semvec/pypi-packages huggingface dataset:
holy-bible-api 1.0.9
A Python client library for the Holy Bible API
Requires Python: >=3.9

# Holy Bible API Python Client

A Python client library for accessing the Holy Bible API with full type support.

## Installation

```bash
pip install holy_bible_api
```

## Usage

### Basic Usage

```python
from holy_bible_api import create_bible_api

# Create an API client
api = create_bible_api()

# Make API calls
bibles = api.get_bibles()
```

### With Type Hints

```python
from holy_bible_api import (
    create_bible_api,
    DefaultApi,
    Bible,
    BibleVerse,
    GetBiblesRes,
    GetBibleVersesRes,
)

# Create a typed API client
api: DefaultApi = create_bible_api()

# Get bibles with type hints
bibles_response: GetBiblesRes = api.get_bibles()
bible: Bible = bibles_response.data[0]

# Get verses with type hints
verses_response: GetBibleVersesRes = api.get_bible_verses(
    bible_id=bible.id,
    book=1,
    chapter=1
)
verse: BibleVerse = verses_response.data[0]
print(f"{verse.book}:{verse.chapter}:{verse.verse} - {verse.text}")
```

### Custom Host

```python
from holy_bible_api import create_bible_api

# Use a custom API host
api = create_bible_api(url="https://custom-host.com")
```

## Available Types

The following types are exported for use:

### API Classes
- `DefaultApi` - Main API client
- `ApiClient` - Low-level HTTP client
- `Configuration` - API configuration
- `ApiResponse` - API response wrapper

### Models
- `Bible` - Bible metadata
- `BibleVerse` - Bible verse data
- `AudioBible` - Audio bible metadata
- `GetBiblesRes` - Response for getting bibles
- `GetBibleVersesRes` - Response for getting verses
- `GetBibleBooksRes` - Response for getting books
- `GetBibleChaptersRes` - Response for getting chapters
- `GetAudioBiblesRes` - Response for getting audio bibles
- `GetAudioBooksRes` - Response for getting audio books
- `GetAudioChaptersRes` - Response for getting audio chapters

### Exceptions
- `OpenApiException` - Base exception
- `ApiTypeError` - Type error
- `ApiValueError` - Value error
- `ApiKeyError` - Key error
- `ApiAttributeError` - Attribute error
- `ApiException` - General API exception

## Type Checking

This package includes `py.typed` marker file for full type checking support with mypy, pyright, and other type checkers.

## License

[Your License Here]
hypestat 0.0.1
A Python package to fetch website statistics from Hypestat.com
Requires Python: >=3.10

# hypestat

A Python package to fetch website statistics from [Hypestat.com](https://hypestat.com).

## Overview

`hypestat` provides a simple interface to scrape and retrieve comprehensive website statistics from Hypestat.com, including traffic data, rankings, revenue estimates, and visitor information.

## Installation

```bash
pip install hypestat
```

## Features

- Fetch website statistics including:
  - Global rank
  - Percentage of global internet users
  - Daily impressions
  - Visitor countries
  - Daily revenue estimates
  - Estimated website value
  - Daily visitors
  - Monthly visits
- Automatic update of outdated statistics
- Session-based requests for efficient data fetching

## Usage

### Basic Example

```python
from hypestat import HypeStat

# Create an instance
hs = HypeStat()

# Get statistics for a domain
stats = hs.get_stats("example.com")

# Access the statistics
print(f"Global Rank: #{stats.rank}")
print(f"Daily Visitors: {stats.daily_visitors}")
print(f"Monthly Visits: {stats.monthly_visits}")
print(f"Daily Revenue: ${stats.daily_revenue}")
print(f"Estimated Value: ${stats.estimated_value}")
print(f"Global Internet Users: {stats.global_internet_users}%")
print(f"Daily Impressions: {stats.impressions}")
print(f"Visitor Countries: {', '.join(stats.visitor_countries)}")
```

## API Reference

### `HypeStat` Class

Main class for interacting with Hypestat.com.

#### Methods

- **`get_stats(domain: str) -> Stats`**
  
  Fetches and returns comprehensive statistics for the specified domain. Automatically attempts to update statistics if they're outdated.
  
  - **Parameters:** `domain` - The domain name to fetch statistics for (e.g., "example.com")
  - **Returns:** `Stats` object containing all website statistics

- **`update_stats(domain: str) -> bool`**
  
  Manually triggers a statistics update for a domain if the data is outdated.
  
  - **Parameters:** `domain` - The domain name to update
  - **Returns:** `True` if update was initiated, `False` if statistics are current or update unavailable

### `Stats` Class

Data class holding website statistics.

#### Attributes

- **`rank`** (int): Global rank of the website
- **`global_internet_users`** (float): Percentage of global internet users
- **`impressions`** (int): Number of daily impressions
- **`visitor_countries`** (list[str]): List of visitor countries
- **`daily_revenue`** (float): Daily revenue estimate in USD
- **`estimated_value`** (float): Estimated value of the website in USD
- **`daily_visitors`** (int): Number of daily visitors
- **`monthly_visits`** (int): Number of monthly visits

## License

This project is licensed under the GPLv3 License - see the LICENSE file for details.

## Disclaimer

This package scrapes data from Hypestat.com. Please be respectful of their terms of service and use this tool responsibly. The accuracy of the data depends on Hypestat.com's own data collection and estimation methods.
ser-metric-bin 12.0.3
This is the implementation of Slope Error Rate in python and written by Arsalan Rahman Mirza for more detail you can contact me with my second email address ersalen@gmail.com
Requires Python: >=3.8

to install write

pip install ser_metric_bin

to use write

import ser_metric
result = ser_metric.ser(0.3, 0.7)



Slope Error Rate (SER)

A Python implementation of Slope Error Rate (SER) — a novel performance evaluation metric for binary classification, designed to provide improved sensitivity and robustness under class imbalance, particularly for biometric authentication systems.

Overview

Slope Error Rate (SER) is a distance-based evaluation metric that quantifies the trade-off between False Acceptance Rate (FAR) and False Rejection Rate (FRR) across decision thresholds. Unlike traditional metrics such as Equal Error Rate (EER), which rely on a single operating point, SER captures error dynamics and provides a more informative assessment of classifier behavior.

SER is especially useful in applications where:

Data is highly imbalanced

False positives and false negatives have asymmetric costs

Threshold sensitivity matters

A lower SER value indicates better overall performance.

Key Features

Designed for binary classification

Robust under class imbalance

Threshold-sensitive evaluation

Based on FAR–FRR geometry

Lightweight and easy to integrate

Suitable for biometrics, spoof detection, anomaly detection, and security systems
hypestat-simplylu 0.0.1
A Python package to fetch website statistics from Hypestat.com
Requires Python: >=3.10

# hypestat

A Python package to fetch website statistics from [Hypestat.com](https://hypestat.com).

## Overview

`hypestat` provides a simple interface to scrape and retrieve comprehensive website statistics from Hypestat.com, including traffic data, rankings, revenue estimates, and visitor information.

## Installation

```bash
pip install hypestat
```

## Features

- Fetch website statistics including:
  - Global rank
  - Percentage of global internet users
  - Daily impressions
  - Visitor countries
  - Daily revenue estimates
  - Estimated website value
  - Daily visitors
  - Monthly visits
- Automatic update of outdated statistics
- Session-based requests for efficient data fetching

## Usage

### Basic Example

```python
from hypestat import HypeStat

# Create an instance
hs = HypeStat()

# Get statistics for a domain
stats = hs.get_stats("example.com")

# Access the statistics
print(f"Global Rank: #{stats.rank}")
print(f"Daily Visitors: {stats.daily_visitors}")
print(f"Monthly Visits: {stats.monthly_visits}")
print(f"Daily Revenue: ${stats.daily_revenue}")
print(f"Estimated Value: ${stats.estimated_value}")
print(f"Global Internet Users: {stats.global_internet_users}%")
print(f"Daily Impressions: {stats.impressions}")
print(f"Visitor Countries: {', '.join(stats.visitor_countries)}")
```

## API Reference

### `HypeStat` Class

Main class for interacting with Hypestat.com.

#### Methods

- **`get_stats(domain: str) -> Stats`**
  
  Fetches and returns comprehensive statistics for the specified domain. Automatically attempts to update statistics if they're outdated.
  
  - **Parameters:** `domain` - The domain name to fetch statistics for (e.g., "example.com")
  - **Returns:** `Stats` object containing all website statistics

- **`update_stats(domain: str) -> bool`**
  
  Manually triggers a statistics update for a domain if the data is outdated.
  
  - **Parameters:** `domain` - The domain name to update
  - **Returns:** `True` if update was initiated, `False` if statistics are current or update unavailable

### `Stats` Class

Data class holding website statistics.

#### Attributes

- **`rank`** (int): Global rank of the website
- **`global_internet_users`** (float): Percentage of global internet users
- **`impressions`** (int): Number of daily impressions
- **`visitor_countries`** (list[str]): List of visitor countries
- **`daily_revenue`** (float): Daily revenue estimate in USD
- **`estimated_value`** (float): Estimated value of the website in USD
- **`daily_visitors`** (int): Number of daily visitors
- **`monthly_visits`** (int): Number of monthly visits

## License

This project is licensed under the GPLv3 License - see the LICENSE file for details.

## Disclaimer

This package scrapes data from Hypestat.com. Please be respectful of their terms of service and use this tool responsibly. The accuracy of the data depends on Hypestat.com's own data collection and estimation methods.