semvec/pypi-packages huggingface dataset:
calc-figure-area 0.0.6
This library is test library.
License: MIT
Keywords: calc figure area

# Calc figure area Library #

## What is this? ##
This library is test library.
The library can calculate the area of a circle by its radius 
and a triangle by its three sides.

There is also a check to see if a triangle is right-angled.

### Using ###
Installation:
```
pip install calc-figure-area
```

Using the library is as simple and convenient as possible:

Let's import it first:
First, import everything from the library (use the `import calc_figure_area.calc_figure_area` construct).

Examples of all operations:
```
import calc_figure_area.calc_figure_area as my_lib

# Create new object
my_circle = my_lib.FigureFactory.create('circle', radius=5)
# Calc figure area
circle_area = my_lib.get_figure_area(my_circle)

# Print result
print(f"Circle area: {circle_area}")
print(f"Is triangle rectangle? {my_lib.is_figure_rectangle(my_circle)}")


# Create new object
my_triangle = my_lib.FigureFactory.create('triangle', side1=3, side2=4, side3=5)
# Calc figure area
triangle_area = my_lib.get_figure_area(my_triangle)

# Print result
print(f"Triangle area: {triangle_area}")
print(f"Is triangle rectangle? {my_lib.is_figure_rectangle(my_triangle)}")

```
smartchunks 0.1.1
Advanced Python chunking with stride, filtering, and expressions
License: MIT
Requires Python: >=3.7


# smartchunks

`smartchunks` is a flexible, powerful chunking utility for Python that provides more than just slicing — it allows pattern-based, overlapping, and conditional chunking.

---

## ✨ Features

- ✅ Standard fixed-size chunking
- ✅ `nth_position`: Take every nth item before or after chunking
- ✅ `chunk_position`: Pick every nth *chunk*
- ✅ `stride`: Create overlapping chunks (sliding window)
- ✅ `fillvalue`: Pad final incomplete chunks
- ✅ `filter_fn`: Apply a custom condition to keep or discard chunks
- ✅ `materialize`: Toggle between generator and list output

---

## 📦 Installation

```bash
pip install smartchunks
```

---

## 🧪 Usage Examples

```python
from smartchunks import chunked

data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
```

### 🔹 Standard Chunking
```python
print(list(chunked(data, size=3)))
# → [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
```

### 🔹 nth_position (Before Chunking)
```python
print(list(chunked(data, size=2, nth_position=2)))
# → [[1, 3], [5, 7], [9]]
```

### 🔹 chunk_position (Every nth Chunk)
```python
print(list(chunked(data, size=2, chunk_position=2)))
# → [[3, 4], [7, 8]]
```

### 🔹 nth_position After Chunking
```python
print(list(chunked(data, size=3, nth_position=2, apply_nth_before_chunk=False)))
# → [[2], [5], [8]]
```

### 🔹 Overlapping chunks (stride)
```python
print(list(chunked(data, size=3, stride=1)))
# → [[1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 6], [5, 6, 7], [6, 7, 8], [7, 8, 9]]
```

### 🔹 Padding incomplete chunks
```python
print(list(chunked([1, 2, 3, 4, 5], size=3, fillvalue=0)))
# → [[1, 2, 3], [4, 5, 0]]
```

### 🔹 Filtering chunks (keep those whose sum > 15)
```python
print(list(chunked(data, size=3, stride=1, filter_fn=lambda x: sum(x) > 15)))
# → [[5, 6, 7], [6, 7, 8], [7, 8, 9], [8, 9]]
```

### 🔹 Materialized output
```python
chunks = chunked(data, size=2)
print(next(chunks))  # Lazy generator by default

chunks = chunked(data, size=2, materialize=True)
print(chunks)  # Fully materialized list of chunks
```

---

## 🧠 Advanced Combinations

```python
print(list(chunked(data, size=2, stride=2, chunk_position=2, nth_position=2, apply_nth_before_chunk=False)))
# Apply chunking with stride, select every 2nd chunk, then take the 2nd element from each
```

---

## 📜 License
MIT License © 2024 Maurya Allimuthu

---

## 🧩 Special Examples

### 🔹 stride with overlap
```python
data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
print(list(chunked(data, size=3, stride=1)))
# → [[1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 6], [5, 6, 7], [6, 7, 8], [7, 8, 9]]
```

---

### 🔹 nth_position then chunk_position
```python
# Pick every 2nd element first, then every 2nd chunk
print(list(chunked(data, size=2, nth_position=2, chunk_position=2, apply_nth_before_chunk=True)))
# → [[5, 7]]
```

---

### 🔹 chunk_position then nth_position
```python
# Chunk normally, keep every 2nd chunk, then take 2nd element from each
print(list(chunked(data, size=2, chunk_position=2, nth_position=2, apply_nth_before_chunk=False)))
# → [[4], [8]]
```
crispy-bootstrap5 2025.6
Bootstrap5 template pack for django-crispy-forms
License: MIT
Requires Python: >=3.8

# crispy-bootstrap5

[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/smithdc1/crispy-bootstrap5/blob/main/LICENSE)

Bootstrap5 template pack for django-crispy-forms

## Installation

Install this plugin using `pip`:
```bash
$ pip install crispy-bootstrap5
```

## Usage

You will need to update your project's settings file to add ``crispy_forms``
and ``crispy_bootstrap5`` to your projects ``INSTALLED_APPS``. Also set
``bootstrap5`` as and allowed template pack and as the default template pack
for your project

```python
INSTALLED_APPS = (
    ...
    "crispy_forms",
    "crispy_bootstrap5",
    ...
)

CRISPY_ALLOWED_TEMPLATE_PACKS = "bootstrap5"

CRISPY_TEMPLATE_PACK = "bootstrap5"
```

## What's new?

Bootstrap 5 introduces [floating labels](https://getbootstrap.com/docs/5.0/forms/floating-labels/).
This template pack include a layout object to use this input type

```python
from crispy_bootstrap5.bootstrap5 import FloatingField

# then in your Layout
... Layout(
    FloatingField("first_name"),
)
```

Accordions also have new features, such as [Accordion flush](https://getbootstrap.com/docs/5.0/components/accordion/#flush) and [Always open](https://getbootstrap.com/docs/5.0/components/accordion/#always-open).
There is a new layout object to use them

```python
from crispy_bootstrap5.bootstrap5 import BS5Accordion

# then in your Layout
# if not informed, flush and always_open default to False
... Layout(
    BS5Accordion(
        AccordionGroup("group name", "form_field_1", "form_field_2"),
        AccordionGroup("another group name", "form_field"),
        flush=True,
        always_open=True
    )
)
```

Support is added for [Switches](https://getbootstrap.com/docs/5.2/forms/checks-radios/#switches). Switches are a custom 
checkbox rendered as a toggle switch. The widget for these fields should be
a [CheckboxInput](https://docs.djangoproject.com/en/4.2/ref/forms/widgets/#django.forms.CheckboxInput).

```python
from crispy_bootstrap5.bootstrap5 import Switch

... Layout(Switch("is_company"))
```


## Development

To contribute to this library, first checkout the code. Then create a new virtual environment:

```bash
cd crispy-bootstrap5
python -m venv venv
source venv/bin/activate
```

Or if you are using `pipenv`:
```bash
pipenv shell
```

Now install the dependencies and tests:
```bash
pip install -e '.[test]'
```

To run the tests:
```bash
pytest
```
tls-client2 1.1
Advanced Python HTTP Client.
License: MIT

# Python-TLS-Client
Python-TLS-Client is an advanced HTTP library based on requests and tls-client.

# Installation
```
pip install tls-client2
```

# Disclaimer
This is a fork of FlorianREGAZ [tls-client](https://github.com/FlorianREGAZ/Python-Tls-Client). <br>
I created this fork because in the original repository the binaries were not updated and bugs remained open for too long.

# Usage
The project description can be found in the original repository. <br>
[https://github.com/FlorianREGAZ/Python-Tls-Client](https://github.com/FlorianREGAZ/Python-Tls-Client)