semvec/pypi-packages huggingface dataset:
whosper 0.1.0
A Whisper-based Automatic Speech Recognition package
Requires Python: >=3.7

```bash
  pip install git+https://github.com/sudoping01/whosper.git
```

```python
from whosper import WhosperTranscriber

# Initialize the transcriber
transcriber = WhosperTranscriber(model_id = "CAYTU/whosper-large-v2") 

# Transcribe an audio file
result = transcriber.transcribe_audio("path/to/your/audio.wav")
print(result)
coral8 0.6.0
Zero-config file loader & simple HTTP bridge
Requires Python: >=3.8

 **coral8** is a zero-config CLI tool that lets you register, inspect, and inject data or code files in Python projects. It’s minimal, modular, and built for local workflows.

---

##  Features

- `coral8 bridge` — register any `.csv`,`.xlsx`,`.yaml`, `.json`, or `.txt` file
- `coral8 peek` — preview the data via command line
- `coral8 graft` — copy Python functions across `.py` files safely via AST
- `coral8 vault` — see what you’ve registered
- `--alias` support — avoid filename collisions with ease
- `coral8 scrub all` - declutter your coral8 space

Coral8 is not a data parser. It’s the layer that makes parsing possible.

Modern projects rely on multiple file formats—CSV, JSON, YAML, TXT, and more. But bridging them across tools, scripts, and notebooks often leads to:

Redundant loaders for each format

Hardcoded paths scattered across files

Confusion over which data files are in use

Coral8 provides a consistent interface to register, manage, and access data files across your entire project.

Use Coral8 to:
Register multiple files from different formats in one step

Safely alias filenames to avoid collisions

Preview connected files directly from the command line

Load registered files into Python with consistent logic

Inject shared functions across .py files using AST-based replacement

Plays well with:
Data analysis tools like pandas, polars, or dask

Machine learning pipelines with mixed input sources

Jupyter notebooks and research workflows

Lightweight CLI-based ETL pipelines
---

##  Installation

You can now install **coral8** directly from PyPI:

```bash
pip install coral8

---

##  Example

python

from coral8.loader import parse_file

sales = parse_file("sales_2022.csv")
config = parse_file("model.yaml")
logdata = parse_file("clickstream.json")

# Use with pandas, or pass directly into other tooling
Once a file is registered, Coral8 handles the rest—no boilerplate, no guesswork.
net-task-client 0.1.4
A nornir net task project
Requires Python: >=3.9
Keywords: network, task, client

# net-task-client

net_task_client is a network task client using nornair to run tasks on multiple devices.

## To Install

```
py -m pip install net-task-client
Please create the following files to run the client.
Example config, hosts, groups, defaults are included with the git package.

~/
├── defaults.yml
├── groups.yml
├── hosts.yml
├── config.yml

```

## Usage
Please make sure you update the inventory file hosts.yml with your settings.
```
import net_task_client
client = net_task_client.TaskHandler()
output = client.run('show version')
client.print_output(output)
```
qiskit-emulator-helper 0.1.2
A helper library to easily find, propose, and get Qiskit's fake backends (emulators).
Requires Python: >=3.8

# Qiskit Emulator Helper

A utility library for easily **searching, recommending, and retrieving fake backends / emulators** from `qiskit-ibm-runtime`.

## Installation

To install the library from the local source code, clone the repository and run `pip`:

```bash
pip install -e .
```

Alternatively, users can install it via:

```bash
pip install qiskit-emulator-helper
```

## Usage

After installation, you can import and use the library with the following name:

```python
import qiskit_emulator_helper as qeh

# 1. List all available emulators
print("--- Listing all available emulators ---")
qeh.show_available_backends()

# 2. Recommend an emulator for a 7-qubit circuit
print("\n--- Proposing an emulator for 7 qubits ---")
qeh.propose_backends(num_qubits=7)

# 3. Retrieve a specific emulator by name
print("\n--- Getting the 'fake_manila' emulator ---")
try:
    backend = qeh.get_backend_by_name('fake_manila')
    print(f"Successfully retrieved: {backend.name}")
    print(f"Number of qubits: {backend.target.num_qubits}")
except ValueError as e:
    print(e)
```