SQLAlchemy
Pytorch
SQLAlchemy | Pytorch | |
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124 | 340 | |
8,841 | 78,016 | |
2.6% | 1.4% | |
9.7 | 10.0 | |
about 24 hours ago | 7 days ago | |
Python | Python | |
MIT License | BSD 1-Clause License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SQLAlchemy
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Python: A SQLAlchemy Wrapper Component That Works With Both Flask and FastAPI Frameworks
In SQLAlchemy, models representing database tables typically subclass sqlalchemy.orm.DeclarativeBase (this class supersedes the sqlalchemy.orm.declarative_base function). Accordingly, the abstract base class in this database wrapper component is a sqlalchemy.orm.DeclarativeBase subclass, accompanied by another custom base class providing additional dunder methods.
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Xz/liblzma: Bash-stage Obfuscation Explained
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can we start considering binary files committed to a repo, even as data for tests, to be a huge red flag, and that the binary files themselves should instead be generated at testing time by source code that's stated as reviewable cleartext. This would make it much harder (though of course we can never really say "impossible") to embed a substantial payload in this way.
when binary files are part of a test suite, they are typically trying to illustrate some element of the program being tested, in this case a file that was incorrectly xz-encoded. Binary files like these weren't typed by hand, they will always ultimately come from something plaintext source.
Here's an example! My own SQLAlchemy repository has a few binary files in it! https://github.com/sqlalchemy/sqlalchemy/blob/main/test/bina... oh noes. Why are those files there? well in this case I just wanted to test that I can send large binary BLOBs into the database driver and I was lazy. This is actually pretty dumb, the two binary files here add 35K of useless crap to the source, and I could just as easily generate this binary data on the fly using a two liner that spits out random bytes. Anyone could see that two liner and know that it isn't embedding a malicious payload.
If I wanted to generate a poorly formed .xz file, I'd illustrate source code that generates random data, runs it through .xz, then applies "corruption" to it, like zeroing out the high bit of every byte. The process by which this occurs would be all reviewable in source code.
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Introducing Flama for Robust Machine Learning APIs
Besides, flama also provides support for SQL databases via SQLAlchemy, an SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. Finally, flama also provides support for HTTP clients to perform requests via httpx, a next generation HTTP client for Python.
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Alembic with Async SQLAlchemy
Alembic is a lightweight database migration tool for usage with SQLAlchemy. The term migration can be a little misleading, because in this context it doesn't mean to migrate to a different database in the sense of using a different version or a different type of database. In this context, migration refers to changes to the database schema: add a new column to a table, modify the type of an existing column, create a new index, etc..
- Imperative vs. Declarative mapping style in Domain Driven Design project
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Unlocking efficient authZ with Cerbos’ Query Plan
To simplify this process, Cerbos developers have come up with adapters for popular Object-Relational Mapping (ORM) frameworks. You can check out for more details on the query plan repo - which also contains adapters for Prisma and SQLAlchemy - as well as a fully functioning application using Mongoose as its ORM.
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Python: Just Write SQL
That above pattern is one I've seen people do even recently, using the "select().c" attribute which from very early versions of SQLAlchemy is defined as "the columns from a subquery of the SELECT" ; this usage began raising deprecation warnings in 1.4 and is fully removed in 2.0 as it was a remnant of a much earlier version of SQLAlchemy. it will do exactly as you say, "make a subquery for each filter condition".
the moment you see SQLAlchemy doing something you see that seems "asinine", send an example to https://github.com/sqlalchemy/sqlalchemy/discussions and I will clarify what's going on, correct the usage so that the query you have is what you expect, and quite often we will add new warnings or documentation when we see people doing things we didn't anticipate.
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A steering council note about making the global
The creator and lead maintainer of SQLAlchemy, one of the most popular and most used Python library for accessing databases (who doesn't?) gave a rather interesting response to PEP703.
If this doesn't ring any alarm bells I don't know what will.
> Basically for the moment the GIL-less idea would likely be burdensome for us and the fact that it's only an "option" seems to strongly imply major compatibility issues that we would not prefer.
https://github.com/sqlalchemy/sqlalchemy/discussions/10002#d...
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More public SQL-queryable databases?
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.
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How useful is Python in accounting and auditing?
When using python with sql databases like postgres or mariadb or SQLite you would use SQLAlchemy or another ORM of if you're feeling brave, you code it by hand. With ORMs you provide the address of your database and it connects for you, letting you use abstractions instead of writing all the SQL yourself (kind of analogous to using vlookups or index match instead of manually entering data).
Pytorch
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Clasificador de imágenes con una red neuronal convolucional (CNN)
PyTorch (https://pytorch.org/)
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AI enthusiasm #9 - A multilingual chatbot📣🈸
torch is a package to manage tensors and dynamic neural networks in python (GitHub)
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
What are some alternatives?
tortoise-orm - Familiar asyncio ORM for python, built with relations in mind
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
PonyORM - Pony Object Relational Mapper
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Peewee - a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Orator - The Orator ORM provides a simple yet beautiful ActiveRecord implementation.
flax - Flax is a neural network library for JAX that is designed for flexibility.
prisma-client-py - Prisma Client Python is an auto-generated and fully type-safe database client designed for ease of use
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
pyDAL - A pure Python Database Abstraction Layer
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more