Metadata-Version: 2.1
Name: tilt
Version: 0.0.5
Summary: A python language binding for the Transparency Information Language and Toolkit (TILT)
Home-page: https://github.com/Transparency-Information-Language/python-tilt
Author: Elias Grünewald
Author-email: gruenewald@tu-berlin.de
License: UNKNOWN
Description: # python-tilt | Transparency Information Language and Toolkit
        
        ## What is the Transparency Information Language and Toolkit?
        With this proposed schema for transparency information with regards to data privacy, an essential step towards a sophisticated ecosystem shall be made by introducing a transparency enhancing toolkit based on a formal language model describing transparency information in the context of multi-service environments and latest legal requirements (EU General Data Protection Regulation). The desired results of the work should be suitable as ready-to-use privacy engineering solutions for developers and serve as a starting point for further research in this area. Eventually, data subjects should (be able to) understand what happens to data relating to them by using the interfaces of the toolkit.
        
        ## What is python-tilt?
        *tilt* is a Python based language binding for the _Transparency Information Language and Toolkit_.
        
        ## Installation
        Install the python client library using pip. See the [project page](https://pypi.org/project/tilt/).
        
        
        ```console
        foo@bar:~$ pip3 install tilt
        Collecting tilt
          Using cached tilt-0.0.1-py3-none-any.whl (22 kB)
        Installing collected packages: tilt
        Successfully installed tilt-0.0.1
        ```
        
        ## Basic usage
        
        See here for an interactive playground [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Transparency-Information-Language/python-tilt/master?filepath=python-tilt-example.ipynb), in which you can run python-tilt in a Juypter notebook.
        
        
        1) Import the transparency information language binding/library.
        2) Create your first object, e.g. a Data Protection Officer with their contact details.
        3) Continue creating your objects, i.e. a Controller and its Representative.
        4) ... (add all other fields, not shown in here) ...
        
        
        ```python
        from tilt import tilt
        
        dpo = tilt.DataProtectionOfficer(name='Max Ninjaturtle', address='21 Jump Street', country='DE', email='jane@mycompany.com', phone='0142 43333')
        print(dpo.to_dict())
        # {'address': '21 Jump Street', 'country': 'DE', 'email': 'jane@mycompany.com', 'name': 'Max Ninjaturtle', 'phone': '0142 43333'}
        
        
        r = tilt.ControllerRepresentative(name='Maxi Müller', email='maxi@mail.com', phone=None)
        c = tilt.Controller(name='MyCompany', address='Straße des 17. Juni', country='DE', division='Main', representative=r)
        print(c.to_dict())
        # {'address': 'Straße des 17. Juni', 'country': 'DE', 'division': 'Main', 'name': 'MyCompany', 'representative': {'email': 'maxi@mail.com', 'name': 'Maxi Müller', 'phone': None}}
        ```
        
        ## Import existing documents
        In order to import exisiting tilt documents (we call them instances), you can use your favorite HTTP client or load from your local disk. Then you can use the native python objects and do any manipulations as you like.[](http://)
        
        
        ```python
        import json
        import requests
        
        file = requests.get('https://raw.githubusercontent.com/Transparency-Information-Language/schema/master/tilt.json')
        instance = tilt.tilt_from_dict(json.loads(file.content))
        
        print(instance.controller.to_dict())
        # {'address': 'Wolfsburger Ring 2, 38440 Berlin', 'country': 'DE', 'division': 'Product line e-mobility', 'name': 'Green Company AG', 'representative': {'email': 'contact@greencompany.de', 'name': 'Jane Super', 'phone': '0049 151 1234 5678'}}
        
        for element in list(instance.data_disclosed):
            for recipient in element.recipients:
                print(recipient.category)
        # Marketing content provider
        # Responsible Statistical Institutes
        
        
        instance.controller.name = 'Yellow Company Ltd.'
        print(instance.controller.to_dict())
        # {'address': 'Wolfsburger Ring 2, 38440 Berlin', 'country': 'DE', 'division': 'Product line e-mobility', 'name': 'Yellow Company Ltd.', 'representative': {'email': 'contact@greencompany.de', 'name': 'Jane Super', 'phone': '0049 151 1234 5678'}}
        ```
        
        ## Create new documents from scratch
        In the example below we are using standard libraries (e.g. sha256 or datetime) in order to create formatted strings. All objects have `from_dict()` and `to_dict()` functions which help you to build or export them.
        
        
        ```python
        from hashlib import sha256
        from datetime import datetime
        
        result = {}
        result["_hash"] = sha256('<insert hashable content here>'.encode('utf-8')).hexdigest()
        result["_id"] = '<your-id-01>'
        result["created"] = '2020-10-02T22:08:12.510696'
        result["language"] = 'en'
        result["modified"] = datetime.now().isoformat()
        result["name"] = 'Green Compancy SE'
        result["status"] = 'active'
        result["url"] = 'https://greencompany.implementation.cloud'
        result["version"] = 42
        
        meta = tilt.Meta.from_dict(result)
        
        print(meta)
        # <tilt.tilt.Meta object at 0x7fef287928d0>
        
        print(meta.to_dict())
        # {'_hash': 'bd8f3c314b73d85175c8ccf15b4b8d26348beca96c9df39ba98fa5dda3f60fcc', '_id': '<your-id-01>', 'created': '2020-10-02T22:08:12.510696', 'language': 'en', 'modified': '2020-07-27T15:14:35.689606', 'name': 'Green Compancy SE', 'status': 'active', 'url': 'https://greencompany.implementation.cloud', 'version': 42}
        ```
        
        ## Validate documents
        See the following example code on how to validate documents using [fastjsonschema](https://horejsek.github.io/python-fastjsonschema/).
        
        ```python
        import fastjsonschema
        import json
        
        import requests
        
        # Load schema to validate against
        file = requests.get('https://raw.githubusercontent.com/Transparency-Information-Language/schema/master/tilt-schema.json')
        schema = json.loads(file.content)
        
        # Load instance/document to validate;
        # you may use your own tilt object with .to_dict() here
        file = requests.get('https://raw.githubusercontent.com/Transparency-Information-Language/schema/master/tilt.json')
        instance = json.loads(file.content)
        
        # Compile schema
        validate_func = fastjsonschema.compile(schema)
        
        # Validate instance against schema
        validate_func(instance)
        ## {'meta': {'_id': 'f1424f86-ca0f-4f0c-9438-43cc00509931', 'name': 'Green Company', 'created': '2020-04-03T15:53:05.929588', 'modified': '2020-04-03T15:53:05.929588',...
        ## => document is valid
        
        
        # Load another example
        file = requests.get('https://raw.githubusercontent.com/Transparency-Information-Language/schema/master/tilt-NOT-valid.json')
        instance = json.loads(file.content)
        
        # Validate another example
        validate_func(instance)
        ## JsonSchemaException: data.controller must contain ['name', 'address', 'country', 'representative'] properties
        ## => document is invalid
        ```
        
        
        ## Author
        Elias Grünewald
        
        ## License
        [MIT License](LICENSE)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
