     :return:
     """
-    contextualized_acronym = acres.util.acronym.Acronym(acronym=acronym, left_context=left_context,
+    contextualized_acronym = Acronym(acronym=acronym, left_context=left_context,
                                                         right_context=right_context)
     contexts = _generate_acronym_contexts(contextualized_acronym)
 
@@ -145,7 +144,7 @@ def fasttype(acronym: str, left_context: str = "", right_context: str = "",
         yield ngram
 
 
-def _find_contexts(acronym: str, min_freq: int) -> 'List[topic_list.Acronym]':
+def _find_contexts(acronym: str, min_freq: int) -> 'List[Acronym]':
     """
     Find contexts in the training data where this acronym appears.
 
@@ -155,22 +154,22 @@ def _find_contexts(acronym: str, min_freq: int) -> 'List[topic_list.Acronym]':
     """
     model = resource_factory.get_center_map(functions.partition(acronym, PARTITIONS))
 
-    all_contexts = []  # type: List[topic_list.Acronym]
+    all_contexts = []  # type: List[Acronym]
     for out_freq, contexts in model.contexts(acronym).items():
         for left, right in contexts:
             # Do not allow empty contexts.
             if left == '' and right == '':
                 continue
             if out_freq < min_freq:
                 break
-            contextualized_acronym = acres.util.acronym.Acronym(acronym=acronym, left_context=left,
+            contextualized_acronym = Acronym(acronym=acronym, left_context=left,
                                                                 right_context=right)
             all_contexts.append(contextualized_acronym)
 
     return all_contexts
 
 
-def _center_provider(contexts: 'List[topic_list.Acronym]', min_freq: int,
+def _center_provider(contexts: 'List[Acronym]', min_freq: int,
                      max_rank: int) -> Iterator[str]:
     """
     Provide unlimited center words for a given list of contexts.
@@ -227,7 +226,7 @@ def create_map(ngrams: Dict[str, int], model: Union[ContextMap, CenterMap],
     return model
 
 
-def _generate_ngram_contexts(ngram: str) -> 'List[topic_list.Acronym]':
+def _generate_ngram_contexts(ngram: str) -> 'List[Acronym]':
     """
     Generate a list of contextualized n-grams with a decreasing central n-gram and increasing \
     lateral context.
@@ -252,12 +251,12 @@ def _generate_ngram_contexts(ngram: str) -> 'List[topic_list.Acronym]':
             left = sys.intern(" ".join(tokens[0:i]))
             right = sys.intern(" ".join(tokens[j:ngram_size]))
             center = sys.intern(" ".join(tokens[i:j]))
-            contexts.append(acres.util.acronym.Acronym(acronym=center, left_context=left,
+            contexts.append(Acronym(acronym=center, left_context=left,
                                                        right_context=right))
     return contexts
 
 
-def _generate_acronym_contexts(contextualized_acronym: 'topic_list.Acronym') -> 'List[topic_list.Acronym]':
+def _generate_acronym_contexts(contextualized_acronym: 'Acronym') -> 'List[Acronym]':
     """
     Generate a list of contextualized acronyms with decreasing lateral context.
 
@@ -279,7 +278,7 @@ def _generate_acronym_contexts(contextualized_acronym: 'topic_list.Acronym') ->
     if right_length > left_length:
         max_length += min(MAX_DIFF, right_length - left_length)
 
-    contexts = []  # type: List[topic_list.Acronym]
+    contexts = []  # type: List[Acronym]
     for j in range(max_length, -1, -1):
         # Left size > right size
         if j > right_length:
@@ -293,7 +292,7 @@ def _generate_acronym_contexts(contextualized_acronym: 'topic_list.Acronym') ->
                 continue
             left_context = " ".join(left[i:left_length])
             right_context = " ".join(right[0:j])
-            contexts.append(acres.util.acronym.Acronym(acronym=contextualized_acronym.acronym,
+            contexts.append(Acronym(acronym=contextualized_acronym.acronym,
                                                        left_context=left_context,
                                                        right_context=right_context))
     return contexts

acres/model/detection_standard.py

@@ -11,6 +11,7 @@
 
 from acres.model import topic_list
 from acres.util import acronym as acro_util
+from acres.util.acronym import Acronym
 
 logger = logging.getLogger(__name__)
 
@@ -77,7 +78,7 @@ def parse_valid(filename: str) -> Set[str]:
     return filter_valid(parse(filename))
 
 
-def update(previous: Dict[str, bool], acronyms: List[acro_util.Acronym]) -> Dict[str, bool]:
+def update(previous: Dict[str, bool], acronyms: List[Acronym]) -> Dict[str, bool]:
     """
     Update a previous detection standard with new acronyms from a topic list, preserving order.
 

acres/ngram/ngrams.py → acres/model/ngrams.py

@@ -18,7 +18,6 @@ class FilteredNGramStat:
 
     @todo ngramstat itself should be a generator
     """
-    NGRAM_SEPARATOR = "\t"
     TOKEN_SEPARATOR = " "
     PRINT_INTERVAL = 1000000
 

acres/model/topic_list.py

@@ -7,7 +7,7 @@
 from operator import attrgetter
 from typing import List, Set
 
-from acres.ngram import ngrams
+from acres.model import ngrams
 from acres.util import acronym as acro_util
 from acres.util import functions