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Library provides read access to the Artesian API

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Artesian.SDK

This Library provides read access to the Artesian API

Getting Started

Installation

You can install the package directly from pip pip.

pip install artesian-sdk

Alternatively, to install this package go to the release page .

How to use

The Artesian.SDK instance can be configured using API-Key authentication

from artesian import ArtesianConfig

cfg = ArtesianServiceConfig("https://fake-artesian-env/", "{api-key}")

QueryService

Using the ArtesianServiceConfig cfg we create an instance of the QueryService which is used to create Actual, Versioned and Market Assessment time series queries

Actual Time Series

from artesian import QueryService,Granularity

qs = QueryService(cfg);
data = qs.createActual() \
    .forMarketData([100011484,100011472,100011477,100011490,100011468,100011462,100011453]) \
    .inAbsoluteDateRange("2018-01-01","2018-01-02") \
    .inTimeZone("UTC") \
    .inGranularity(Granularity.HOUR) \
    .execute()

To construct an Actual Time Series the following must be provided.

Actual QueryDescription
Market Data IDProvide a market data id or set of market data id's to query
Time GranularitySpecify the granularity type
Time Extraction WindowAn extraction time window for data to be queried

Go to Time Extraction window section

Versioned Time Series

from artesian import QueryService,Granularity

qs = QueryService(cfg);
q = qs.createVersioned() \
    .forMarketData([100042422,100042283,100042285,100042281,100042287,100042291,100042289]) \
    .inAbsoluteDateRange("2018-01-01","2018-01-02") \
    .inTimeZone("UTC") \
    .inGranularity(Granularity.HOUR)


q.forMUV().execute()
q.forLastNVersions(2).execute()
q.forLastOfDays("2019-03-12","2019-03-16").execute()
q.forLastOfDays("P0Y0M-2D","P0Y0M2D").execute()
q.forLastOfDays("P0Y0M-2D").execute()
q.forLastOfMonths("2019-03-12","2019-03-16").execute()
q.forLastOfMonths("P0Y-1M0D","P0Y1M0D").execute()
q.forLastOfMonths("P0Y-1M0D").execute()
q.forVersion("2019-03-12T14:30:00").execute()
q.test1.forMostRecent("2019-03-12","2019-03-16").execute()
q.test1.forMostRecent("P0Y0M-2D","P0Y0M2D").execute()
q.test1.forMostRecent("P0Y0M-2D").execute()
q.test1.forMostRecent("2019-03-12","2019-03-16").execute()
q.test1.forMostRecent("P0Y-1M0D","P0Y1M0D").execute()
q.test1.forMostRecent("P0Y-1M0D").execute() 

To construct a Versioned Time Series the following must be provided.

Versioned QueryDescription
Market Data IDProvide a market data id or set of market data id's to query
Time GranularitySpecify the granularity type
Versioned Time Extraction WindowVersioned extraction time window
Time Extraction WindowAn extraction time window for data to be queried

Go to Time Extraction window section

Market Assessment Time Series

from artesian import QueryService

qs = QueryService(cfg);
data = qs.createMarketAssessment() \
    .forMarketData([100000032,100000043]) \
    .forProducts(["D+1","Feb-18"]) \
    .inAbsoluteDateRange("2018-01-01","2018-01-02") \
    .execute()

To construct a Market Assessment Time Series the following must be provided.

Mas QueryDescription
Market Data IDProvide a market data id or set of market data id's to query
ProductProvide a product or set of products
Time Extraction WindowAn extraction time window for data to be queried

Go to Time Extraction window section

Artesian SDK Extraction Windows

Extraction window types for queries.

Date Range

 .inAbsoluteDateRange("2018-08-01", "2018-08-10")

Relative Interval

 .inRelativeInterval(RelativeInterval.ROLLING_WEEK)

Period

 .inRelativePeriod("P5D")

Period Range

 .inRelativePeriodRange("P-3D", "P10D")

MarketData Service

Using the ArtesianServiceConfig cfg we create an instance of the MarketDataService which is used to retrieve MarketData infos.

from artesian import MarketDataService

mds = MarketDataService(cfg);

To list MarketData curves

page = 1
pageSize = 100
res = mds.readCurveRange(100042422, page, pageSize, versionFrom="2016-12-20" , versionTo="2019-03-12")

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