semvec/pypi-packages huggingface dataset:
looking 0.0.1
A smart log viewer
Requires Python: >=3.7

# What

`looking` is a smart log viewer.

# How

1. Install `pip install looking`
2. Use `looking /path/to/log/file.txt`
3. Other options:

   a. `looking -f /path/to/log/file.txt` to follow the appended text, just like `tail -f`.

   b. `looking -` to read standard input, just like `vim -`. e.g. `grep SOME_ID /path/to/log/file.txt | looking -`.

# Features

- `looking` highlights common keywords for programming languages, as well as user registered keywords for visual highlights.
- `looking` makes viewing large objects of key-value pairs, or a long list of values easier.
- `looking` smartly filters and parallelizes log lines for multi-thread logs.
- `looking` makes copy/pasting from logs easier.
dsl-dict-analyser 0.0.6
A Python package for analysing dsl dictionaries. Dsl dictionary is a dict type for lingvo app.
Requires Python: >=3.6

# dsl_dict_analyser

A Python package for analysing dsl dictionaries. Dsl dictionary is a dict type for lingvo app.

## Installation

You can install the package using pip:

```bash
pip install dsl_dict_analyser
```
## Usage

```python

from dsl_dict_analyser import read
# Read the DSL dictionary file
dsl_dict = read("path/to/dsl_dict.txt")
# then your can read the dsl_dict
# like dsl_dict.cards
# or dsl_dict.name
```
## Changelog

### 0.0.1 (2024-12-11)
-  Initial release

### 0.0.2-4 (2024-12-11)
- add ci/cd
- fix some language dict bug.(deu dict name format error)

### 0.0.5 (2024-12-26)
- fix a p bug

### 0.0.6 (2024-12-26)
- deu and jap language word divide
seros 0.1.1
A Python module for finding prime numbers using the Sieve of Eratosthenes
Requires Python: >=3.6

# Seros

**Seros** is a simple Python package that contains useful functions for prime number generation and feature scaling.

## Features

- `soe`: Sieve of Eratosthenes for finding prime numbers up to a given number.
- `scale_features`: Scales numerical data using Z-score normalization or Min-Max scaling.

## Installation

To install the package, you can clone the repository or use pip if available.

### Using pip:

pip install seros
metatool 0.1.0
A Python interface for metatool functionality
Requires Python: >=3.9

# Metatool

A Python package that provides a simple interface to metatool functionality.

## Installation

```bash
pip install metatool
```

## Usage

```python
from metatool import MetaTool

# Initialize with configuration
metatool = MetaTool(
    openai_api_key="your-api-key",  # Optional: can also use environment variable
    model_name="gpt-4o-mini",     # Optional: defaults to gpt-4o-mini
    temperature=0.0,                  # Optional: defaults to 0.0
)

# Process instructions
response = metatool.run("Your instructions here")
print(response)
```

## Configuration Options

The `MetaToolConfig` class, which inherits from `BaseModel`, defines the following configuration options for MetaTool:

- `openai_api_key`: Optional[str] - Your OpenAI API key (default: None)
- `model_name`: str - The model to use (default: "gpt-4o-mini")
- `temperature`: float - Model temperature setting (default: 0.0)
- `verbose`: bool - Enable verbose output (default: False)
- `root_dir`: str - Root directory for MetaTool files (default: "./metatool_tmp")
- `api_key`: Optional[str] - API key for storage service (default: None)
- `database_path`: str - SQLite database path relative to root_dir (default: "metatool.db")

## Features

- Class-based interface with configuration options
- Simple method for processing instructions
- Customizable model and tool settings

## Requirements

- Python 3.9+
- Dependencies listed in setup.py
tengen 0.1.6
Generate string using template
Requires Python: >=3.13

# tengen
Generate string using template

## Concept
Use templates to simplify string replacement

**[done.tngn]**
```
{0} is done.
```

## What is possible
1. String replacement using templates

## Reason for development
- I want to make string replacement easier using templates

## Versions

|Version|Summary|
|:--|:--|
|0.1.6|Release tengen|

## Installation
### tengen
`pip install tengen`

## CLI
### render
Rendering using templates

#### 1. Prepare template file(done.tngn)
**[done.tngn]**
```
{0} is done.
```

#### 2. Rendering templates by CLI execution

```
render # <template name> <args>
  [With value]
    -o|--output  # Output file path
```
`tengen render done TENGEN`
```
TENGEN is done.
```
Vizura 0.1.10
Tool for Data Analysis
Requires Python: >=3.6

# Vizura


![Vizura Logo](https://raw.githubusercontent.com/ash-sha/vizura/refs/heads/main/logo.png)

![Build Status](https://img.shields.io/github/workflow/status/ash-sha/vizura/Python%20CI?label=build)
![PyPI Version](https://img.shields.io/pypi/v/vizura?logo=pypi)
![License](https://img.shields.io/pypi/l/vizura?logo=open-source)

Welcome to the **Vizura** package, a comprehensive tool for analyzing and visualizing basic statistics.

**Vizura** is a data analysis and visualization tool developed using Python and Streamlit. It provides valuable insights into datasets by generating summary statistics and offering interactive visualizations.

## Installation

To install Vizura, execute the following command:

```bash
pip install git+https://github.com/ash-sha/vizura.git #on Project Root directory
````
or  use the standard installation via PyPI:
```
pip install vizura
```

## Usage Example

```python
import vizura

# Example usage of Vizura
data = ...  # Load your dataset
vizura.numerical(data) # Generates a dashboard displaying summary statistics for numerical columns in the dataset.
vizura.categorical(data) # Displays a dashboard of summary statistics for categorical columns.
vizura.calculate_correlations(data) # Computes correlations between filtered numerical columns using Pearson, Kendall, and Spearman methods.
vizura.plot_correlation(data) # Visualizes the correlation matrices for Pearson, Kendall, and Spearman.
```

For a live demo and example statistics, you can explore the demo at: [https://vizura.streamlit.app](https://vizura.streamlit.app)

## Contributing

We welcome contributions to improve **Vizura**! To contribute:
1. Fork the repository
2. Create a new branch (`git checkout -b feature-name`)
3. Make your changes
4. Commit your changes (`git commit -am 'Add new feature'`)
5. Push to your branch (`git push origin feature-name`)
6. Create a pull request
onto_match 0.0.2
Check if RDF data aligns with an ontology.
Requires Python: <4.0,>=3.9

# onto-match

[![Release](https://img.shields.io/github/v/release/atomobianco/onto-match)](https://img.shields.io/github/v/release/atomobianco/onto-match)
[![Build status](https://img.shields.io/github/actions/workflow/status/atomobianco/onto-match/main.yml?branch=main)](https://github.com/atomobianco/onto-match/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/atomobianco/onto-match/branch/main/graph/badge.svg)](https://codecov.io/gh/atomobianco/onto-match)
[![Commit activity](https://img.shields.io/github/commit-activity/m/atomobianco/onto-match)](https://img.shields.io/github/commit-activity/m/atomobianco/onto-match)
[![License](https://img.shields.io/github/license/atomobianco/onto-match)](https://img.shields.io/github/license/atomobianco/onto-match)

A Python library for validating RDF data alignment with ontologies without requiring SHACL definitions.

- **Github repository**: <https://github.com/atomobianco/onto-match/>
- **Documentation** <https://atomobianco.github.io/onto-match/>

## Why onto-match?

When working with Large Language Models (LLMs) to extract RDF data based on ontologies, it's crucial to verify that the extracted data aligns correctly with the target ontology.
While tools like [pySHACL](https://github.com/RDFLib/pySHACL) exist for RDF validation, they:

- Require explicit SHACL shape definitions, which are not always available
- May fail on certain validation checks

This library provides a programmatic approach to verify ontology alignment, making it particularly suitable for:

- Validating LLM-extracted RDF data
- Working with ontologies that lack SHACL definitions
- Getting detailed violation reports for debugging and improvement

## Features

- Validate RDF data against ontology definitions without SHACL
- Detect undefined classes and properties
- Verify property domain and range constraints
- Provide detailed violation reports

## Installation

```bash
pip install onto-match
```

## Quick Start

```python
from rdflib import Graph
from onto_match import validate

# Load your ontology and data graphs
data = Graph().parse("your_data.ttl")
ontology = Graph().parse("your_ontology.ttl")

# Validate the data
is_valid, violations, report = validate(data, ontology)

if not is_valid:
    print(report)
```
code-animate 0.0.10
A package to animate your function call step by step in terminal
Requires Python: >=3.8


# code_animate
Allows you to animate your code step by step. 

Note - press Enter to conitnue to next step

# Installation
```
pip install code_animate
```

# Quickstart
```python
from code_animate import animate

@animate
def triangle(height: int) -> str:
    output: str = ""

    for i in range(height):
        num_stars: int = i + 1
        stars_str: str = "*" * num_stars
        output += stars_str + "\n"

    return output

print(triangle(4))

"""
def triangle(height: int) -> str:         
                                          
    output: str = ""                      {'height': 4, 'output': ''}
    for i in range(height):               
        num_stars: int = i + 1            {'i': 3, 'num_stars': 4}
        stars_str: str = "*" * num_stars  {'stars_str': '****'}
        output += stars_str + "\n"        {'output': '*\n**\n***\n****\n'}
    return output     
"""
```
dbine 0.1.6
Auxiliary tools related to databases
Requires Python: >=3.13

# dbine
Auxiliary tools related to databases

## Concept
PDF output from database table definitions

### Database table definitions(MySQL)
```sql
DROP DATABASE IF EXISTS db;
CREATE DATABASE db;

DROP USER IF EXISTS _user_;
CREATE USER _user_ IDENTIFIED BY 'pass';

GRANT ALL ON db.* TO _user_;

DROP TABLE IF EXISTS no_comments;
CREATE TABLE no_comments (
  id INT PRIMARY KEY,
  name VARCHAR(10)
) COMMENT 'コメントなしテーブル';

DROP TABLE IF EXISTS with_comments;
CREATE TABLE with_comments (
  id INT PRIMARY KEY COMMENT 'ID',
  name VARCHAR(10) COMMENT '名前'
) COMMENT 'コメントつきテーブル';

DROP TABLE IF EXISTS relations;
CREATE TABLE relations (
  id INT PRIMARY KEY COMMENT 'ID',
  no_comment_id INT COMMENT 'コメントなしテーブルのID',
  with_comment_id INT COMMENT 'コメントつきテーブルのID'
);
```

### PDF(PNG)
![](./images/database_mysql.png)

## What is possible
1. Log in to the database and get table definition information
2. Output table definition information as an ER diagram-like image in PDF
3. Convert PDF to image

## Reason for development
- I want to output the relationships between database table definitions as a PDF or image so that I can understand them at a glance

## Supported database types
- PostgreSQL
- MySQL
- SQLite

## Versions

|Version|Summary|
|:--|:--|
|0.1.6|Added SQLite to supported databases|
|0.1.4|Improved ease of use|
|0.1.3|Release dbine|

## Installation
### [dbine](https://pypi.org/project/dbine/)
`pip install dbine`

### [Graphviz](https://graphviz.org/download/)
Required for PDF output

### [Poppler](https://github.com/Belval/pdf2image?tab=readme-ov-file)
Required for PDF image conversion

## CLI
### pdf.write
Write database table definition to PDF

#### 1. Prepare database connection config file(database.yaml)
**[database.yaml]**
```yaml
Type: MySQL
DatabaseName: db
UserName: _user_
Password: pass
Host: localhost
Port: 0
```

#### 2. PDF write by CLI execution

```
pdf.write # <yaml file path> <pdf file path>
```
`dbine pdf.write database.yaml database.pdf`
```
database.pdf is done.
```

### pdf.convert
Convert PDF to image

#### 1. Image(PNG) conversion by CLI execution

```
pdf.convert # <pdf file path> <image file path>
```
`dbine pdf.convert database.pdf database.png`
```
database.png is done.
```
pingscope 0.1.6
Measuring and graphing ping
Requires Python: >=3.13

# pingscope
Measuring and graphing ping

## Concept
Returns the ping result as an integer value in milliseconds and outputs an image

### Ping result
```
#{"Dst": "www.google.com", "Count": 5}
12
11
11
12
11
#{"Avg": 12, "Min": 11, "Max": 12, "ElapsedTime": 5.056681200047024}
```

### PNG
![](./images/usage.png)

## What is ping
### Purpose
- Confirm communication with communication partner and measure response speed

### Command
`ping www.google.com -n 5`

### Result
```
www.google.com [x.x.x.x]に ping を送信しています 32 バイトのデータ:
x.x.x.x からの応答: バイト数 =32 時間 =10ms TTL=119
x.x.x.x からの応答: バイト数 =32 時間 =11ms TTL=119
x.x.x.x からの応答: バイト数 =32 時間 =11ms TTL=119
x.x.x.x からの応答: バイト数 =32 時間 =13ms TTL=119
x.x.x.x からの応答: バイト数 =32 時間 =13ms TTL=119

x.x.x.x の ping 統計:
    パケット数: 送信 = 5、受信 = 5、損失 = 0 (0% の損失)、
ラウンド トリップの概算時間 (ミリ秒):
    最小 = 10ms、最大 = 13ms、平均 = 11ms
```

## What is possible
1. Returns the ping execution result as an integer value in milliseconds
2. Output ping results as images

## Reason for development
- I would like to obtain the round trip time (hereinafter referred to as __RTT__), which is the ping result, as an integer value in milliseconds to make it easier to process
- I want to output RTT as an image so that I can understand it at a glance
- I want to express the stability of RTT using color

## RTT tiers
|Rank|Range|Color image|Color name|Color code|
|:-:|:-:|:-:|:-:|:-:|
|S|0 - 9ms|![](https://via.placeholder.com/16/0000ff/FFFFFF/?text=%20)|Blue|#0000FF|
|A|10 - 14ms|![](https://via.placeholder.com/16/a0d8ef/FFFFFF/?text=%20)|Skyblue|#87CEEB|
|B|15 - 19ms|![](https://via.placeholder.com/16/00ff00/FFFFFF/?text=%20)|Green|#00FF00|
|C|20 - 29ms|![](https://via.placeholder.com/16/ffff00/FFFFFF/?text=%20)|Yellow|#FFFF00|
|D|30 - 49ms|![](https://via.placeholder.com/16/ee7800/FFFFFF/?text=%20)|Orange|#FFA500|
|E|50ms over|![](https://via.placeholder.com/16/ff0000/FFFFFF/?text=%20)|Red|#FF0000|

## Versions

|Version|Summary|
|:--|:--|
|0.1.6|Release pingscope|

## Installation
### [pingscope](https://pypi.org/project/pingscope/)
`pip install pingscope`

## CLI
### ping
Execute ping and create image

#### 1. Image(PNG) conversion by CLI execution

```
ping # <ping file name> <dst>
  [With value]
    -c|--count     5  # Count
    -m|--max-count 30 # Max count
```
`pingscope ping google www.google.com`
```
google.ping is done.
google.png is done.
```