Metadata-Version: 2.1
Name: opdm-api
Version: 0.0.5
Summary: ENTSO-E OPDM client SOAP API implementation in python
Home-page: https://github.com/Haigutus/OPDM
Author: Kristjan Vilgo
Author-email: kristjan.vilgo@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: requests
Requires-Dist: zeep
Requires-Dist: urllib3
Requires-Dist: lxml
Requires-Dist: aniso8601

# OPDM
Python implementation of OPDM SOAP API. OPDM is used to exchange Electrical Grid Models between ENTSO-E TSO-s and RSC-s

# Installation

    pip install opdm-api

or

    pip install --user opdm-api

or 

    python -m pip install --user opdm-api


# Usage

## Initialise
    import opdm-api

    service = opdm-api.create_client("https://opdm.elering.sise:8443", username="user", password="pass")

## Upload File
### Upload a file
    response = service.publication_request(file_path_or_objet)

### Upload all files in a directory
    import glob
    imort os

    for file_name in glob.glob1(direcotry_path, "*.zip"):
        service.publication_request(os.path.join(direcotry_path, file_name))

## Get File Upload/Publication Report
    publication_report = get_profile_publication_report(model_ID)

or

    publication_report = get_profile_publication_report(filename="uploaded_file_name.zip")

## Subscribe for Model publications
### Get available Publications
    available_publications = service.publication_list()

### Subscribe for BDS
*available publications: BDS, IGM, CGM*

    response = service.publication_subscribe("BDS")

### Subscribe for all IGM-s except RT

    time_horizons = [f"{item:02d}" for item in list(range(1,32))] + ["ID", "1D", "2D", "YR"]
    for time_horizon in time_horizons:
        print(f"Adding subscription for {time_horizon}")
        response = service.publication_subscribe("IGM", subscription_id=f"IGM-{time_horizon}", metadata_dict={'pmd:timeHorizon': time_horizon})
        print(response)

## Cancel Subscription
    response = publication_cancel_subscription(subscription_id)

## Query Data
### Model
*Model consists of multiple files*

    query_id, response = service.query_object(object_type = "IGM", metadata_dict = {'pmd:scenarioDate': '2019-07-28T00:30:00', 'pmd:timeHorizon': '1D'})

### File

    query_id, response = service.query_profile('pmd:timeHorizon': '1D', 'pmd:cgmesProfile': 'SV'})

### Create nice table of returned Query responses

    import pandas

    pandas.set_option("display.max_rows", 12)
    pandas.set_option("display.max_columns", 10)
    pandas.set_option("display.width", 1500)
    pandas.set_option('display.max_colwidth', -1)

    print(pandas.DataFrame(response['sm:QueryResult']['sm:part'][1:]))

## Download a File
### Download to OPDM Client and return local path to the file
    response = service.get_content(file_UUID)
    print(response['sm:GetContentResult']['sm:part'][1]['opdm:Profile']['opde:Content'])

### Download and Save file
    response = service.get_content(file_UUID, return_payload=True)
    with open(f"{file_UUID}.zip", 'wb') as cgmes_file:
        report_file.write(response['sm:GetContentResult']['sm:part'][1]['opdm:Profile']['opde:Content'])






