semvec/pypi-packages huggingface dataset:
cmuseo 1.0.1
Perceptually uniform colormaps for scientific visualization
Requires Python: >=3.7

# cmuseo

**cmuseo** is a Python package that provides *perceptually uniform colormaps*, ensuring accurate gradients and accessible data interpretation for scientific visualization, with palette names reflecting the key colors of each colormap.

- **_vivian_** transitions smoothly from midnight *vi*olet through refreshing teal-green (*vi*ridian) to bright pale c*an*ary yellow, forming a vibrant palette well-suited for clear, engaging visualizations in data science and research.

- **_indira_** moves from deep *indi*go through plum purple and brilliant orange into light st*ra*w yellow, offering a luminous, warm palette ideal for visualizations requiring energy and contrast.

- **_elsa_** progresses from dark *el*derberry purple through deep blue and pastel *sa*pphire to frosty mint and pale jade, creating a cool, crystalline palette suited for visualizations with an icy aesthetic and arctic clarity.


![cmuseo colormaps preview](https://www.iup.uni-bremen.de/carbon_ghg/products/cmuseo/colormaps_preview.png)

## Features

- Unique RGB colormaps designed with perceptual uniformity in mind  
- Easy integration with `matplotlib`  
- Openly licensed under GNU GPL v3.0  

## Installation

```bash
pip install cmuseo
```

## Usage

### Basic usage

```python
import cmuseo
```

### Example: Previewing colormaps

```python
import matplotlib.pyplot as plt
import numpy as np
import cmuseo

colormaps = ['vivian', 'indira', 'elsa']

fig, axs = plt.subplots(len(colormaps), 1, figsize=(8, 0.8*len(colormaps)))

gradient = np.linspace(0, 1, 256).reshape(1, -1)

for ax, cmap_name in zip(axs, colormaps):
    ax.imshow(gradient, aspect='auto', cmap=cmap_name)
    ax.text(-0.02, 0.5, cmap_name, va='center', ha='right', transform=ax.transAxes)
    ax.set_axis_off()

plt.tight_layout()
plt.show()
```
redis-sizer 1.0.0
A simple command-line tool for analyzing memory usage across keys in a Redis database.
Requires Python: >=3.11

# redis-sizer

A simple command-line tool for analyzing memory usage across keys in a Redis database.

![Sample output](https://raw.githubusercontent.com/mienxiu/redis-sizer/refs/heads/main/docs/sample_output.jpg)

redis-sizer can help with the following problems:
- Optimize caching strategy.
- Gain insights into memory usage at different namespace levels.
- Identify which parts of your application consume the most memory.

## Installation

Install via pip:

```bash
pip install redis-sizer
```

## Usage

Run redis-sizer by specifying the Redis host along with any desired options:

```bash
redis-sizer [OPTIONS] HOST
```

Options:

- `--port`: Port number [default: 6379]
- `--db`: DB number [default: 0]
- `--password`: Password [default: None]
- `--socket-timeout`: Socket timeout in seconds [default: 10]
- `--socket-connect-timeout`: Socket connect timeout in seconds [default: 10]
- `--pattern`: Pattern to filter keys [default: *]
- `--sample-size`: Number of keys to sample [default: None]
- `--namespace-separator`: Separator for key namespaces [default: :]
- `--memory-unit`: Memory unit for display in result table [default: B]
- `--max-leaves`: Maximum number of leaf keys to display per namespace [default: 5]
- `--batch-size`: Batch size for scanning and calculating memory usage [default: 1000]

### Aggregating Memory Usage by Key Groups

Many applications using Redis adopt hierarchical key naming conventions.
For example, if your keys follow a colon-delimited format (e.g., `users:logs:...`, `users:profiles:...`), they can be visualized as a nested or tree-like structure:

```
DB
├── users:
│   ├── logs:
│   │   └── ...
│   └── profiles:
│       └── ...
...
```

redis-sizer leverages this hierarchical structure to aggregate and analyze memory usage, and displays aggregated statistics for each namespace level.

## Considerations

- Since data can change during analysis, the final result may not accurately reflect the database’s state at the beginning of the process.
- For databases with large collections of keys, consider using the `--sample-size` option to balance processing time with accuracy. If `--sample-size` is not specified, redis-sizer will perform perform a full scan.
- Increasing `--batch-size` can reduce network overhead. However, this can increase the load on the Redis server without providing meaningful performance improvements and, in some cases, may even lead to server blocking. Adjust these values carefully based on your server’s capacity.

## Redis Version Compatibility

- This tool relies on the Redis [`MEMORY USAGE`](https://redis.io/docs/latest/commands/memory-usage/) command, which has been available since version 4.0.0.
- It has been tested and verified to work with Redis versions 4, 5, 6, and 7.

## Dependencies

redis-sizer depends on:

- [redis-py](https://github.com/redis/redis-py): to communicate with the Redis database.
- [typer](https://github.com/fastapi/typer): to build CLI application, with output formatting supported by [rich](https://github.com/Textualize/rich)
custombox 0.1.3
Custom tkinter dialog box with flexible buttons and commands
Requires Python: >=3.6

hello and welcome to the custombox module, in this module you can add custom messages
with custom commands and buttons, so your not forced on only "Ok", "Cancel", "Yes", "No"
and the others, you can put it all custom!

also download tismiy at https://scratch.mit.edu/projects/1103965827/fullscreen/ for FREE