def render_book_to_stream(self,
file_stream,
book,
inits=None,
mapdicts=None,
**keywords):
session, tables = file_stream
thebook = book
initializers = inits
colnames_array = common.get_book_headers_in_array(book)
if initializers is None:
initializers = [None] * len(tables)
if mapdicts is None:
mapdicts = [None] * len(tables)
scattered = zip(tables, colnames_array, mapdicts, initializers)
importer = sql.SQLTableImporter(session)
for each_table in scattered:
adapter = sql.SQLTableImportAdapter(each_table[0])
adapter.column_names = each_table[1]
adapter.column_name_mapping_dict = each_table[2]
adapter.row_initializer = each_table[3]
importer.append(adapter)
to_store = OrderedDict()
for sheet in thebook:
# due book.to_dict() brings in column_names
# which corrupts the data
to_store[sheet.name] = sheet.get_internal_array()
save_data(importer, to_store, file_type=self._file_type, **keywords)
def render_book_to_stream(self, file_stream, book,
inits=None, mapdicts=None, **keywords):
session, tables = file_stream
thebook = book
initializers = inits
colnames_array = common.get_book_headers_in_array(book)
if initializers is None:
initializers = [None] * len(tables)
if mapdicts is None:
mapdicts = [None] * len(tables)
scattered = zip(tables, colnames_array, mapdicts, initializers)
importer = sql.SQLTableImporter(session)
for each_table in scattered:
adapter = sql.SQLTableImportAdapter(each_table[0])
adapter.column_names = each_table[1]
adapter.column_name_mapping_dict = each_table[2]
adapter.row_initializer = each_table[3]
importer.append(adapter)
to_store = OrderedDict()
for sheet in thebook:
# due book.to_dict() brings in column_names
# which corrupts the data
to_store[sheet.name] = sheet.get_internal_array()
save_data(importer, to_store, file_type=self._file_type, **keywords)
def render_book_to_stream(self,
models,
book,
inits=None,
mapdicts=None,
batch_size=None,
**keywords):
colnames_array = common.get_book_headers_in_array(book)
new_models = [model for model in models if model is not None]
initializers = inits
if initializers is None:
initializers = [None] * len(new_models)
if mapdicts is None:
mapdicts = [None] * len(new_models)
scattered = zip(new_models, colnames_array, mapdicts, initializers)
importer = django.DjangoModelImporter()
for each_model in scattered:
adapter = django.DjangoModelImportAdapter(each_model[0])
adapter.column_names = each_model[1]
adapter.column_name_mapping_dict = each_model[2]
adapter.row_initializer = each_model[3]
importer.append(adapter)
to_store = OrderedDict()
for sheet in book:
# due book.to_dict() brings in column_names
# which corrupts the data
to_store[sheet.name] = sheet.get_internal_array()
save_data(importer,
to_store,
file_type=self._file_type,
batch_size=batch_size,
**keywords)
def render_book_to_stream(self, models, book,
inits=None, mapdicts=None,
batch_size=None, **keywords):
colnames_array = common.get_book_headers_in_array(book)
new_models = [model for model in models if model is not None]
initializers = inits
if initializers is None:
initializers = [None] * len(new_models)
if mapdicts is None:
mapdicts = [None] * len(new_models)
scattered = zip(new_models, colnames_array, mapdicts, initializers)
importer = django.DjangoModelImporter()
for each_model in scattered:
adapter = django.DjangoModelImportAdapter(each_model[0])
adapter.column_names = each_model[1]
adapter.column_name_mapping_dict = each_model[2]
adapter.row_initializer = each_model[3]
importer.append(adapter)
to_store = OrderedDict()
for sheet in book:
# due book.to_dict() brings in column_names
# which corrupts the data
to_store[sheet.name] = sheet.get_internal_array()
save_data(importer, to_store, file_type=self._file_type,
batch_size=batch_size, **keywords)
def test_get_book_headers_in_array():
data = iter([["a", "b", "c"], [1, 2, 3]])
book_stream = BookStream({"test": data})
colnames_array = get_book_headers_in_array(book_stream)
eq_(colnames_array, [["a", "b", "c"]])
def test_get_book_headers_in_array():
data = iter([['a', 'b', 'c'], [1, 2, 3]])
book_stream = BookStream({'test': data})
colnames_array = get_book_headers_in_array(book_stream)
eq_(colnames_array, [['a', 'b', 'c']])