semvec/pypi-packages huggingface dataset:
oidc-register 0.2.1
OpenID Connect Dynamic Client Registration tool

oidc-register
=============

`OpenID Connect <https://openid.net/connect/>`_ Dynamic Client Registration tool.

.. image:: https://img.shields.io/pypi/v/oidc-register.svg?style=flat
  :target: https://pypi.python.org/pypi/oidc-register

This utility should work with any standards compliant OpenID Connect provider.

It has been tested with:

* `Ipsilon <https://ipsilon-project.org/>`_
persian-phonemizer 0.4.0
A tool for translating Persian text to IPA (International Phonetic Alphabet)A small example package
Requires Python: >=3.6

# persian_phonemizer
A tool for translating Persian text to IPA (International Phonetic Alphabet).

In Persian, one written word can have different pronunciations and different meanings according to the pronunciation. 
This library helps with disambiguation of such words.

A few examples of use cases of this library are:
* Input for TTS systems
* Helping people in learning Persian
* Adding pronunciation for Persian words in texts of other languages

## Installation

```
pip install persian_phonemizer
```

## Usage

Fast start:

```
>>> from persian_phonemizer import Phonemizer
>>> phonemizer = Phonemizer()
>>> phonemizer.phonemize("آن مرد مرد.")
'ʔɒːn mæɾd moɾd .'
>>> phonemizer.phonemize("دوچرخه جدید علی گم شد.")
'dovtʃʰæɾxeje dʒædiːde ʔæliː ɡom ʃod .'
```

you can set the package to output Persian text with eraab instead of IPA:

```
>>> phonemizer = Phonemizer(output_format='eraab')
>>> phonemizer.phonemize("آن مرد مرد.")
'آن مَرد مُرد .'
```
## What's inside?

- A database containing words, part-of-speech, pronunciation and meaning according to Moen dictionary
    - script for parsing Dehkhoda dictionary is available in the dataset directory. Still, the results are not used in the package because some pronunciations are outdated and will do more harm than good.
- A Part-of-Speech tagger and a Dependency Parser trained on [Universal Dependencies](https://universaldependencies.org/) dataset using [spaCy](https://spacy.io/)
- A Grapheme to Phoneme model using a seq-to-seq neural network implemented in Pytorch. More info is provided in [g2p_fa](https://github.com/de-mh/g2p_fa) repo.
These assets were created to be used in this repo but each one has the ability to be used separately.

## How does it work?

This package uses several approaches for finding the proper pronunciation. 
1. Input text gets normalized and tokenized
2. Root word for each word in input is calculated using a lemmatizer to cover complex verbs and nouns
3. Each word is looked up for pronunciations in the database.
    - If there is no pronunciation available, pronounce is predicted using [g2p_fa](https://github.com/de-mh/g2p_fa).
    - If there is one pronunciation, that one is used.
    - If there is more than one pronunciation, the correct one is chosen based on the Part-of-Speech tag for that word.
4. Suffix and prefix pronunciations are added for each word
5. Add `e` or `je` between words when needed using the dependency parser
tikapipy 1.1.7
An api-wrapper for https://tiktok.jiroawesome.tech/.
Requires Python: >=3.6

# tikapipy

- An api-wrapper for https://tiktok.jiroawesome.tech/.

## Installation

```
pip install tikapipy
```

## Example

### XSS_STUB

```python
from tikapipy import TikApi
api = TikApi(key='') # api key
payload = "payload"
print(api.xss_stub(payload=payload)) # res: int
```

### X-GORGON

```python
from tikapipy import TikApi
api = TikApi(key='') # api key
url = "url"
coolies = "cookies"
print(api.x_gorgon(url=url, cookies=cookies)) # res: str
```

### X-KHRONOS

```python
from tikapipy import TikApi
api = TikApi(key='') # api key
url = "url"
coolies = "cookies"
print(api.x_khronos(url=url, cookies=cookies)) # res: int
```

### DEVREG (X-LOG + X-APP-LOG)

```python
from tikapipy import TikApi
api = TikApi(key='') # api key
print(api.devreg()) # res: json
```

### X-LADON

```python
from tikapipy import TikApi
api = TikApi(key='') # api key
print(api.xladon()) # res: str
```

## API-KEY

- DM Virtuality.#6670 on Discord to purchase an api-key.
sfsutils 1.1.1
A KSP SFS savefile parser
Requires Python: >=3.7

# sfsutils

A KSP SFS savefile parser

## Install

`pip install sfsutils`

## Usage

Example:
```python
import sfsutils
data = sfsutils.parse_savefile("saves/persistent.sfs")
# edit data
sfsutils.writeout_savefile(data, destination_file="saves/edited.sfs")
```
All documentation is in the docstrings of each function.

Available functions are (see docstrings for more info):
* parse_savefile - Parses an SFS file from stream or file
* writeout_savefile - Writes out the parsed data back into the SFS format

## Notes

The parsing order of this library is deterministic, but note that this guarantee is provided by Python dictionaries sorting keys by the order of insertion (this is the case since Python 3.6).


There is a Cython implementation of this module.
With the Cython implementation, parsing is about 4x as fast, and serialisation is about 2x as fast. The Cython backend will automatically be built and selected if Cython is installed along with a working C compiler at the time when this library is installed. If Cython is not available or the build otherwise fails, the pure Python backend will be installed instead.

The backend in use can be checked with sfsutils.BACKEND (possible values: "Python", "Cython").

## License

GPLV3