semvec/pypi-packages huggingface dataset:
graphs-kpineiro 1.1.4
Homework 4 CS3250
Requires Python: >=3.7

Overview

* Heap: A special kind of binary tree where the parent node is always smaller than its child nodes.
* The smallest element is always at the top (heap[0]).
* Heaps are useful for efficiently managing priority queues.

Key Functions
* heappush(heap, item): Adds an item to the heap while maintaining its order.
* heappop(heap): Removes and returns the smallest item from the heap.
* heapify(x): Converts a list into a heap in place.
* heappushpop(heap, item): Adds an item to the heap, then removes and returns the smallest item.
* heapreplace(heap, item): Removes and returns the smallest item, then adds the new item to the heap.
ws-hash 1.0.0
A simple yet hash library implemented in Python, featuring both 256-bit and 512-bit hash functions.
Requires Python: >=3.6

# 🛠️ ws-hash

![Python](https://img.shields.io/badge/python-3.8%2B-blue.svg) 
![License](https://img.shields.io/badge/license-GNU%20GPLv3-green.svg)

A simple hash library implemented in Python, featuring both 256-bit and 512-bit hash functions.

> [!CAUTION]
> THIS LIBRARY IS NOT TESTED FOR BEING SECURE, DO NOT STORE SENSITIVE INFORMATION WITH THIS.

## Features
> What this silly little library is capable of.

- **256-bit Hashing**: Can produce hashes with a bit size of 256.
- **512-bit Hashing**: Can produce hashes with a bit size of 512.

## Installation
> Installing the silly hash Library.

You can install `ws-hash` by installing the package from the python-package-index (pypi). To do this, run the install command below.

```python
pip install ws-hash
```

## Usage
> Importing the silly Library.

To use the ws-hash functions, you can import them as follows:

```python
import ws_hash
```
Hashing Example

Here's how to hash a string using both the 256-bit and 512-bit functions:

```python
# Hash & print the string in ws256 and ws512.
print(ws_hash.ws256("Lorem ipsum, dolor sit amet."))
print(ws_hash.ws512("Lorem ipsum, dolor sit amet."))
```
bcsl-python 0.8.0
Bootstrap-based Causal Structure Learning
Requires Python: >=3.6

# BCSL Python

Python port of the Bootstrap-based Causal Structure Learning Algorithm. Depends on the causal-learn package for scoring.


## Installation

```bash
pip install bcsl-python causal-learn
```

## Usage

```python
import numpy as np

from bcsl import BCSL

# Generate synthetic data for testing
n_samples = 200

# Independent variables
Var1 = np.random.normal(0, 1, n_samples)
Var2 = np.random.normal(0, 1, n_samples)

# Dependent variables
Var3 = 2 * Var1 + np.random.normal(0, 1, n_samples)  # Var3 depends on Var1
Var4 = 0.5 * Var2 + np.random.normal(0, 1, n_samples)  # Var4 depends on Var2
Var5 = (
        Var3 + Var4 + np.random.normal(0, 1, n_samples)
)  # Var5 depends on Var3 and Var4
data = pd.DataFrame(
    {"Var1": Var1, "Var2": Var2, "Var3": Var3, "Var4": Var4, "Var5": Var5}
)
bcsl = BCSL(data, num_bootstrap_samples=4)

# Step 1: Learn local skeletons using HITON-PC
local_skeletons = bcsl.learn_local_skeleton()
print("Local Skeletons:", local_skeletons)

# Step 2: Resolve asymmetric edges using bootstrap
undirected_graph = bcsl.combine_local_to_global_skeleton()
print("Global Skeleton (resolved):", bcsl.global_skeleton)
print("Undirected Graph:", undirected_graph)

# Step 3: Orient edges using BDeu and hill-climbing
dag = bcsl.orient_edges()
print("Final DAG:", dag)
```

## Reference
Xianjie Guo, Yujie Wang, Xiaoling Huang, Shuai Yang, and Kui Yu. 2022. Bootstrap-based Causal Structure Learning. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM '22). Association for Computing Machinery, New York, NY, USA, 656–665. https://doi.org/10.1145/3511808.3557249
grscheller.untyped 0.4.1
### Untyped Modules - OBSOLETED!
Requires Python: >=3.11

# Python modules geared to code that is not strictly typed

Class Nada represents a missing value. Unlike None, it accepts almost
all methods and returns itself. See [grscheller.experimental][2] on PyPI
for the current maintained version.

* **Repositories**
  * obsoleted PyPI project [grscheller.untyped][1]
  * replaced by PyPI project [grscheller.experimental][2]
  * [Source code][3] on *GitHub*

### Modules

* grscheller.untyped.nada
  * singleton representing the absence of a value
  * failed attempt to give Python a bottom type

---

[1]: https://pypi.org/project/grscheller.untyped/
[2]: https://pypi.org/project/grscheller.experimental/
[3]: https://github.com/grscheller/untyped/