betterdataclass 4.0

A multipurpose dataclass libarary used for validation and data structuring.

betterdataclass is a Python library that enhances the functionality of the existing dataclass system. It provides additional features and improvements to make working with data classes even better.

Features

1. StrictDictionary

The StrictDictionary class is a powerful data class that acts like a dictionary, allowing you to store and access key-value pairs. It enforces strict typing of the values based on the annotations of the class attributes, ensuring data integrity and preventing type-related bugs.

2. StrictList

The StrictList class is an enhanced version of the built-in list class. It allows you to create lists with strict typing and restrictions on the elements. You can define the allowed types or even customize restrictions to ensure that only valid elements are added to the list.

Authors

• @Asutosh Rath

Installation

You can install betterdataclass using pip:

pip install betterdataclass

Restrictions

• Accepted typing Types

  • Union

  • Optional

  • Final

  • Dict

  • Tuple

  • Set

  • List

  • Literal

  • anything that ``typing.get_origin()`` 1 times leads to the aforementioned types or the default generic types

• Can’t produce JSON file out of Enum, but it is accepted.

• Can’t add data members post class defination, i.e. in runtime.

Usage Example- StrictDictionary

Let’s see a simple example of using betterdataclass to create a strict dictionary and list.

Creating a ``StrictDictionary``

from betterdataclass import StrictDictionary

class Person(StrictDictionary):
    name: str
    age: int

# Create an instance of the strict dictionary
person = Person(name='John', age=30)

# Access the attributes
print(person.name)  # Output: John
print(person.age)   # Output: 30

# Add new attribute with type checking
person['address'] = '123 Main Street'

# Print the strict dictionary
print(person)       # Output: {'name': 'John', 'age': 30, 'address': '123 Main Street'}

Creating a ``StrictList``

from betterdataclass import StrictList

class NumberList(StrictList):
    types = (int, float)

# Create an instance of the strict list
numbers = NumberList([1, 2, 3.14])

# Access the elements
print(numbers[0])   # Output: 1
print(numbers[1])   # Output: 2
print(numbers[2])   # Output: 3.14

# Add new element with type checking
numbers.append(4)

# Print the strict list
print(numbers)      # Output: [1, 2, 3.14, 4]

More ``StrictDictionary`` complex Example

This will speed you up what are the edge capabilities of the library is. 1. ### Example 1 ```python from betterdataclass import StrictDictionary from typing import List, Optional

class Address(StrictDictionary):
    street: str
    city: str
    postal_code: str

class Person(StrictDictionary):
    name: str
    age: int
    addresses: List[Address]
    phone: Optional[str] = None

# Create an instance of the strict dictionary
person = Person(
    name='John',
    age=30,
    addresses=[
        Address(street='123 Main Street', city='New York', postal_code='10001'),
        Address(street='456 Elm Street', city='Los Angeles', postal_code='90001')
    ],
    phone='555-1234'
)

# Access the attributes
print(person.name)
print(person.age)
print(person.addresses)
print(person.phone)

# Add new attribute with type checking

# Print the strict dictionary
print(person)
```
~~``` person['email'] = '[e-mail]' ```~~
<br>*This won't work. I can't add new data members on the go. Hence the name StrictDictionary.*

2. Example 2.

   from betterdataclass import StrictDictionary
   from typing import List, Dict, Any
   
   class Address(StrictDictionary):
       street: str
       city: str
       postal_code: str
   
   class Contact(StrictDictionary):
       email: str
       phone: str
   
   class Person(StrictDictionary):
       name: str
       age: int
       addresses: List[Address]
       contacts: Dict[str, Contact]
       metadata: Dict[str, Any]
   
   # Create an instance of the strict dictionary
   person = Person(
       name='John',
       age=30,
       addresses=[
           Address(street='123 Main Street', city='New York', postal_code='10001'),
           Address(street='456 Elm Street', city='Los Angeles', postal_code='90001')
       ],
       contacts={
           'personal': Contact(email='[e-mail]', phone='555-1234'),
           'work': Contact(email='[e-mail]', phone='555-5678')
       },
       metadata={
           'employee_id': 12345,
           'position': 'Manager',
           'active': True
       }
   )
   
   # Access the attributes
   print(person.name)
   print(person.age)
   print(person.addresses)
   print(person.contacts)
   print(person.metadata)
   
   # Access nested attributes
   print(person.addresses[0].street)
   print(person.contacts['personal'].email)
   print(person.metadata['position'])

3. Example 3.

   from betterdataclass import StrictDictionary
   from typing import Dict, Union, Optional
   
   class Address(StrictDictionary):
       street: str
       city: str
       postal_code: str
   
   class Contact(StrictDictionary):
       email: str
       phone: Union[str, int]
   
   class Person(StrictDictionary):
       name: str
       age: int
       address: Optional[Address]
       contacts: Optional[Dict[str, Union[Contact, Dict[str, str]]]]
   
   # Create an empty instance of the strict dictionary
   person = Person()
   
   # Add data using key mapping and attribute setting
   person['name'] = 'John'
   person.name = 'John'
   person['age'] = 30
   person.age = 30
   
   # Add nested data using key mapping
   person['address'] = Address(street='123 Main Street', city='New York', postal_code='10001')
   
   # Add nested data using attribute setting
   person.address = Address(street='123 Main Street', city='New York', postal_code='10001')
   
   # Add multiple levels of nested data using key mapping
   person['contacts'] = {
       'personal': Contact(email='[e-mail]', phone='555-1234'),
       'work': {
           'email': '[e-mail]',
           'phone': 12345
       }
   }
   
   # Add multiple levels of nested data using attribute setting
   person.contacts = {
       'personal': Contact(email='[e-mail]', phone='555-1234'),
       'work': {
           'email': '[e-mail]',
           'phone': 12345
       }
   }
   
   # Print the strict dictionary
   print(person)

Usage Example- StrictList

Creating a ``StrictList``

from betterdataclass import StrictList

class NumberList(StrictList):
    types = (int, float)

# Create an instance of the strict list
numbers = NumberList([1, 2, 3.14])

# Access the elements
print(numbers[0])   # Output: 1
print(numbers[1])   # Output: 2
print(numbers[2])   # Output: 3.14

# Add new element with type checking
numbers.append(4)

# Print the strict list
print(numbers)      # Output: [1, 2, 3.14, 4]

Validation usage ``StrictList`` example

from betterdataclass import StrictList
import re

class EmailList(StrictList):
    def restriction(self, value):
        email_regex = r'^[\w\.-]+@[\w\.-]+\.\w+$'
        if not re.match(email_regex, str(value)):
            return False
        return True

# Create an instance of the EmailList
emails = EmailList()

# Add email values
emails.append('[e-mail]')
emails.append('[e-mail]')
emails.append('invalid_email')  # Throws error

# Print the list
print(emails)

Roadmap

• ☐ Make Validation decorators

• ☐ Make StrictDictionary comply with Enum

• ☐ Make it work with other dataclasses

The Long and the short is I want generalise all the dataclass options we got