CLN: Replace comprehensions list/set/dict functions with corresponding symbols

Author: mroeschke

asv_bench/benchmarks/frame_ctor.py

@@ -23,9 +23,9 @@ def setup(self):
         self.some_dict = list(self.data.values())[0]
         self.dict_list = [dict(zip(self.columns, row)) for row in self.frame.values]
 
-        self.data2 = dict(
-            ((i, dict(((j, float(j)) for j in range(100)))) for i in
-             range(2000)))
+        self.data2 = {i: {j: float(j) for j in range(100)}
+                      for i in range(2000)}
+
 
     def time_frame_ctor_list_of_dict(self):
         DataFrame(self.dict_list)

asv_bench/benchmarks/packers.py

@@ -17,7 +17,7 @@ def _setup(self):
         self.N = 100000
         self.C = 5
         self.index = date_range('20000101', periods=self.N, freq='H')
-        self.df = DataFrame(dict(('float{0}'.format(i), randn(self.N)) for i in range(self.C)), index=self.index)
+        self.df = DataFrame({'float{0}'.format(i): randn(self.N) for i in range(self.C)}, index=self.index)
         self.df2 = self.df.copy()
         self.df2['object'] = [('%08x' % randrange((16 ** 8))) for _ in range(self.N)]
         self.remove(self.f)

asv_bench/benchmarks/replace.py

@@ -23,7 +23,7 @@ class replace_large_dict(object):
     def setup(self):
         self.n = (10 ** 6)
         self.start_value = (10 ** 5)
-        self.to_rep = dict(((i, (self.start_value + i)) for i in range(self.n)))
+        self.to_rep = {i: self.start_value + i for i in range(self.n)}
         self.s = Series(np.random.randint(self.n, size=(10 ** 3)))
 
     def time_replace_large_dict(self):
@@ -35,8 +35,8 @@ class replace_convert(object):
 
     def setup(self):
         self.n = (10 ** 3)
-        self.to_ts = dict(((i, pd.Timestamp(i)) for i in range(self.n)))
-        self.to_td = dict(((i, pd.Timedelta(i)) for i in range(self.n)))
+        self.to_ts = {i: pd.Timestamp(i) for i in range(self.n)}
+        self.to_td = {i: pd.Timedelta(i) for i in range(self.n)}
         self.s = Series(np.random.randint(self.n, size=(10 ** 3)))
         self.df = DataFrame({'A': np.random.randint(self.n, size=(10 ** 3)),
                              'B': np.random.randint(self.n, size=(10 ** 3))})

ci/lint.sh

@@ -97,6 +97,19 @@ if [ "$LINT" ]; then
     fi
     echo "Check for use of lists instead of generators in built-in Python functions DONE"
 
+    echo "Check for use of comprehensions using set(), dict() or list()"
+
+    # Example: Avoid `list(i for i in some_iterator)` in favor of `[i for i in some_iterator]`
+    #
+    # Check the following functions:
+    # list(), set(), dict()
+    grep -R --include="*.py*" -E "(list|dict|[^frozen]set)\([^\{)=]* for .* in [^}]*\)"
+
+    if [ $? = "0" ]; then
+        RET=1
+    fi
+    echo "Check for use of comprehensions using set(), dict() or list() DONE"
+
 else
     echo "NOT Linting"
 fi

doc/sphinxext/numpydoc/phantom_import.py

@@ -60,8 +60,8 @@ def import_phantom_module(xml_file):
     # Sort items so that
     # - Base classes come before classes inherited from them
     # - Modules come before their contents
-    all_nodes = dict((n.attrib['id'], n) for n in root)
-    
+    all_nodes = {n.attrib['id']: n for n in root}
+
     def _get_bases(node, recurse=False):
         bases = [x.attrib['ref'] for x in node.findall('base')]
         if recurse:

pandas/_libs/parsers.pyx

@@ -2227,7 +2227,7 @@ def _concatenate_chunks(list chunks):
     for name in names:
         arrs = [chunk.pop(name) for chunk in chunks]
         # Check each arr for consistent types.
-        dtypes = set(a.dtype for a in arrs)
+        dtypes = {a.dtype for a in arrs}
         if len(dtypes) > 1:
             common_type = np.find_common_type(dtypes, [])
             if common_type == np.object:

pandas/_libs/tslibs/offsets.pyx

@@ -33,7 +33,7 @@ from np_datetime cimport (pandas_datetimestruct,
 _MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
            'AUG', 'SEP', 'OCT', 'NOV', 'DEC']
 _int_to_month = {(k + 1): v for k, v in enumerate(_MONTHS)}
-_month_to_int = dict((v, k) for k, v in _int_to_month.items())
+_month_to_int = {v: k for k, v in _int_to_month.items()}
 
 
 class WeekDay(object):

pandas/_libs/tslibs/resolution.pyx

@@ -53,7 +53,7 @@ _ONE_HOUR = 60 * _ONE_MINUTE
 _ONE_DAY = 24 * _ONE_HOUR
 
 DAYS = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
-_weekday_rule_aliases = dict((k, v) for k, v in enumerate(DAYS))
+_weekday_rule_aliases = {k: v for k, v in enumerate(DAYS)}
 
 _MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
            'AUG', 'SEP', 'OCT', 'NOV', 'DEC']

pandas/_version.py

@@ -141,11 +141,11 @@ def git_versions_from_keywords(keywords, tag_prefix, verbose):
         if verbose:
             print("keywords are unexpanded, not using")
         raise NotThisMethod("unexpanded keywords, not a git-archive tarball")
-    refs = set(r.strip() for r in refnames.strip("()").split(","))
+    refs = {r.strip() for r in refnames.strip("()").split(",")}
     # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of
     # just "foo-1.0". If we see a "tag: " prefix, prefer those.
     TAG = "tag: "
-    tags = set(r[len(TAG):] for r in refs if r.startswith(TAG))
+    tags = {r[len(TAG):] for r in refs if r.startswith(TAG)}
     if not tags:
         # Either we're using git < 1.8.3, or there really are no tags. We use
         # a heuristic: assume all version tags have a digit. The old git %d
@@ -154,7 +154,7 @@ def git_versions_from_keywords(keywords, tag_prefix, verbose):
         # between branches and tags. By ignoring refnames without digits, we
         # filter out many common branch names like "release" and
         # "stabilization", as well as "HEAD" and "master".
-        tags = set(r for r in refs if re.search(r'\d', r))
+        tags = {r for r in refs if re.search(r'\d', r)}
         if verbose:
             print("discarding '{}', no digits".format(",".join(refs - tags)))
     if verbose:

pandas/core/common.py

@@ -347,7 +347,7 @@ def map_indices_py(arr):
     Returns a dictionary with (element, index) pairs for each element in the
     given array/list
     """
-    return dict((x, i) for i, x in enumerate(arr))
+    return {x: i for i, x in enumerate(arr)}
 
 
 def union(*seqs):