Excel Serializer is a Python package that provides a set of functions and classes to serialize and deserialize Python objects to and from Excel files. The API is designed to be intuitive and familiar, closely mirroring the interface of the built-in json module. This makes it easy to configure and use for developers who are already accustomed to working with JSON serialization.
- load: Deserialize an Excel file to a Python object.
- loadw: Deserialize an openpyxl workbook to a Python object.
- dump: Serialize a Python object to an Excel file.
- dumpw: Serialize a Python object to an openpyxl workbook.
- openpyxl: This module relies on the
openpyxllibrary for reading from and writing to Excel files. Ensure thatopenpyxlis installed in your environment to use this module.
You can install the package using pip:
pip install excel-serializerThis module has four builtin types:
List: A list of values.Tuple: A tuple of values.Dict: A dictionary of key-value pairs.DictList: A list of dictionaries all having the same keys.
You can easily add your own types by subclassing ExcelEncoder and ExcelDecoder classes. See how to do so in examples
below.
import excel_serializer as es
data = {'name': 'John', 'age': 30, 'city': 'New York'}
es.dump(data, 'data.xlsx')import excel_serializer as es
data = es.load('data.xlsx')
print(data)
# Output: {'name': 'John', 'age': 30, 'city': 'New York'}You can either convert the custom object to a built-in type:
import excel_serializer as es
class CustomEncoder(es.ExcelEncoder):
def default(self, obj):
if isinstance(obj, set):
return list(obj)
return super()._default(obj)
data = {'numbers': {1, 2, 3}}
es.dump(data, 'data.xlsx', cls=CustomEncoder)or implement a custom encoder to handle the serialization of the custom object:
import excel_serializer as es
class CustomEncoder(es.ExcelEncoder):
def write_set(self, sheet, type_cell, st):
cols = ('Value',)
type_cell.value = f'Set {type_cell.value}'
sheet.append((type_cell,))
sheet.append(cols)
for i, e in enumerate(st):
sheet.append((i + 1, self.encode(sheet, i + 3, 2, str(i + 1), e)))
return 2 + len(st), 1, cols
def write_custom_type(self, sheet, type_cell, obj):
if isinstance(obj, set):
return self.write_set(sheet, type_cell, obj)
return super().write_custom_type(sheet, type_cell, obj)
data = {'numbers': {1, 2, 3}}
es.dump(data, 'data.xlsx', cls=CustomEncoder)import excel_serializer as es
class CustomDecoder(es.ExcelDecoder):
def read_set(self, sheet_name, rows):
headers = next(rows)
if len(headers) != 1:
raise es.ExcelDecodeError(f'Invalid list headers. Expected 1, found {len(headers)}',
self.workbook, sheet_name, 2, len(headers) + 1)
if headers[0].value != 'Value':
raise es.ExcelDecodeError(f'Invalid list headers. Expected "Value", found "{headers[0].value}"',
self.workbook, sheet_name, 2, 1)
return set(self.read_value(row[0]) for row in rows)
def read_custom_type(self, sheet_type, sheet_name, rows):
if sheet_type == 'Set':
return self.read_set(sheet_name, rows)
return super().read_custom_type(sheet_type, sheet_name, rows)
data = es.load('data.xlsx', cls=CustomDecoder)
print(data)
# Output: {'numbers': {1, 2, 3}}This project is licensed under the MIT License. See the LICENSE file for details.
Alexandre 'Tsu' Manuel - tsu@sulvia.fr