oasislmf.platform_api.client

Classes

ApiEndpoint	Used to Implement the default requests common to all Oasis API
JsonEndpoint	Used for JSON data End points.
FileEndpoint	File Resources Endpoint for Upload / Downloading
API_models	Used to Implement the default requests common to all Oasis API
API_portfolios	Used to Implement the default requests common to all Oasis API
API_analyses	Used to Implement the default requests common to all Oasis API
APIClient

Module Contents

class oasislmf.platform_api.client.ApiEndpoint(session, url_endpoint, logger=None)

Bases: object

Used to Implement the default requests common to all Oasis API End points.

logger

session

url_endpoint = ''

create(data)

get(ID=None)

delete(ID)

search(metadata={})

class oasislmf.platform_api.client.JsonEndpoint(session, url_endpoint, url_resource, logger=None)

Bases: object

Used for JSON data End points.

logger

session

url_endpoint = ''

url_resource = ''

get(ID)

post(ID, data)

delete(ID)

download(ID, file_path, overwrite=True)

class oasislmf.platform_api.client.FileEndpoint(session, url_endpoint, url_resource, logger=None)

Bases: object

File Resources Endpoint for Upload / Downloading

logger

session

url_endpoint = ''

url_resource = ''

upload(ID, file_path, content_type=None)

upload_byte(ID, file_bytes, filename, content_type=None)

download(ID, file_path, overwrite=True, chuck_size=1024)

get(ID)

get_dataframe(ID)

Return file endpoint as dict of pandas Dataframes:

either ‘application/gzip’: search and extract all csv or ‘text/csv’: return as dataframe

post(ID, data_object, content_type='application/json')

post_dataframe(ID, data_frame)

delete(ID)

class oasislmf.platform_api.client.API_models(session, url_endpoint)

Bases: ApiEndpoint

Used to Implement the default requests common to all Oasis API End points.

resource_file

settings

versions

storage_links

chunking_configuration

scaling_configuration

setting_templates

data_files(ID)

create(supplier_id, model_id, version_id, data_files=[])

update(ID, supplier_id, model_id, version_id, data_files=[])

class oasislmf.platform_api.client.API_portfolios(session, url_endpoint)

Bases: ApiEndpoint

Used to Implement the default requests common to all Oasis API End points.

accounts_file

location_file

reinsurance_info_file

reinsurance_scope_file

currency_conversion_json

storage_links

reporting_currency

errors_file

validate

exposure_run

exposure_transform

create(name)

update(ID, name)

create_analyses(ID, name, model_id)

Create new analyses from Exisiting portfolio

class oasislmf.platform_api.client.API_analyses(session, url_endpoint)

Bases: ApiEndpoint

Used to Implement the default requests common to all Oasis API End points.

lookup_errors_file

lookup_success_file

lookup_validation_file

summary_levels_file

input_file

input_generation_traceback_file

output_file

run_traceback_file

run_log_file

settings_file

settings

run_progress

input_file_tar_list

output_file_tar_list

input_file_tar_extract

output_file_tar_extract

chunking_configuration

create(name, portfolio_id, model_id, data_files=[])

update(ID, name, portfolio_id, model_id, data_files=[])

status(ID)

generate(ID)

run(ID)

generate_and_run(ID)

cancel_analysis_run(ID)

cancel_generate_inputs(ID)

cancel(ID)

copy(ID)

data_files(ID)

storage_links(ID)

sub_task_list(ID)

combine(analysis_ids, config, name='combine-analysis')

class oasislmf.platform_api.client.APIClient(api_url='http://localhost:8000', api_ver='V2', auth_type=None, username='admin', password='password', client_id='oasis-service', client_secret='serviceNotSoSecret', access_token=None, refresh_token=None, token_url=None, scope=None, timeout=25, logger=None, **kwargs)

Bases: object

logger

api

api_ver = ''

models

portfolios

analyses

data_files

task_status

oed_peril_codes()

server_info()

healthcheck()

healthcheck_connections()

queue()

queue_status()

upload_portfolio_file(portfolio_id, portfolio_file, upload_data)

Upload a portfolio file using the API. Supports absolute filepaths or bytestreams.

If uploading a byte stream upload_data is a dict with the keys name which is a str containing the filename and bytes containing the byte stream of the file data. For example:

```python upload_portfolio_file(<portfolio_id>, “location_file”,

{‘bytes’: <byte_stream>, ‘name’: <filename>})

```

Parameters:

• portfolio_id (int) – Portfolio {id} from

• portfolio_file (str) – The name of the portfolio file to update. One of the following options location_file, accounts_file, reinsurance_info_file, reinsurance_scope_file or currency_conversion_json.

• upload_data ([str, dict]) – The file to upload through the api. This should be a str if it is a filepath or a dict if it is a byte stream with the keys name and bytes corresponding to the filename and bytestream respectively.

upload_portfolio_reporting_currency(portfolio_id, reporting_currency)

upload_inputs(portfolio_name=None, portfolio_id=None, location_fp=None, accounts_fp=None, ri_info_fp=None, ri_scope_fp=None, currency_conversion_fp=None, reporting_currency=None)

get_currency_conversion(filepath)

Gets either the json or csv file referenced in the json and tells the endpoint which is needed

Parameters:

filepath (str) – path to json file

Returns:

path to either same json file or csv file referenced by json file

Return type:

string

upload_settings(analyses_id, settings)

Upload an analyses run settings to an API

Method to post JSON data or upload a settings file containing JSON data

Parameters:

• analyses_id (int) – Analyses settings {id} from, v1/analyses/{id}/settings

• settings ([str, dict]) – Either a valid filepath or dictionary holding the settings

create_analysis(portfolio_id, model_id, analysis_name=None, analysis_settings_fp=None)

run_generate(analysis_id, poll_interval=5)

Generates the inputs for the analysis based on the portfolio. The analysis must have one of the following statuses, NEW, INPUTS_GENERATION_ERROR, INPUTS_GENERATION_CANCELLED, READY, RUN_COMPLETED, RUN_CANCELLED or RUN_ERROR.

run_analysis(analysis_id, analysis_settings_fp=None, poll_interval=5)

Runs all the analysis. The analysis must have one of the following statuses, NEW, RUN_COMPLETED, RUN_CANCELLED or RUN_ERROR

reconnect(analysis_id, output_dir=None, poll_interval=5)

Reconnects to an analysis that is still generating inputs or running, and resumes polling from its current status - without re-triggering input generation or the run itself. If the run has already completed, downloads the output (when output_dir is given).

download_output(analysis_id, download_path='', filename=None, clean_up=False, overwrite=True)

cancel_generate(analysis_id)

Cancels a currently inputs generation. The analysis status must be GENERATING_INPUTS

cancel_analysis(analysis_id)

Cancels a currently running analysis. The analysis must have one of the following statuses, PENDING or STARTED