fixing linting errors in pxi.in files (linting was broken)

Author: datapythonista

pandas/_libs/algos_common_helper.pxi.in

@@ -150,6 +150,7 @@ def get_dispatch(dtypes):
 
 {{for name, c_type, dtype in get_dispatch(dtypes)}}
 
+
 def ensure_{{name}}(object arr, copy=True):
     if util.is_array(arr):
         if (<ndarray> arr).descr.type_num == NPY_{{c_type}}:

pandas/_libs/groupby_helper.pxi.in

@@ -351,6 +351,7 @@ def group_last_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
                 else:
                     out[i, j] = resx[i, j]
 
+
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_nth_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
@@ -410,6 +411,8 @@ def group_nth_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
 
 
 {{if name != 'object'}}
+
+
 @cython.boundscheck(False)
 @cython.wraparound(False)
 def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,

pandas/_libs/hashtable_class_helper.pxi.in

@@ -466,12 +466,12 @@ cdef class {{name}}HashTable(HashTable):
     @cython.boundscheck(False)
     def unique(self, const {{dtype}}_t[:] values):
         cdef:
-           Py_ssize_t i, n = len(values)
-           int ret = 0
-           {{dtype}}_t val
-           khiter_t k
-           {{name}}Vector uniques = {{name}}Vector()
-           {{name}}VectorData *ud
+            Py_ssize_t i, n = len(values)
+            int ret = 0
+            {{dtype}}_t val
+            khiter_t k
+            {{name}}Vector uniques = {{name}}Vector()
+            {{name}}VectorData *ud
 
         ud = uniques.data
 

pandas/_libs/hashtable_func_helper.pxi.in

@@ -128,6 +128,7 @@ cpdef value_count_{{dtype}}({{scalar}}[:] values, bint dropna):
 @cython.boundscheck(False)
 {{if dtype == 'object'}}
 
+
 def duplicated_{{dtype}}(ndarray[{{dtype}}] values, object keep='first'):
 {{else}}
 
@@ -210,9 +211,11 @@ def duplicated_{{dtype}}({{scalar}}[:] values, object keep='first'):
 @cython.boundscheck(False)
 {{if dtype == 'object'}}
 
+
 def ismember_{{dtype}}(ndarray[{{scalar}}] arr, ndarray[{{scalar}}] values):
 {{else}}
 
+
 def ismember_{{dtype}}({{scalar}}[:] arr, {{scalar}}[:] values):
 {{endif}}
 
@@ -236,7 +239,6 @@ def ismember_{{dtype}}({{scalar}}[:] arr, {{scalar}}[:] values):
         {{scalar}} val
         kh_{{ttype}}_t * table = kh_init_{{ttype}}()
 
-
     # construct the table
     n = len(values)
     kh_resize_{{ttype}}(table, min(n, len(values)))

pandas/_libs/join_func_helper.pxi.in

@@ -25,7 +25,6 @@ on_dtypes = ['uint8_t', 'uint16_t', 'uint32_t', 'uint64_t',
 }}
 
 
-
 {{for table_type, by_dtype in by_dtypes}}
 {{for on_dtype in on_dtypes}}