semvec/pypi-packages huggingface dataset:
tronclipy 0.0.1
tronclipy library for Python
License: MIT

## How to use

```python
from tronpy import Tron
from tronpy.keys import PrivateKey

client = Tron(network='nile')
# Private key of TJzXt1sZautjqXnpjQT4xSCBHNSYgBkDr3
priv_key = PrivateKey(bytes.fromhex("8888888888888888888888888888888888888888888888888888888888888888"))

txn = (
    client.trx.transfer("TJzXt1sZautjqXnpjQT4xSCBHNSYgBkDr3", "TVjsyZ7fYF3qLF6BQgPmTEZy1xrNNyVAAA", 1_000)
    .memo("test memo")
    .build()
    .inspect()
    .sign(priv_key)
    .broadcast()
)

print(txn)
# > {'result': True, 'txid': '5182b96bc0d74f416d6ba8e22380e5920d8627f8fb5ef5a6a11d4df030459132'}
print(txn.wait())
# > {'id': '5182b96bc0d74f416d6ba8e22380e5920d8627f8fb5ef5a6a11d4df030459132', 'blockNumber': 6415370, 'blockTimeStamp': 1591951155000, 'contractResult': [''], 'receipt': {'net_usage': 283}}
```

### Async Client

```python
import asyncio

from tronpy import AsyncTron
from tronpy.keys import PrivateKey

# private key of TMisHYBVvFHwKXHPYTqo8DhrRPTbWeAM6z
priv_key = PrivateKey(bytes.fromhex("8888888888888888888888888888888888888888888888888888888888888888"))

async def transfer():
    async with AsyncTron(network='nile') as client:
        print(client)

        txb = (
            client.trx.transfer("TJzXt1sZautjqXnpjQT4xSCBHNSYgBkDr3", "TVjsyZ7fYF3qLF6BQgPmTEZy1xrNNyVAAA", 1_000)
            .memo("test memo")
            .fee_limit(100_000_000)
        )
        txn = await txb.build()
        print(txn)
        txn_ret = await txn.sign(priv_key).broadcast()
        print(txn_ret)
        # > {'result': True, 'txid': 'edc2a625752b9c71fdd0d68117802860c6adb1a45c19fd631a41757fa334d72b'}
        print(await txn_ret.wait())
        # > {'id': 'edc2a625752b9c71fdd0d68117802860c6adb1a45c19fd631a41757fa334d72b', 'blockNumber': 10163821, 'blockTimeStamp': 1603368072000, 'contractResult': [''], 'receipt': {'net_usage': 283}}

if __name__ == '__main__':
    asyncio.run(transfer())
```

Or close async client manually:

```python
from httpx import AsyncClient, Timeout
from tronpy.providers.async_http import AsyncHTTPProvider
from tronpy.defaults import CONF_NILE


async def transfer():
    _http_client = AsyncClient(limits=Limits(max_connections=100, max_keepalive_connections=20),
                               timeout=Timeout(timeout=10, connect=5, read=5))
    provider = AsyncHTTPProvider(CONF_NILE, client=_http_client)
    client = AsyncTron(provider=provider)
    print(client)

    priv_key = PrivateKey(bytes.fromhex("8888888888888888888888888888888888888888888888888888888888888888"))
    txb = (
        client.trx.transfer("TJzXt1sZautjqXnpjQT4xSCBHNSYgBkDr3", "TVjsyZ7fYF3qLF6BQgPmTEZy1xrNNyVAAA", 1_000)
        .memo("test memo")
        .fee_limit(100_000_000)
    )
    txn = await txb.build()
    print(txn)
    txn_ret = await txn.sign(priv_key).broadcast()

    print(txn_ret)
    print(await txn_ret.wait())
    await client.close()

if __name__ == '__main__':
    asyncio.run(transfer())
```
chatGPT-automator 0.1.21
Regarding automating ChatGPT using Selenium in Python
License: MIT
Requires Python: >=3.6

# ChatGPT Automator
Regarding automating ChatGPT using Selenium in Python, it's an intriguing approach that combines the power of conversational AI with web automation tools. ChatGPT, as we know, is a state-of-the-art language model by OpenAI, capable of producing human-like text based on the input it receives. On the other hand, Selenium is a widely used tool for controlling web browsers through programs and performing browser automation. It's primarily used for automating web applications for testing purposes, but it's versatile enough for various other tasks as well.

By integrating ChatGPT with Selenium in a Python environment, one can potentially automate various web-based tasks. For instance, it might be possible to build a system where ChatGPT can interact with web platforms, fill forms, retrieve information, or even interact with users on web interfaces autonomously. This fusion can pave the way for more interactive and dynamic web applications, especially when they are AI-driven.

Such an integration would require a deep understanding of both ChatGPT's capabilities and Selenium's features. Given the potential applications and the synergy between conversational AI and web automation, this could be a promising area of exploration for developers and enthusiasts alike.

## Instructions

1. Install:
```
pip install chatGPT-automator
```
<br />

2. How to initialize:
```python
from chatGPT_automator import ChatGPTAutomator

chatgpt = ChatGPTAutomator()


```

login_check (bool):

Specifies whether to check for a successful login when initializing the ChatGPT session. If set to True, the automator will verify that the login was successful before proceeding with any further actions. The default value is True.

<br />

3. How to interact with ChatGPT:
```python

question = "How ChatGPT Ignited the A.I. Competition Wave"

chatgpt.send_prompt_to_chatgpt(question)

# wait a moment ...

answer = chatgpt.return_last_response()

print(answer)

```
optigatrust 1.5.1
A ctypes based Python wrapper for the OPTIGA™ Trust M Host Library for C
License: MIT
Requires Python: >=3.5
Keywords: ECDHE ECDSA RSA ECC X509 NISTP256 NIST384 OPTIGA TRUST TRUSTX TRUSTM

[![PyPI](https://img.shields.io/pypi/v/optigatrust.svg)](https://pypi.org/project/optigatrust/)

# Infineon OPTIGA™ Trust M Host Library for Python

A [ctypes](https://docs.python.org/3/library/ctypes.html) based Python wrapper for the [OPTIGA™ Trust M Host Library for C](https://github.com/Infineon/optiga-trust-m).

The source code of this Python package is available in the [OPTIGA™ Trust M Host Library for Python](https://github.com/Infineon/python-optiga-trust) GitHub repository.

## Features

This Python module is a wrapper for the [OPTIGA™ Trust M Host Library for C](https://github.com/Infineon/optiga-trust-m) and allows the communication with OPTIGA™ Trust M devices.

Please see the [OPTIGA™ Trust M Overview Repository](https://github.com/Infineon/optiga-trust-m-overview) for more information on our OPTIGA™ Trust M product family.
 
## Installation

```bash
$ python -m pip install optigatrust
```

### libusb: Allow access to USB device (USB-to-UART-interface)

If you want to use the `optigatrust` Python package with libusb and a USB-to-UART-interface from user space, the access has to be permitted with a udev rule.

#### Automatic installation of the udev rule (root permission needed)

When the package installation is performed with root permissions, it will install the udev rule for the OPTIGA™ Trust M Perso2Go board automatically.

```bash
$ sudo python -m pip install optigatrust
```

#### Manual installation of the udev rule

For manually installing the udev rule, please consult the README.md in our [OPTIGA™ Trust M Host Library for Python](https://github.com/Infineon/python-optiga-trust) GitHub repository.

## Documentation

The documentation of this Python module can be found here:
* [Online documentation on GitHub.io](https://infineon.github.io/python-optiga-trust)
* [Source code documentation on GitHub](https://github.com/Infineon/python-optiga-trust)

## OPTIGA™ Trust M product information

Please find more information about the OPTIGA™ Trust M product family on the [OPTIGA™ Trust M Overview Repository](https://github.com/Infineon/optiga-trust-m-overview).

## Source code and examples

Please find the source code and examples for this Python module on the [OPTIGA™ Trust M Host Library for Python](https://github.com/Infineon/python-optiga-trust) GitHub repository.

## Licensing

This project is published under the MIT license and with copyright of Infineon Technologies AG. For more details, see the [OPTIGA™ Trust M Host Library for Python](https://github.com/Infineon/python-optiga-trust) GitHub repository.
log2doc 0.1.0
A package to log Linux/Windows command history and generate documentation using Gemini AI.
License: MIT
Requires Python: >=3.6

# Linux Command Logger

A Python package to extract recent Linux/Windows commands from the command history and explain them concisely. The explanations are fetched from the Gemini API.

## Installation

You can install the package via pip:

```bash
pip install linux-command-logger
linux-command-logger 0.1.0
A package to log Linux/Windows command history and generate documentation using Gemini AI.
License: MIT
Requires Python: >=3.6

# Linux Command Logger

A Python package to extract recent Linux/Windows commands from the command history and explain them concisely. The explanations are fetched from the Gemini API.

## Installation

You can install the package via pip:

```bash
pip install linux-command-logger