importation code factorization

ChildProject/annotations.py

@@ -31,7 +31,7 @@ class AnnotationManager:
  IndexColumn(name = 'range_onset', description = 'covered range start time in milliseconds, measured since `time_seek`', regex = r"([0-9]+)", required = True),
  IndexColumn(name = 'range_offset', description = 'covered range end time in milliseconds, measured since `time_seek`', regex = r"([0-9]+)", required = True),
  IndexColumn(name = 'raw_filename', description = 'annotation input filename location, relative to `annotations/<set>/raw`', filename = True, required = True),
- IndexColumn(name = 'format', description = 'input annotation format', choices = ['TextGrid', 'eaf', 'vtc_rttm', 'vcm_rttm', 'alice', 'its', 'cha', 'NA'], required = False),
+ IndexColumn(name = 'format', description = 'input annotation format', choices = converters.keys() + ['NA'], required = False),
  IndexColumn(name = 'filter', description = 'source file to filter in (for rttm and alice only)', required = False),
  IndexColumn(name = 'annotation_filename', description = 'output formatted annotation location, relative to `annotations/<set>/converted (automatic column, don\'t specify)', filename = True, required = False, generated = True),
  IndexColumn(name = 'imported_at', description = 'importation date (automatic column, don\'t specify)', datetime = "%Y-%m-%d %H:%M:%S", required = False, generated = True),
@@ -195,27 +195,9 @@ def _import_annotation(self, import_function: Callable[[str], pd.DataFrame], ann
  try:
  if callable(import_function):
  df = import_function(path)
- elif annotation_format == 'TextGrid':
- from .converters import TextGridConverter
- df = TextGridConverter.convert(path)
- elif annotation_format == 'eaf':
- from .converters import EafConverter
- df = EafConverter.convert(path)
- elif annotation_format == 'vtc_rttm':
- from .converters import VtcConverter
- df = VtcConverter.convert(path, source_file = filter)
- elif annotation_format == 'vcm_rttm':
- from .converters import VcmConverter
- df = VcmConverter.convert(path, source_file = filter)
- elif annotation_format == 'its':
- from .converters import ItsConverter
- df = ItsConverter.convert(path, recording_num = filter)
- elif annotation_format == 'alice':
- from .converters import AliceConverter
- df = AliceConverter.convert(path, source_file = filter)
- elif annotation_format == 'cha':
- from .converters import ChatConverter
- df = ChatConverter.convert(path)
+ elif annotation_format in converters:
+ converter = converters[annotation_format]
+ df = converter.convert(path, filter)
  else:
  raise ValueError("file format '{}' unknown for '{}'".format(annotation_format, path))
  except:

ChildProject/converters.py

@@ -128,7 +128,7 @@ def convert(filename: str, source_file: str = '') -> pd.DataFrame:
 
 class AliceConverter(AnnotationConverter):
  FORMAT = 'alice'
- 
+
  @staticmethod
  def convert(filename: str, source_file: str = '') -> pd.DataFrame:
  df = pd.read_csv(
@@ -287,10 +287,10 @@ def extract_from_regex(pattern, subject):
  return df
 
 class TextGridConverter(AnnotationConverter):
- FORMAT = 'textgrid'
+ FORMAT = 'TextGrid'
 
  @staticmethod
- def convert(filename: str) -> pd.DataFrame:
+ def convert(filename: str, filter = None) -> pd.DataFrame:
  import pympi
  textgrid = pympi.Praat.TextGrid(filename)
 
@@ -330,7 +330,7 @@ class EafConverter(AnnotationConverter):
  FORMAT = 'eaf'
 
  @staticmethod
- def convert(filename: str) -> pd.DataFrame:
+ def convert(filename: str, filter = None) -> pd.DataFrame:
  import pympi
  eaf = pympi.Elan.Eaf(filename)
 
@@ -463,7 +463,7 @@ def role_to_addressee(role):
  return ChatConverter.ADDRESSEE_TABLE[ChatConverter.SPEAKER_ROLE_TO_TYPE[role]]
 
  @staticmethod
- def convert(filename: str) -> pd.DataFrame:
+ def convert(filename: str, filter = None) -> pd.DataFrame:
 
  import pylangacq