semvec/pypi-packages huggingface dataset:
falcon-marshmallow 0.3.0
Automatic Marshmallow (De)serialization in Falcon
Keywords: ihiji,falcon,marshmallow,marshalling,middleware,serialization,deserialization,json,wsgi


Falcon-Marshmallow is a middleware library designed to assist
developers who wish to easily incorporate automatic (de)serialization
using Marshmallow schemas into their Falcon application. Once
the middleware is in place, requests to any resources that have
a ``schema`` attribute defined will automatically use that schema
to parse the request body. In addition, responses for that resource
will automatically use the defined schema to dump results.

You may also specify method-specific schemas on a resource, e.g.
``patch_schema``, which will be used only when the request method
matches the schema prefix.

By default, this middleware will also automatically parse requests
and responses to JSON even if they do not have any schema(s) defined.
This can be easily disabled, if you would prefer to use your own JSON
parsing middleware. This is done using ``simplejson`` by default,
but you may specify any module or object you like that implements
the public interface of the standard library ``json`` module.
subscene2 1.0.2
A Python wrapper for SubScene
Requires Python: >=3.6

# Python wraper for SubScene(.)com

We are working on developing an api for Subscene(.)com. And making the code more managable.
Before using in production please be sure it works well.

### Usage:

CLI:
```
Use: -n 'name' -y 'year' -l 'language' [Optional]
    Usage:
        -h or --help | Show this help message
        -n or --name | Name of the movie/media
        -y or --year | Year of release
        -l or --lang | Language of desired subtitle
```

Script:
```python3
from subscene.SubScene import SubScene

sub = SubScene() # Initialize the api Class
detail = {
    'name': 'Hello',
    'year': '2008'
    }
link = sub.getDetail(detail) # Available Subtitles
print(link)
links = sub.getSubLink(link) # Link to Specific Subtitle
print(links)
down = sub.getDownLink(links[0]) # DownLoad link for Specific Language
print(down)
```

Making with love by [Rakibul Yeasin](https://github.com/dreygur) and [Abdullah Zayed](https://github.com/xaadu)
wikitablewrapper 0.2.6
Parsing, Proccesing, Annotating and Storing WikiTables in Json
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, <4
Keywords: NIF parser table NLP

# wikitablewrapper


**Install virtual ennvironment of python3**
```sh
sudo apt-get install curl
sudo apt install python3-pip
sudo apt install virtualenv
virtualenv env --python=python3
cd env && source bin/activate
```

**Install dependencies**
```sh
pip3 install simplejson
pip3 install xmltodict
```

**Install locally DBpedia Spotlight**
Ubuntu
```sh
sudo snap install docker
```
or Debian
```sh
wget https://download.docker.com/linux/debian/dists/jessie/pool/stable/amd64/docker-ce_17.03.0~ce-0~debian-jessie_amd64.deb
sudo dpkg -i docker-ce_17.03.0~ce-0~debian-jessie_amd64.deb
```

See if you have the image already in your computer
```sh
sudo docker image ls
```
if you don't have it, then run
```sh
sudo docker pull dbpedia/spotlight-english
sudo docker run -d -p 2222:80 dbpedia/spotlight-english spotlight.sh
```

If you have to stop it, see the CONTAINER ID, and then do it
```sh
sudo docker container ls
sudo docker stop CONTAINER_ID
```
test it
> curl http://localhost:2222/rest/annotate   -H "Accept: application/json"   --data-urlencode "text=Brazilian state-run giant oil company Petrobras signed a three-year technology and research cooperation agreement with oil service provider Halliburton."   --data "confidence=0.3"   --data "support=20"

**To install this package, just run:**
```sh
pip3 install -i https://test.pypi.org/simple/ wikitablewrapper
```


# How use it?


```python
wt = WikitableWrapper(20)
wt.createHtmlFile = True

wt.includeBabelfy = True
wt.includeTagme = True
wt.includeFremeNer = True
wt.includeDBpediaSpotlightLocal = True

# you can do, either
wt.outputFolder="1Out"  # Optional
wt.processJson("1Tablas/1003231_2.json")

# or
wt.ProcessFolderOfJson("100Tablas","100Out")
```

See below an example of how use the Benchamrk class

```python
wb = WikitableBenchmark()
dSys = {"Babelfy":"_babelfy", "TagME":"_tagme", "FremeNER":"_fremener", "DBpedia Spotlight":"_dbpst"}
wb.MeasureF1_and_Summarize("100Tablas","100Out", dSys, "100Benchmark")
```