excel-serializer 1.1.4

Dump/Load Excel files to/from Python objects

Excel Serializer

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.

Key Features

• 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.

Dependencies

• openpyxl: This module relies on the openpyxl library for reading from and writing to Excel files. Ensure that openpyxl is installed in your environment to use this module.

Installation

You can install the package using pip:

pip install excel-serializer

Builtin types

This 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.

Usage

Encoding basic Python object hierarchies

import excel_serializer as es

data = {'name': 'John', 'age': 30, 'city': 'New York'}
es.dump(data, 'data.xlsx')

Decoding Excel files

import excel_serializer as es

data = es.load('data.xlsx')
print(data)
# Output: {'name': 'John', 'age': 30, 'city': 'New York'}

Using a custom encoder

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)

Using a custom decoder

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}}

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Alexandre 'Tsu' Manuel - [e-mail]

Links

• Homepage