semvec/pypi-packages huggingface dataset:
sklearn_freezer 0.2.0
Utility package for compiling scikit-learn classifiers for faster single-sample inference
Requires Python: >=3.10

# Sklearn-Freezer

High-performance scikit-learn classifier compilation for ultra-fast inference.

## Overview

Compiles scikit-learn `predict_proba` methods into optimized implementations for real-time applications.

**Support:** `RandomForestClassifier` and `DecisionTreeClassifier` binary classification only.

## Installation

```bash
pip install sklearn-freezer[all]  # Includes all backends
```

## Quick Start

```python
import sklearn_freezer as skf
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification
import numpy as np

# Train model
X, y = make_classification(n_samples=1000, n_features=4, random_state=42, n_classes=2)
clf = RandomForestClassifier(random_state=42).fit(X, y)

# Compile for single fast inference
fast_predict = skf.compile(clf.predict_proba, backend="c")

# Fast prediction
probability = fast_predict(*X[0])
```

## Backends

- **python**: Pure Python (baseline)
- **cython**: Cython-compiled (faster)
- **c**: Native C extension (fastest)

## Batch Processing

```python
# Compile for fast batch inference (cython/c only)
batch_predict = skf.compile(clf.predict_proba, backend="c", batch_mode="numpy")

# Example batch input
X_batch = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.float64)

# Get probabilities using the compiled implementation
probabilities = batch_predict(X_batch)

# Get probabilities using the original scikit-learn method
# Both results should be identical, but the compiled implementation is faster
probabilities = clf.predict_proba(X_batch)[:, 1]
```

## Module Caching

```python
# Save compiled module for reuse
fast_predict = skf.compile(clf.predict_proba, backend="c", module_name="my_model")
# Subsequent calls with same module_name will reuse if source unchanged
```

## Examples

```bash
python example/basic_compiler_test.py      # Basic compilation test
python example/sklearn_model_benchmark.py  # Model performance benchmark
```

## Requirements

- Python 3.10+
- scikit-learn
- cython (for Cython backend)
- setuptools (for C backend)
- a C compiler (for C backends)
mseep-ffmpeg-mcp 1.0.1
使用ffmpeg,对视频进行裁剪，拼接，滤镜等操作
Requires Python: >=3.10

/app/publisher/tmp/pypi_publish_f640c5ae-0826-4b06-9174-5fd3a8dfc2c7/package/Package managed by MseeP.ai
microprojects 0.1.1
MicroProjects in Python
Requires Python: >=3.10
Keywords: calculator, ideas, microprojects, project ideas

## MicroProjects
This is a collection of MicroProjects I code for fun..

## Table of Content
- [MicroProjects](#microprojects)
- [Table of Content](#table-of-content)
- [Getting MicroProjects](#getting-microprojects)
    - [Source](#source)
    - [PyPI (Python)](#pypi-python)
- [1. Calculator](#1-calculator)
    - [Usage:](#usage)
- [2. ngit](#2-ngit)
    - [Usage:](#usage-1)

## Getting MicroProjects

### Source

Clone the development version from [MicroProjects - GitHub](https://github.com/nyx-4/MicroProjects.git)

```sh
git clone https://github.com/nyx-4/MicroProjects.git
cd MicroProjects
pip install .
```

### PyPI (Python)

Use the package manager pip to install foobar.

```sh
pip install microprojects
```


## 1. [Calculator](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/calc)
A simple calculator written in Python that _just_ works. The source code is available on [nyx-4/MicroProjects/calc - GitHub](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/calc).

### [Usage](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/calc#usage):
- From CLI: `calc 5 + 10 x 3 - 2`
- As Python module: `python -m microprojects.calc 5 + 10 x 3 - 2`
- From Python source: `microprojects.calc("5 + 10 x 3 - 2")`


## 2. [ngit](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/ngit)
Git re-implementation in Python that is _perfectly compatible_ with with [Git SCM](https://git-scm.com/). The source code is available on [nyx-4/MicroProjects/ngit - GitHub](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/ngit).

### [Usage](https://github.com/nyx-4/MicroProjects/tree/main/microprojects/ngit#usage):
- From CLI:
```sh
ngit init
```