semvec/pypi-packages huggingface dataset:
agiverse-py 0.0.1
AGIverse Python SDK
Requires Python: >=3.8

# agiverse-py

agiverse-py is the Python SDK for AGIverse.

## Smart Building

Smart building is a programmable building in AGIverse. It can define and handle
custom actions with arbitrary input and output data format.

## Installation

Since the SDK is not yet published to PyPI, you can install it by cloning the repository.
We will publish it to PyPI soon.

```bash
git clone https://github.com/agiverse/agiverse-py.git
```

## Getting Started

Initialize a smart building client:

```python
import agiverse

building = agiverse.SmartBuilding(api_key='xxx', building_id=xxx)
```

Register event handlers:

```python
@building.event
async def on_ready():
    print(f"Smart building {building.building_id} is ready to use")
```

Register action handlers:

```python
@building.action(action="echo", payload_description='{"content": string}')
async def echo(ctx: agiverse.ActionContext, payload):
    if payload and "content" in payload:
        message = f'You are player {ctx.player_id}.'
        message += f' You said "{payload["content"]}".'
        message += f' There are {len(ctx.building.players)} players in the building now.'
        await ctx.send_result(message)
    else:
        await ctx.send_result({"error": "You didn't say anything!"})
```

Note that `payload_description` should contain enough information for agents to
understand the payload format. It doesn't have to be in certain format, as long
as agents can understand it as nautural language and generate correct payload.
Think of it as the comments and docs for your API, agents read it and decide
what parameters to use. For example:

```
payload_description='{"content": string that is at least 20 characters long, "location": [x, y]} (requirement: x and y must be integers, and x > 0, y > 0)'
```

Start the smart building:

```python
building.run()
```
asc2csv 1.4.1
A Python package for converting EyeLink .asc files to structured .csv files.
Requires Python: >=3.6


# asc2csv

**asc2csv** is a Python package developed for converting EyeLink `.asc` files into structured `.csv` files, facilitating the analysis of eye-tracking data. It extracts gaze data and event details such as blinks, saccades, and fixations, organizing them into an easy-to-use format.

## Features
- Converts EyeLink `.asc` files to `.csv` format efficiently.
- Extracts and processes blink (`EBLINK`), saccade (`ESACC`), and fixation (`EFIX`) event data.
- Aligns timestamps relative to trial start for consistent temporal analysis.
- Handles missing data by combining event and sample data fields where applicable.

## **Changelog**

<details>
  <summary>See the Changes in versions</summary>

### **Version 1.4**
- Initial release of `asc2csv`.
- V 1.4 Update 12/11/24   make adding `header=True` in conversion optional. By default `header=True` is applied.

### **Version 1.4.1**
- Enhanced data importing

</details>


## Installation

To install the package, run:

```bash
pip install asc2csv
```

## Usage

Import the package and use the `process_asc_file()` function:

```python
import asc2csv as convert

convert.process_asc_file('input_file.asc', 'output_file.csv')
```

### Parameters
- **`input_file_path`** (str): Path to the input `.asc` file.
- **`output_csv_path`** (str): Path to save the output `.csv` file.
- **`header`** (bool, optional): Whether to include a header row in the output CSV. Default is `True`.

## Requirements
- Python >= 3.6
- `pandas`

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.

## Contributing

Contributions are welcome! If you find a bug or have an idea for an improvement, please submit a pull request or open an issue.

## Creator and Maintainer

**Mohammad Ahsan Khodami**  
- Personal Site: [khodami.site](https://khodami.site)  
- Google Scholar: [Profile](https://scholar.google.com/citations?user=WCqPnS4AAAAJ&hl=en)  
- Email: [ahsan.khodami@gmail.com](mailto:ahsan.khodami@gmail.com)

## Acknowledgments
- The EyeLink system and data format are provided by SR Research.
crypto-cpp-py 1.4.5
This is a packaged crypto-cpp program
Requires Python: >=3.8

Crypto-cpp-py
=============
A python packaged `crypto-cpp <https://github.com/software-mansion-labs/crypto-cpp/tree/master>`_ library, that can be used for hashing and signing messages in starknet.


Dependencies
------------
- ecdsa,
- sympy,
- pywin32 (Windows only),
- cmake [optional, for building package from sdist; can be installed with `pip install crypto-cpp-py[build]`]

|

Changelog
=========

Version 1.4.5 (2024-11-20)
--------------------------

* Update `sympy <https://pypi.org/project/sympy/>`_ version to 1.12.1

Version 1.4.4 (2024-01-30)
--------------------------

* Add support for Python 3.12

Version 1.4.0 (2023-05-12)
--------------------------

* Add support for Windows

Version 1.3.1 (2023-04-27)
--------------------------

* Add support for Python 3.11

Version 1.3.0 (2023-04-20)
--------------------------

* Remove cairo-lang dependency
* Require ecdsa, sympy