Metadata-Version: 2.1
Name: fhir2dataset
Version: 0.1.2
Summary: Transform FHIR to Dataset
Home-page: https://github.com/arkhn/FHIR2Dataset
Author: Lucile Saulnier
Author-email: contact@arkhn.com
License: Apache License 2.0
Description: # FHIR2Dataset
        
        Transform FHIR to dataset for ML applications
        
        ## FHIR2Dataset in Detail
        
        This repo allows to make a SQL query on a FHIR API and to retrieve tabular data.
        
        _FHIR2Dataset is still under active development!_
        
        ## Installation
        
        ### With pip
        
        `pip install fhir2dataset`
        
        ### From source
        
        After cloning this repository, you can install the required dependencies
        
        ```
        pip install -r requirements.txt
        npm install --prefix ./fhir2dataset/metadata
        ```
        
        For usage, refer to this [turorial](https://htmlpreview.github.io/?https://github.com/arkhn/FHIR2Dataset/blob/query_tests/examples/tutorial.html) and then this [Jupyer Notebook](examples/example.ipynb)
        
        ## Getting started
        
        Two possible ways to enter the query : as a SQL query or as a JSON config file
        
        **SQL query as entry**
        
        ```
        from fhir2dataset import Query, FHIRRules, FHIR2DatasetParser
        
        fhir_api_url = 'http://hapi.fhir.org/baseR4/'
        fhir_rules = FHIRRules(fhir_api_url=fhir_api_url)
        query = Query(fhir_api_url, fhir_rules=fhir_rules)
        parser = FHIR2DatasetParser()
        ```
        
        ```
        sql_like_query = "SELECT (alias n°1).a, (alias n°1).b, (alias n°1).c, (alias n°2).a FROM (Resource type 1) as (alias n°1)
        INNER JOIN (Resource type 2) as (alias n°2)
        ON (alias n°1).d = (alias n°2)
        INNER JOIN (Resource type 3) as (alias n°3)
        ON (alias n°2).b = (alias n°3) WHERE (alias n°2).c = "value 1"
        AND (alias n°2).d = "value 2"
        AND (alias n°3).a = "value 3"
        AND (alias n°3).b = "value 4""
        ```
        
        ```
        config_from_parser = parser.parse(sql_like_query)
        query.from_config(config_from_parser)
        query.execute()
        df = query.main_dataframe
        ```
        
        **JSON config file as entry**
        
        ```
        from fhir2dataset.query import Query
        from fhir2dataset.fhirrules_getter import FHIRRules
        
        fhir_api_url = 'http://hapi.fhir.org/baseR4/'
        fhir_rules = FHIRRules(fhir_api_url=fhir_api_url)
        query = Query(fhir_api_url, fhir_rules=fhir_rules)
        ```
        
        config.json :
        
        ```json
        {
            "select": {
                "alias n°1": ["a", "b", "c"],
                "alias n°2": ["a"]
            },
            "from": {
                "alias n°1": "Resource type 1",
                "alias n°2": "Resource type 2",
                "alias n°3": "Resource type 3"
            },
            "join": {
                "inner": {
                    "alias n°1": {
                        "d": "alias n°2"
                    },
                    "alias n°2": {
                        "b": "alias n°3"
                    }
                }
            },
            "where": {
                "alias n°2": {
                    "c": "value 1",
                    "d": "value 2"
                },
                "alias n°3": {
                    "a": "value 3",
                    "b": "value 4"
                }
            }
        }
        ```
        
        ```
        # Enter in dirname the path of config.json
        filename_config = 'config.json'
        
        with open(os.path.join(dirname, filename_config)) as json_file:
            config = json.load(json_file)
        
        query.from_config(config)
        query.execute()
        df = query.main_dataframe
        ```
        
        ## Examples
        
        Check out examples of queries and how they are transformed in call to the FHIR api!
        
        -   [Select the gender and name for patients born after 2000](examples/example1.md)
        -   [Get clinical information about patients that were in intensive care unit because of Coronavirus](examples/example2.md)
        
        ## Contributing
        
        The following commands on a terminal and in your virtual environment allow you to do some minimal local testing before each commit:
        
        ```
        pip install -r requirements-dev.txt
        pre-commit install
        ```
        
        If you ever want to delete them you just have to do:
        
        ```
        pre-commit clean
        ```
        
        ## Publish
        
        First, you need to have `twine` installedd
        
        ```
        pip install --user --upgrade twine
        ```
        
        Make sure you have bumped the version number in `setup.py`, then run the following:
        
        ```
        python setup.py sdist bdist_wheel
        python -m twine upload dist/*
        ```
        
Keywords: arkhn,medical,fhir,FHIR,Dataset,API
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
