def execute(self, *args):
# essential parameters check
valid = EssentialParameters(
self.__class__.__name__,
[self._src_dir, self._dest_dir, self._dest_pattern],
)
valid()
if self._dest_pattern:
self._logger.warning(
"'dest_pattern' will be unavailable in the near future."
+ "'dest_pattern' will change to 'dest_name'."
)
if not self._src_pattern and not self._src_filenames:
raise InvalidParameter(
"Specifying either 'src_pattern' or 'src_filenames' is essential."
)
if self._src_pattern and self._src_filenames:
raise InvalidParameter(
"Cannot specify both 'src_pattern' and 'src_filenames'."
)
if self._src_pattern:
files = File().get_target_files(self._src_dir, self._src_pattern)
else:
files = []
for file in self._src_filenames:
files.append(os.path.join(self._src_dir, file))
if len(files) == 0:
raise FileNotFound("No files are found.")
elif len(files) == 1:
self._logger.warning("Two or more input files are required.")
file = files.pop(0)
df1 = pandas.read_csv(
file,
dtype=str,
encoding=self._encoding,
)
for file in files:
df2 = pandas.read_csv(
file,
dtype=str,
encoding=self._encoding,
)
df1 = pandas.concat([df1, df2])
df1.to_csv(
os.path.join(self._dest_dir, self._dest_pattern),
encoding=self._encoding,
index=False,
)
def execute(self, *args):
# essential parameters check
valid = EssentialParameters(
self.__class__.__name__,
[self._src_dir, self._dest_dir, self._dest_pattern],
)
valid()
if not self._src_pattern and not self._src_filenames:
raise InvalidParameter(
"Specifying either 'src_pattern' or 'src_filenames' is essential."
)
if self._src_pattern and self._src_filenames:
raise InvalidParameter(
"Cannot specify both 'src_pattern' and 'src_filenames'.")
if self._src_pattern:
files = File().get_target_files(self._src_dir, self._src_pattern)
else:
files = []
for file in self._src_filenames:
files.append(os.path.join(self._src_dir, file))
if len(files) < 2:
raise InvalidCount("Two or more input files are required.")
file = files.pop(0)
df1 = pandas.read_csv(
file,
dtype=str,
encoding=self._encoding,
)
for file in files:
df2 = pandas.read_csv(
file,
dtype=str,
encoding=self._encoding,
)
df1 = pandas.concat([df1, df2])
df1.to_csv(
os.path.join(self._dest_dir, self._dest_pattern),
encoding=self._encoding,
index=False,
)
