A PyQT GUI application for converting InfoLease report outputs into Excel files. Handles parsing and summarizing. Learns where files are meant to be store and compiles monthly and yearly summaries.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
InfoLeaseExtract/venv/Lib/site-packages/pandas/_libs/algos_common_helper.pxi.in

72 lines
2.1 KiB

"""
Template for each `dtype` helper function using 1-d template
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
# ----------------------------------------------------------------------
# ensure_dtype
# ----------------------------------------------------------------------
def ensure_platform_int(object arr):
# GH3033, GH1392
# platform int is the size of the int pointer, e.g. np.intp
if util.is_array(arr):
if (<ndarray>arr).descr.type_num == cnp.NPY_INTP:
return arr
else:
# equiv: arr.astype(np.intp)
return cnp.PyArray_Cast(<ndarray>arr, cnp.NPY_INTP)
else:
return np.array(arr, dtype=np.intp)
def ensure_object(object arr):
if util.is_array(arr):
if (<ndarray>arr).descr.type_num == NPY_OBJECT:
return arr
else:
# equiv: arr.astype(object)
return cnp.PyArray_Cast(<ndarray>arr, NPY_OBJECT)
else:
return np.array(arr, dtype=np.object_)
{{py:
# name, c_type, dtype
dtypes = [('float64', 'FLOAT64', 'float64'),
# ('float32', 'FLOAT32', 'float32'), # disabling bc unused
('int8', 'INT8', 'int8'),
('int16', 'INT16', 'int16'),
('int32', 'INT32', 'int32'),
('int64', 'INT64', 'int64'),
# Disabling uint and complex dtypes because we do not use them
# (and compiling them increases wheel size)
# ('uint8', 'UINT8', 'uint8'),
# ('uint16', 'UINT16', 'uint16'),
# ('uint32', 'UINT32', 'uint32'),
# ('uint64', 'UINT64', 'uint64'),
# ('complex64', 'COMPLEX64', 'complex64'),
# ('complex128', 'COMPLEX128', 'complex128')
]
def get_dispatch(dtypes):
for name, c_type, dtype in dtypes:
yield name, c_type, dtype
}}
{{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}}:
return arr
else:
return arr.astype(np.{{dtype}}, copy=copy)
else:
return np.array(arr, dtype=np.{{dtype}})
{{endfor}}