semvec/pypi-packages huggingface dataset:
multiversx-sdk-network-providers 1.0.0
Deprecated. Instead, use multiversx-sdk.
Requires Python: >=3.8

[![No Maintenance Intended](http://unmaintained.tech/badge.svg)](http://unmaintained.tech/)

This project is deprecated. All the functionality has been moved to the new [repository](https://github.com/multiversx/mx-sdk-py).

The migration guide as a GitHub issue can be found [here](https://github.com/multiversx/mx-sdk-py/issues/41).
multiversx-sdk-wallet 1.0.0
Deprecated. Instead, use multiversx-sdk.
Requires Python: >=3.8

[![No Maintenance Intended](http://unmaintained.tech/badge.svg)](http://unmaintained.tech/)

This project is deprecated. All the functionality has been moved to the new [repository](https://github.com/multiversx/mx-sdk-py).

The migration guide as a GitHub issue can be found [here](https://github.com/multiversx/mx-sdk-py/issues/41).
multiversx-sdk-core 1.0.0
Deprecated. Instead, use multiversx-sdk.
Requires Python: >=3.8

[![No Maintenance Intended](http://unmaintained.tech/badge.svg)](http://unmaintained.tech/)

This project is deprecated. All the functionality has been moved to the new [repository](https://github.com/multiversx/mx-sdk-py).

The migration guide as a GitHub issue can be found [here](https://github.com/multiversx/mx-sdk-py/issues/41).
ezusergen 0.1.3
A simple username generator that combines random words with numbers
Requires Python: >=3.6

# Usergen

`ezusergen` is a simple Python package that generates usernames by combining random words and a random number.

## Installation

```bash
pip install ezusergen
```

```python
#Usage
import ezusergen as gen

username = gen.generate(7) # 7 = word length, default (if left blank) = 7
print(username)  # Example: SeedmanWelding532

# You can also just generate usernames without numbers now by using it like this:
username2 = gen.generate(7, noNum=True)
print(username2) # Example: SeedmanWelding
```
audiotoken 0.3.1
A package for creating audio tokens
Requires Python: >=3.10

# Audiotoken

Tokenize audio to get acoustic and semantic tokens.

## Installation

```bash
pip install audiotoken
```

## Usage

### Encoding

You can either use an acoustic or semantic encoder to encode audio and get tokens.

```python
from pathlib import Path
from audiotoken import AudioToken, Tokenizers
encoder = AudioToken(tokenizer=Tokenizers.acoustic, device='cuda:0')
encoded_audio = encoder.encode(Path('path/to/audio.wav'))
```

There are 1 acoustic and 2 semantic tokenizers available:

1. `Tokenizers.acoustic`
2. `Tokenizers.semantic_s` (Small)
3. `Tokenizers.semantic_m` (Medium)

### Decoding

You can decode acoustic tokens like this:

```python
from pathlib import Path
from audiotoken import AudioToken, Tokenizers

tokenizer = AudioToken(tokenizer=Tokenizers.acoustic, device='cuda:0')
encoded_audio = tokenizer.encode(Path('path/to/audio.wav'))
decoded_audio = tokenizer.decode(encoded_audio)

# Save the decoded audio and compare it with the original audio
import torch
import torchaudio
torchaudio.save(
    'reconstructed.wav',
    decoded_audio,
    sample_rate=24000
)
```

You can decode semantic tokens like this:

```python
from pathlib import Path
from audiotoken import AudioToken, Tokenizers

semantic_tokenizer = AudioToken(tokenizer=Tokenizers.semantic_s, device='cuda:0')
semantic_toks = semantic_tokenizer.encode(Path('path/to/audio.wav'))
decoded_audio = semantic_tokenizer.decode(semantic_toks)

# Save the decoded audio and compare it with the original audio
import torch
import torchaudio
torchaudio.save(
    'reconstructed.wav',
    decoded_audio,
    sample_rate=24000
)
```

See [examples/usage.ipynb](examples/usage.ipynb) for more usage examples.

## APIs

Core class

```python
from audiotoken import AudioToken, Tokenizers
tokenizer = AudioToken(tokenizer=Tokenizers.semantic_m, device='cuda:0')
```

See [audiotoken/core.py](audiotoken/core.py) for complete documentation of APIs.

There are 3 APIs provided:

1. `tokenizer.encode`: Encode single audio files/arrays at a time
2. `tokenizer.encode_batch_files`: Encode multiple audio files in batches and save them to disk directly
   1. **NOTE**: `encode_batch_files` is not safe to run multiple times on the same list of files as it can result in incorrect data.
   This will be fixed in a future release.
3. `tokenizer.decode`: Decode acoustic/semantic tokens
fck-aws-sso 0.2.5
A tool to automate AWS SSO login
Requires Python: <4.0,>=3.10

# A CLI tool to automate AWS SSO login. It uses selenium with chrome under the hood.

### 1. Install with `pipx`

```
pipx install fck-aws-sso
```

### 2. Run first time with `--no-headless`

You need that to save your browser user data. `BROWSER=true` is hack so aws sso won't open browser. Browser will be opened by `fck-aws-sso`.

```
BROWSER=true aws sso login | fck-aws-sso --no-headless
```

### 3. Add to `.bashrc` or `.zshrc`

```
BROWSER=true aws sso login | fck-aws-sso
```

### 4. Forget that you ever had to login to AWS SSO manually.

## How it works

Script reads `aws sso login` output from stdin and parses it. Then it opens chrome with user data dir and navigates to AWS SSO login page. After that it fills the form and submits it. Finally it waits for aws sso to confirm login and then it closes chrome. There is default headless mode so you won't see anything. If you want to see what's going on you can use `--no-headless` option. It will open chrome and you will see what's going on.

## Prerequisites

You need `google-chrome` installed and in your `PATH`.