semvec/pypi-packages huggingface dataset:
smart-budgeting-pkg 0.1.0
Reusable budget projections & anomaly checks for Spendwise
License: MIT
Requires Python: >=3.9

# smart-budgeting-pkg

Reusable finance analytics for Spendwise:

- Moving average & projection of month-end spend
- Budget status (projected vs. limit)
- Simple anomaly detection hooks

## Quickstart

```python
from smart_budgeting_pkg.analytics import BudgetInsights
bi = BudgetInsights(window=4, warn_threshold=0.1)
proj = bi.projected_monthly_spend(month_to_date=220.0, days_elapsed=7, days_in_month=30)
print(bi.budget_status(budget=800.0, projected=proj))
```
cv-tasks-lib 1.0.0
Computer Vision Library - Display source code for 9 CV tasks
License: MIT
Requires Python: >=3.7
Keywords: computer-vision, opencv, image-processing, education

# CVLIB - Computer Vision Library

A Python library that displays complete source code for 9 computer vision tasks.

## Installation

```bash
pip install cvlib
```

## Usage

Import and display the source code of any task:

```python
import cvlib

# Display individual tasks
cvlib.show_task_1()    # Image handling
cvlib.show_task_2()    # Geometric transformations
cvlib.show_task_3()    # Homography matrix
cvlib.show_task_4()    # Perspective transformation
cvlib.show_task_5()    # Camera calibration
cvlib.show_task_6()    # Fundamental matrix
cvlib.show_task_7()    # Edge, line, corner detection
cvlib.show_task_8()    # SIFT features
cvlib.show_task_9()    # SIFT and HOG descriptors

# Display all 9 tasks
cvlib.show_all()
```

## Available Functions

- `show_task_1()` - Image operations (resize, rotate, flip, blur)
- `show_task_2()` - Geometric transformations (translation, rotation, scaling, shearing)
- `show_task_3()` - Homography matrix computation
- `show_task_4()` - Perspective transformation
- `show_task_5()` - Camera calibration with barrel distortion
- `show_task_6()` - Fundamental matrix from stereo images
- `show_task_7()` - Canny edges, Hough lines, Harris/Shi-Tomasi corners
- `show_task_8()` - SIFT keypoint detection and descriptors
- `show_task_9()` - SIFT and HOG descriptors
- `show_all()` - Display all 9 tasks

## Example

```python
import cvlib

# See the complete code for task 1
cvlib.show_task_1()

# Output:
# ================================================================================
# TASK 1: IMAGE HANDLING AND PROCESSING
# ================================================================================
# def image_operations(image_path=None):
#     """Task 1: Perform basic image operations: resize, rotate, flip, blur"""
#     if image_path is None:
#         from skimage import data
#         img = data.astronaut()
#     ...
```

## Requirements

- Python >= 3.7
- opencv-python
- numpy
- matplotlib
- scikit-image
- scikit-learn

## License

MIT
exasol-sagemaker-extension 0.11.6
Exasol SageMaker Integration
License: MIT
Requires Python: <4.0,>=3.10
Keywords: exasol, sagemaker

# SageMaker Extension

This project provides a Python library that trains data stored in Exasol using AWS SageMaker.


## Table of Contents

### Information for Users

* [User Guide](doc/user_guide/user_guide.md)
* [Tutorial](https://github.com/exasol/data-science-examples/blob/main/tutorials/machine-learning/sagemaker-extension/tutorial.md)
* [Changelog](doc/changes/changelog.md)

### Information for Contributors


* [System Requirement Specification](doc/system_requirements.md)
* [Design](doc/design.md)
* [Dependencies](doc/dependencies.md)