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This is a simple json database. The package provides a simple ORM between python objects and json objects with a well type-hinted schema.
engine = AppEngine()
async with engine.students as students:
students.add_range(Student("John", "Doe"), Student("Jane", "Doe"))
async for student in engine.students:
print(student.first_name, student.last_name)
# Can you guess ? )
This package maps your python objects to json and then you can save, get, modify or delete them using async methods.
This package is for tiny and simple projects. with a low amount of data.
The package is available at PYPI as json-entity.
Let's see how you can get started with the package.
See also our Wiki.
You can take a look at src/examples, if you're not on reading mode.
This data base consist of 3 main elements:
1- Model
It's obvious that you should have a model for your data to save, update, or ...
Since this library works with json, your model can contain everything
that JSON can.
2- Collection
You have a collection of data for every model, therefor,
The relation between Model and Collection is one to one.
3- Engine
This is where all collections are operate.
So, Every Engine
has some Collection
s where each collection
contains a set of an unique Model
.
Models are simple python class.
from sjd import TEntity, Engine, properties as props
@props.auto_collect()
class Person(TEntity):
def __init__(self, first_name: int, last_name: str, age: int):
self.first_name = first_name
self.last_name = last_name
self.age = age
Using auto_collect()
method,
the model will automatically collect properties form __init__
method.
It's really not necessary to create a collection by your own! And maybe you better )
Let us do that for ya ( Of course you can create customized Collections ).
Now you need to setup database's engine and define your collections there.
# ---- sniff ----
class AppEngine(Engine):
__db_path__ = "my_database"
persons = Engine.set(Person)
That's all you need to do for now.
Now it's time for some fireworks 🎇.
Since the package is async
, you'll need an event loop for it.
import asyncio
# ---- sniff ----
async def main():
...
if __name__ == "__main__":
asyncio.run(main())
Now you can work with database inside main function.
async def main():
engine = AppEngine()
collection = engine.persons
async with collection:
collection.add_range(
Person("John", "Doe", 20),
Person("Jane", "Doe", 21),
Person("Jack", "jones", 22),
Person("Jill", "jones", 23),
)
Iterate over all persons in the collection
async for person in collection:
print(person.first_name, person.last_name, person.age)
You can do more advanced query stuff with queryable context
.
async with collection.get_queryable() as persons:
async for person in persons.where(lambda p: p.age > 21):
print(person.first_name, person.last_name, person.age)
Or get only one directly.
target = await collection.get_first_async(lambda s: s.first_name, "John")
You can easily update your data:
async with collection.get_queryable() as persons:
async for person in persons.where(lambda p: p.last_name == "jones"):
person.last_name = "Jones"
await collection.save_changes_async()
Or even delete them ...
async with collection.get_queryable() as persons:
async for person in persons.where(lambda p: p.last_name == "Doe"):
collection.delete(person)
await collection.save_changes_async()
There're a lot more! see src/examples.
FAQs
A simple and async json database.
We found that json-entity demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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