semvec/pypi-packages huggingface dataset:
boring-math-recursive-functions 1.0.0
Recursive Functions Package
Requires Python: >=3.13
Keywords: ackermann, fibonacci, recursive, recursive functions

Boring Math - Recursive Functions
=================================

PyPI project
`boring-math-recursive-functions
<https://pypi.org/project/boring-math-recursive-functions>`_.

The purpose of this project is to explore different ways to efficiently
implement recursion in Python.

Computable recursive functions can be defined with previously defined or even
not yet defined values. Functions defined using previously well defined values
having "base cases" are called "primitively recursive functions." Not all
computable functions are primitively recursive.

This pypi project is part of the
`boring math
<https://grscheller.github.io/boring-math>`_ projects.

Documentation
-------------

Documentation for this project is hosted on
`GitHub Pages
<https://grscheller.github.io/boring-math/recursive-functions/development/build/html>`_.

Copyright and License
---------------------

Copyright (c) 2023-2025 Geoffrey R. Scheller. Licensed under the Apache
License, Version 2.0. See the LICENSE file for details.
boring-math-probability-distributions 0.8.1
Visualize probability distributions
Requires Python: >=3.13
Keywords: distribution, probability distributions, sample data

Boring Math - Probability Distributions
=======================================

PyPI project
`boring-math-probability-distributions
<https://pypi.org/project/boring-math-probability-distributions>`_.

Package to generate and visualize probability distributions.

- continuous distributions:

  - Normal: ``boring_math.probability_distributions.normal``
  - Uniform: ``boring_math.probability_distributions.uniform``

- discrete distributions:

  - Binomial: ``boring_math.probability_distributions.binomial``

This pypi project is part of the
`boring math
<https://grscheller.github.io/boring-math>`_ projects.

Documentation
-------------

Documentation for this project is hosted on
`GitHub Pages
<https://grscheller.github.io/boring-math/probability-distributions/development/build/html/>`_.

Copyright and License
---------------------

Copyright (c) 2023-2025 Geoffrey R. Scheller. Licensed under the Apache
License, Version 2.0. See the LICENSE file for details.
mcp-ads-sdk 0.1.0
Ad monetization SDK for Model Context Protocol servers
Requires Python: >=3.8
Keywords: mcp, model-context-protocol, ads, monetization, ai

# mcpadserver

Ad monetization SDK for Model Context Protocol (MCP) servers.

## Installation

```bash
pip install mcpadserver
```

## Quick Start

```python
from mcpadserver import AdClient
from mcp.server import Server
from mcp.types import TextContent

app = Server("my-server")
ad_client = AdClient(api_key="your_api_key")

@app.call_tool()
async def get_data(query: str):
    # Your main data logic
    data = fetch_data(query)

    # Request contextual ad
    ad = await ad_client.request_ads(context=f"query: {query}")

    # Return as MCP content blocks
    return [
        TextContent(type="text", text=f"Data: {data}"),
        TextContent(
            type="text",
            text=f"📢 Sponsored by {ad['sponsor']}\n{ad['content']}\n{ad['link']}"
        )
    ]
```

## Features

- 🔌 **MCP-Native**: Drop-in SDK for MCP servers
- 🔒 **Privacy-Safe**: No cookies, no tracking, contextual only
- 💰 **70/30 Split**: Publishers keep 70% of revenue
- 📊 **Real-time Analytics**: Track impressions, clicks, and earnings
- ⚡ **5-Minute Setup**: Start earning immediately

## Documentation

Visit [mcpadserver.com/docs](https://mcpadserver.com/docs) for full documentation.

## License

MIT License - see LICENSE file for details.
autohack-next 1.1.0
highly customizable competitive programming Hack tool written in Python.
Requires Python: >=3.10
Keywords: competitive-programming, hack, automation

# autohack-next

> English | [简体中文](./docs/README_zh.md)

A highly customizable competitive programming Hack tool written in Python.

A completely refactored version of [autohack](https://github.com/gi-b716/autohack) with clearer configuration, a redesigned interface, and more powerful performance.

## Installation

autohack-next is published as a package on PyPI. Install it using a Python package manager, or you can download pre-built binary files to run. Development (pre-release) versions are published to TestPyPI.

## Usage

Run the following command:

```bash
python -m autohack
```

or

```bash
autohack
```

On the first run, it will generate a `.autohack` folder in the current directory and exit.

After adjusting the settings in `.autohack/config.json`, run it again to start using.

## Build

See [release.yml](./.github/workflows/release.yml)

## Custom Checker

You can use custom checkers in the `checker.name` configuration option.

`autohack-next` will read files named `{checker.name}.py` from the `.autohack/checkers` folder.

Custom checker files need an activate function that receives the argument list (i.e., the `checker.args` configuration option) and returns a checker function.

The checker function needs to accept input, output, answer, and argument list, and return a tuple. The tuple contains a boolean value (true when Accepted) and a string (the checker output).

Optionally, a custom checker may also provide a `deactivate` function which accepts the same `checker.args` dictionary and returns `None`; this can be used for cleanup or post-processing.

Formally, your function signatures should be as follows:

```python
# autohack/core/checker.py

from typing import Callable, TypeAlias

checkerType: TypeAlias = Callable[[bytes, bytes, bytes, dict], tuple[bool, str]]
activateType: TypeAlias = Callable[[dict], checkerType]
deactivateType: TypeAlias = Callable[[dict], None]
```

There are several built-in checkers available.

### builtin_basic

Compares output with answer text-wise, ignoring trailing spaces at line ends and final newlines.

#### Arguments for builtin_basic

None.

### builtin_always_ac

For testing purposes, always returns Accepted.

#### Arguments for builtin_always_ac

None.

### builtin_testlib

Support for [testlib](https://github.com/MikeMirzayanov/testlib/).

#### Arguments for builtin_testlib

##### compiler

Compiler path used to compile the checker.

Default: `g++`

##### checker

Checker filename.

Default: `checker.cpp`

##### compile_args

Compilation arguments.

Default: `[]`