Assimilator - the best Python patterns for the best projects
Install now
pip install py-assimilator
What is that all about?
- We want to write the best code.
- We need the best patterns and techniques for this.
- We use PyAssimilator and save lots of time.
- We use PyAssimilator and write the best code.
- We use PyAssimilator and use the best patterns.
- We use PyAssimilator and have no dependencies in our code.
- We use PyAssimilator and can switch one database to another in a matter of seconds.
- We learn PyAssimilator once and use it forever!
- And most importantly, we make Python projects better!
Code comparison
Before PyAssimilator:
# BAD CODE :(
def create_user(username: str, email: str):
# NO PATTERNS!
# ONLY ONE DATABASE CHOICE!
new_user = User(username=username, email=email, balance=0) # DEPENDENCY!
session = db_session() # DEPENDENCY!
session.add(new_user)
session.commit() # NO ACID TRANSACTIONS!
return new_user
After:
# GOOD CODE :)
def create_user(username: str, email: str, uow: UnitOfWork):
# BEST DDD PATTERNS
# PATTERN SUBSTITUTION/MULTIPLE DATABASES AT ONCE
with uow: # ACID TRANSACTIONS IN ANY DATABASE
new_user = uow.repository.save(
username=username, # NO MODEL DEPENDENCIES
email=email,
balance=0,
)
uow.commit() # AUTO ROLLBACK
return new_user
So, do I really need it?
If you want to spend less time writing your code, but write better code - then you must use PyAssimilator. It can be hard to start if you have no experience with good code, so you can watch creator's video tutorials.
Our vision
Make Python the best programming language for enterprise development and use all of its dynamic capabilities to write things that other languages can't even comprehend!
- Pattern substitution(switch databases easily) ✔️
- Event-based apps(in development) 🛠️
- 45% of all Python projects use PyAssimilator 🛠️
- Independent code(in development) 🛠️
- Adaptive patterns(in development) 🛠️
- Automatic code improvements(in development) 🛠️
- Decentralized code management(in development) 🛠️
If you want to help with any of those things - be free to contribute to the project. Remember, you never do anything for free - and that will not be the case either.
Sources
Contributors
Stars history
⭐Stargazers⭐
We love all people who star our library. You can look at all stargazers in the documentation:
https://knucklesuganda.github.io/py_assimilator/#stars-history
If you star the library you will appear there as well!
Types of patterns
These are different use cases for the patterns implemented:
- Database - patterns for database/data layer interactions.
- Events(in development) - projects with events or event-driven architecture.
- Unidentified - patterns that are useful for different purposes.
Available providers
Providers are different patterns for external modules like SQLAlchemy or FastAPI.
- Alchemy(Database, Events) - patterns for SQLAlchemy for both database and events.
- Kafka(Events) - patterns in Kafka related to events.
- Internal(Database, Events) - internal is the type of provider that saves everything in memory(dict, list and all the tools within your app).
- Redis(Database, Events) - redis_ allows us to work with Redis memory database.
- MongoDB(Database) - mongo allows us to work with MongoDB database.
1 maintainer
Metadata
1 maintainer
Release files for py-assimilator 1.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| py_assimilator-1.3.1.tar.gz | 27.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| py_assimilator-1.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 76.8 kB
Release files / py_assimilator-1.3.1.tar.gz
| Download URL | py_assimilator-1.3.1.tar.gz |
|---|---|
| Size | 27.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
43b3292a82a3bd7251ae7c531634f9c70544c21b807e8268c8f545aaa9b6e935
|
|
BLAKE2b-256 checksum How to use checksums |
6d19ffcc25b2efcdb164c8ed5fcff85c7a14b35ce792ff71574d73e489e9a893
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Release files / py_assimilator-1.3.1-py3-none-any.whl
| Download URL | py_assimilator-1.3.1-py3-none-any.whl |
|---|---|
| Size | 49.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
94f184f43097f7587f679a76489eb00e6aa40a1bdf95863458ff7d87a094fbd2
|
|
BLAKE2b-256 checksum How to use checksums |
9b669acbd24cb5489ae5a6c824244ac3778f8c6c83efc2795eb8df1a5b371443
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Security for py-assimilator 1.3.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
