Alexander Hultnér
Founder, Hultnér Technologies (https://hultner.se). Want me to speak at your company? Corporate training? Or just a fresh pair of eyes on your project? Contact me for contracts.
Data Classes
In Python 3.6 and beyond
PyCon SE 2018, Stockholm, Sweden
Alexander Hultnér
Alexander Hultnér
Lead Product Developer at Cetrez
Python Data Classes
Cetrez
A hybrid company within tech and business development.
- Build software system for large international brands
- Our HQ in Gothenburg is a Normandie inspired castle
- We host Hackathons, Meetups, etc
- We love Python
Python Data Classes
Outline
Python Data Classes
Alexander Hultnér
- Why
- Cheatsheet summary, Data Classes in two minutes
- History
- Using Data Classes
- Examples
- Utility Classes
- JSON-handling
- Interactive Jupyter session, showing real usecases
- Conclusion
- Questions & links
Why?
Python Data Classes
Alexander Hultnér
-
Simplifies Python Classes
- Less boilerplate => less bugs
-
Built on top of previous experience
- not bound to legacy
-
In standard Python
- Libraries and ecosystem likely to grow
- Extensible and customisable
Cheatsheet
Python Data Classes in two minutes
Alexander Hultnér
- Coming in Python 3.7
- Usable in 3.6
-
pip install dataclasses
- requires type annotations and sorted dict
-
- Native alternative to attrs
- Learned from NamedTuples
History
Python Data Classes
Alexander Hultnér
- NamedTuple
-
attrs
- Similar libraries
- ORM-libraries such as SQLAlchemy
- PEP 557-backport
Data class
Minimal example
""" A minimal basic example """
from dataclasses import dataclass
from datetime import datetime
# A PyCon Example class
@dataclass
class PyCon:
location: str
date: datetime
year: int = 2018 # Default year
# You get init, repr & eq for free out of the box
# More available through decorator paramsAlexander Hultnér
Data class
Extended example
@dataclass
class PyCon:
location: str
# Can be passed as a str or datetime
date: Union[datetime, str]
# Add a factory for this year
year: int = field(
default_factory=lambda: datetime.now().year
)
# post init runs after __init__ finishes
def __post_init__(self):
if isinstance(self.date, str):
# Raises a ValueError if string is invalid isoformat
self.date = datetime.fromisoformat(self.date)Alexander Hultnér
Utility functions
Python Data Classes
Alexander Hultnér
-
dataclass-module
- asdict
- astuple
- make_dataclass
- is_dataclass
- replace
- and more
-
Handy attributes on the class
- __annotations__
- __dataclass_params__
- __dataclass_fields__
JSON-Conversion
Python Data Classes
Alexander Hultnér
-
asdict
- Passed to json.dumps
-
Create instance from json
- Expand kwargs (**)
-
Custom JSONEncode
- Can be made in a few lines of code
- Will show more details in Jupyter
Interactive Jupyter session
Python Data Classes
Alexander Hultnér
Will show different different useful examples
in Jupyter Lab.
The notebook, with all code, links, etc from this
presentation will be available on my GitHub (@hultner)
Conclusion
Python Data Classes
Alexander Hultnér
- Great code generator
- Usable in 3.6 onward
- Native i 3.7
- Versatile
Go out and use data classes!
Questions?
And links!
Python Data Classes
Alexander Hultnér
Data Classes, in Python 3.6 and beyond
By Alexander Hultnér
Data Classes, in Python 3.6 and beyond
Python 3.7 is here and the @dataclass-decorator is a major new feature simplifying class-creation. In this talk, we will learn to use the power of data classes to make our codebases cleaner and leaner in a pythonic way. We will also learn how to use the back-port in Python 3.6 codebases before upgrading.
