Helo is a simple and small low-level asynchronous ORM using Python asyncio. It is very intuitive and easy to use.
Helo can help you easily build expressive common SQL statements in your asynchronous applications. You only need to use friendly object-oriented APIs to manipulate data without caring about the details of SQL statement writing and data processing.
- Requires: Python 3.7+
- Only supports MySQL now, and the version is 5.7+
- Integration with web framework:
- quart, see with quart
- Not supports table relationship now
$ pip install helo
See the installation wiki page for more options.
See the wiki page for more information and quickstart documentation.
First, you should to import helo
and instantiate a global variable with helo.G
import helo
db = helo.G()
Defining models is simple:
class Author(helo.Model):
id = helo.BigAuto()
name = helo.VarChar(length=45, null=False)
email = helo.Email(default='')
password = helo.VarChar(length=100, null=False)
create_at = helo.Timestamp(default=helo.ON_CREATE)
class Post(helo.Model):
id = helo.Auto()
title = helo.VarChar(length=100)
author = helo.Int(default=0)
content = helo.Text(encoding=helo.ENCODING.UTF8MB4)
create_at = helo.Timestamp(default=helo.ON_CREATE)
update_at = helo.Timestamp(default=helo.ON_UPDATE)
Show some basic examples:
import asyncio
import datetime
async def show_case():
# Binding the database(creating a connection pool)
await db.bind('mysql://user:password@host:port/db')
# Creating tables
await db.create_tables([Author, Post])
# Inserting few rows:
author = Author(name='at7h', password='1111')
author_id = await author.save()
print(author_id) # 1
authors = await Author.get(author_id)
print(author.id, author.name) # 1, at7h
await Author.update(email='g@gmail.com').where(Author.id == author_id).do()
ret = await Author.insert(name='pope', password='2222').do()
posts = [
{'title': 'Python', 'author': 1},
{'title': 'Golang', 'author': 2},
]
ret = await Post.minsert(posts).do()
print(ret) # (2, 1)
# Supports expressive and composable queries:
count = await Author.select().count()
print(count) # 2
# Last gmail author
author = await Author.select().where(
Author.email.endswith('gmail.com')
).order_by(
Author.create_at.desc()
).first()
print(author) # [<Author object at 1>]
# Using `helo.adict`
authors = await Author.select(
Author.id, Author.name
).where(
Author.id < 2
).all(wrap=False)
print(author) # [{'id': 1, 'name': 'at7h'}]
# Paginate get authors who wrote Python posts this year
authors = await Author.select().where(
Author.id.in_(
Post.select(Post.author).where(
Post.update_at > datetime.datetime(2019, 1, 1),
Post.title.contains('Python')
).order_by(
Post.update_at.desc()
)
)
).paginate(1, 10)
print(authors) # [<Author object at 1>]
# How many posts each author wrote?
author_posts = await Author.select(
Author.name, helo.F.COUNT(helo.SQL('1')).as_('posts')
).join(
Post, helo.JOINTYPE.LEFT, on=(Author.id == Post.author)
).group_by(
Author.name
).rows(100)
asyncio.run(show_case())
If you're using quart , a minimum application example is:
import quart
import helo
app = quart.Quart(__name__)
app.config["HELO_DATABASE_URL"] = "mysql://user:password@host:port/db"
db = helo.G(app)
@app.route('/api/authors')
async def authors():
await Author.insert(
name='at7h', email='g@test.com', password='xxxx'
).do()
author_list = await Author.select().all(False)
return quart.jsonify(author_list)
app.run()
Run it:
$ curl http://127.0.0.1:5000/api/authors
[{"email":"g@test.com","id":1,"name":"at7h","password":"xxxx"}]
👉 See more examples
I hope those who are interested can join in and work together.
Any kind of contribution is expected: report a bug 🐞, give a advice or create a pull request 🙋♂️