semvec/pypi-packages huggingface dataset:
wikitext-asymptote 0.0.4
Custom wikitext parser to produce html, plain text fields and relevant links from wikipedia page source code.
Requires Python: >=3.7

# Wikitext Asymptote
Custom wikitext parser to produce html, plain text fields and relevant links from wikipedia page source code.

## Get started
To install the `wikitext_asymptote` package, simply run 

    pip install wikitext_asymptote

You can then use the package as follows:

    import wikitext_asymptote as wa

    # Raw wikitext goes here
    page = """..."""
    
    # Parse it
    parsed_page = wa.parse_page(page)

    # parsed_page contains fields for html, plain text or links
    print(parsed_page)

    # parsed_page = {
    #     'html': '...',
    #     'text': '...',
    #     'opening_text': '...',
    #     'auxiliary_text': [...],
    #     'heading': [...],
    #     'links': [...]
    # }

## About
This package was created to fulfill the precise needs for parsing wikitext in the context of the [EPFL Graph](https://www.epfl.ch/about/facts/epfl-graph/) project, which are a bit more involved than the defaults from `mwparserfromhell`.

However, the task of parsing wikitext taking into account all its syntax is gigantic. Already deciding, not even implementing, the parsing of each template in the myriad that's available, with all its variations, is virtually unfeasible.

Hence, the approach we have decided to commit to is that of _approximation_ (hence [Asymptote](https://en.wikipedia.org/wiki/Asymptote)). We try to parse a number of templates, tags and other entities as correctly as possible, in a way that _most_ cases are covered. In addition, we also have defaults, which may or may not be adequate for some cases. This implies that the parsed output is not perfect, and that is by design. From that point on, we work on a case-by-case basis to include parsing for new templates, tags or other entities, should the need arise. 

## Acknowledgements
Wikitext asymptote is built on top of the [`mwparserfromhell`](https://github.com/earwig/mwparserfromhell) package, so we acknowledge and are grateful for the work of their creators.
omnicloud-airport 0.0.2
platform for interacting with omnicloud
Requires Python: >=3.10,<4.0
Keywords: omnicloud,supercloud,multicloud,cloud computing,migration


# Omnicloud.Airport


Omnicloud.Airport is a Python package for handling data transfer to and from cloud storage providers. It provides a set of classes that implement a common interface for working with cloud storage, making it easy to switch between providers and abstract classes for extending self.

<br/>


## Conception

### Terminal

It is an object that provides cloud related features to existing objects. For example:

- omnicloud.airport.terminals.Dict contains methods for processing dictionary;
- omnicloud.airport.terminals.Pickle - for handling a pickle object.

Every terminal is inherited fom his based object: Dict from dict, Pickle from pickle, so
you can use it in your code directly.

Each terminals contains one or more Gates.


### Gate

Gate is a object that interacts with single cloud.

- omnicloud.airport.terminals.Dict.GStorageJSON - with JSON files at the Google Cloud
Storage bucket;
- omnicloud.airport.terminals.Dict.LocalJSON - with local file.


### Addons

The omnicloud.airport is a platform additional terminals or gates can be installed
into that.

For more information please read [the developer docs](https://docs.omnicloud.world/projects/py-airport/development).


> ## Filling with objects
>
> The base package omnicloud.airport contains terminals for object from a pretty python only and gates for local files to theme.
>
> If you need more please install additional packages. For example omnicloud-airport-dict-gcs
> to get a gate to Google Cloud Storage for dictionary or omnicloud-airport-pydantic to get a
> terminal for pydantic.


## Installation & usage

```bash linenums="1"
pip3 install --upgrade omnicloud-airport
```

```py linenum=1
from omnicloud.airport.terminals import Dict

test_dict = {}
Dict(test_dict).departure('LocalJSON::/tmp::ensure_ascii=False', 'file_name.json')
```

The first argument of the method departure is a "waybill". The second is a filename.

The waybill is a specification for processing data in string format that contains three elements
separated by "::":

1) name of class that represented needs gate;

2) the place for saving to;

3) additional options in format "key=value||key=value||key=b64:..."; it is optional argument.


As a waybill well as filename can contains a part of path:

```py
Dict(test_dict).departure('LocalJSON::/tmp/a::ensure_ascii=False', 'file.json')
Dict(test_dict).departure('LocalJSON::/tmp::ensure_ascii=False', 'a/file.json')
```

Both command in the tutorial above save a data to file "/tmp/a/file.json"

For interaction with different storage (cloud provider) you have to change waybill in your config
or environment variable:

```bash
pip3 install omnicloud-airport-gcp
```

then

```py
Dict(test_dict).departure('GStorageJSON::gs://bucket::ensure_ascii=False||key_file=...', 'a/file.json')
```