semvec/pypi-packages huggingface dataset:
nanodrr 0.1.0
Blazing fast differentiable DRR rendering in modern PyTorch
Requires Python: >=3.10

# nanodrr

A performance-oriented reimplementation of [`DiffDRR`](https://github.com/eigenvivek/DiffDRR) with the following improvements:

- Optimized, pure PyTorch implementation (**~5× faster than `DiffDRR` at baseline**)
- Modular design (freely swap subjects, extrinsics, and intrinsics during rendering)
- Compatibility with `torch.compile` and mixed precision
- Extensive type hints with `jaxtyping`
- Standard Python package structure managed with `uv`

All projective geometry is implemented internally using the standard [Hartley and Zisserman](https://www.cambridge.org/core/books/multiple-view-geometry-in-computer-vision/0B6F289C78B2B23F596CAA76D3D43F7A) pinhole camera formulation.

## Installation

> [!NOTE]
>
> On `pytorch<2.9`, `torch.compile` with `bfloat16` is slower than eager due to a CUDA graph capture issue (see [Benchmarks](#benchmarks)). Use `pytorch>=2.9` (Triton ≥3.5) for best results.

```
pip install "git+https://github.com/eigenvivek/nanodrr.git"
```

## Benchmarks

> [!IMPORTANT]
> - **~5× faster** than [`DiffDRR`](https://github.com/eigenvivek/DiffDRR) out of the box, without compilation (946 FPS vs 213 FPS)
> - **~8× faster** with `torch.compile` and `bfloat16` on `pytorch>=2.9` (1,650 FPS vs 213 FPS)
> - **~2.5× less memory** than `DiffDRR` (516 MB vs 1,344 MB peak reserved with `bfloat16` + compile)

![Benchmarking runtime, FPS, and memory usage.](tests/benchmark/benchmark.png "benchmark")

> *Mean ± std. dev. of 10 runs, 100 loops each. Benchmarked by rendering 200×200 DRRs on an NVIDIA RTX 6000 Ada (48 GB) with Python 3.12. Compile represents `torch.compile(mode="reduce-overhead", fullgraph=True)`. Full experiment at [`tests/benchmark/`](tests/benchmark/).*

## Roadmap

- [x] Implement a fully optimized renderer
- [x] Port strictly necessary modules from `DiffDRR` (e.g., SE(3) utilities, loss functions, and 2D plotting)
- [x] Migrate 3D plotting functions to an optional module
- [ ] Integrate with [`xvr`](https://github.com/eigenvivek/xvr) to speed up network training and registration
- [ ] Integrate with [`polypose`](https://github.com/eigenvivek/polypose) to speed up registration
- [ ] Release as `v1.0.0` of `DiffDRR`!
pulp-python 3.25.1
pulp-python plugin for the Pulp Project
Requires Python: >=3.11

# pulp_python

[![PyPI](https://img.shields.io/pypi/v/pulp_python.svg)](https://pypi.python.org/pypi/pulp_python)
[![Pulp Nightly CI/CD](https://github.com/pulp/pulp_python/actions/workflows/nightly.yml/badge.svg)](https://github.com/pulp/pulp_python/actions/workflows/nightly.yml)

A Pulp plugin to support hosting your own pip compatible Python packages.

For more information, please see the [documentation](https://docs.pulpproject.org/pulp_python/) or the
[Pulp project page](https://pulpproject.org).
fakeredis 2.34.0
Python implementation of redis API, can be used for testing purposes.
Requires Python: >=3.7
Keywords: RedisBloom, RedisJson, RedisTimeSeries, dragonfly, redis, redis-stack, testing, valkey

fakeredis: A python implementation of Redis Protocol API
========================================================

[![badge](https://img.shields.io/pypi/v/fakeredis)](https://pypi.org/project/fakeredis/)
[![CI](https://github.com/cunla/fakeredis-py/actions/workflows/test.yml/badge.svg)](https://github.com/cunla/fakeredis-py/actions/workflows/test.yml)
[![badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/cunla/b756396efb895f0e34558c980f1ca0c7/raw/fakeredis-py.json)](https://github.com/cunla/fakeredis-py/actions/workflows/test.yml)
[![badge](https://img.shields.io/pypi/dm/fakeredis)](https://pypi.org/project/fakeredis/)
[![badge](https://img.shields.io/pypi/l/fakeredis)](./LICENSE)
[![Open Source Helpers](https://www.codetriage.com/cunla/fakeredis-py/badges/users.svg)](https://www.codetriage.com/cunla/fakeredis-py)
--------------------



Documentation is hosted in https://fakeredis.readthedocs.io/

# Intro

FakeRedis is a pure-Python implementation of the Redis Protocol API. It provides enhanced versions of
the [redis-py][redis-py]/[valkey-py][valkey-py] Python bindings for Redis.

It enables running tests requiring [Redis][redis]/[ValKey][valkey]/[DragonflyDB][dragonflydb]/[KeyDB][keydb] server
without an actual server.

It also enables testing compatibility of different key-value datastores.

That provides the following added functionality: A built-in Redis server that is automatically installed, configured and
managed when the Redis bindings are used. A single server shared by multiple programs or multiple independent servers.
All the servers provided by FakeRedis support all Redis functionality including advanced features such as RedisJson,
RedisBloom, GeoCommands.

See [official documentation][readthedocs] for list of supported commands.

# Sponsor

fakeredis-py is developed for free.

You can support this project by becoming a sponsor using [this link](https://github.com/sponsors/cunla).

[readthedocs]: https://fakeredis.readthedocs.io/

[redis-py]: https://github.com/redis/redis-py

[valkey]: https://github.com/valkey-io/valkey

[redis]: https://redis.io/

[dragonflydb]: https://dragonflydb.io/

[keydb]: https://docs.keydb.dev/

[valkey-py]: https://github.com/valkey-io/valkey-py