Darksky feature snapshot

A high-level look at Stitch's Darksky (v1) integration, including release status, useful links, and the features supported in Stitch.

STITCH
Release status

Released on January 3, 2020

 Supported by

Singer Community
Stitch plan

Standard

 API availability

Available
Singer GitHub repository

singer-io/tap-darksky
REPLICATION SETTINGS
Anchor Scheduling

Supported

 Advanced Scheduling

Supported
Table-level reset

Unsupported

 Configurable Replication Methods

Unsupported
DATA SELECTION
Table selection

Unsupported

 Column selection

Unsupported
Select all

Unsupported
TRANSPARENCY
Extraction Logs

Supported

 Loading Reports

Supported

Connecting Darksky

Step 1: Retrieve your Darksky secret key

  1. Log into your Darksky API account here.
  2. On your account home page, your Secret Key is available at the top of the page. You will use this Secret Key to add your integration.

Step 2: Add Darksky as a Stitch data source

  1. Sign into your Stitch account.

  2. On the Stitch Dashboard page, click the Add Integration button.

  3. Click the Darksky icon.

  4. Enter a name for the integration. This is the name that will display on the Stitch Dashboard for the integration; it’ll also be used to create the schema in your destination.

    For example, the name “Stitch Darksky” would create a schema called stitch_darksky in the destination. Note: Schema names cannot be changed after you save the integration.

  5. In the Language field, enter the language code. Ex: ‘en’ for English, ‘es’ for Spanish, and ‘fr’ for French. For a full list of available language codes, check the Request Parameters section of the Darksky API documentation.
  6. In the Location List field, enter the latitude and longitude of the the locations to be returned for weather forecast information. The locations must be semi-colon deliniated. Ex: <latitude>,<longitude> is an accepted value for a single location, and <latitude>,<longitude>;<latitude>,<longitude>; ... etc is accepted for multiple locations.
  7. In the Secret Key field, paste your Darksky secret key that you retrieved in Step 1.
  8. In the Units field, enter the measurement system to be returned for weather forecast information. Ex: ‘us’ for Imperial Units, and ‘si’ for International System of Units. For a full list of available measurement systems, check the Request Parameters section of the Dark Sky API documentation

Step 3: Define the historical replication start date

The Sync Historical Data setting defines the starting date for your Darksky integration. This means that data equal to or newer than this date will be replicated to your data warehouse.

Change this setting if you want to replicate data beyond Darksky’s default setting of 1 year. For a detailed look at historical replication jobs, check out the Syncing Historical SaaS Data guide.

Step 4: Create a replication schedule

In the Replication Frequency section, you’ll create the integration’s replication schedule. An integration’s replication schedule determines how often Stitch runs a replication job, and the time that job begins.

Darksky integrations support the following replication scheduling methods:

To keep your row usage low, consider setting the integration to replicate less frequently. See the Understanding and Reducing Your Row Usage guide for tips on reducing your usage.

Initial and historical replication jobs

After you finish setting up Darksky, its Sync Status may show as Pending on either the Stitch Dashboard or in the Integration Details page.

For a new integration, a Pending status indicates that Stitch is in the process of scheduling the initial replication job for the integration. This may take some time to complete.

Free historical data loads

The first seven days of replication, beginning when data is first replicated, are free. Rows replicated from the new integration during this time won’t count towards your quota. Stitch offers this as a way of testing new integrations, measuring usage, and ensuring historical data volumes don’t quickly consume your quota.

Darksky table reference

forecast

The forecasts table contains weather conditions for a particular date and location. The locations are determined by the locations entered into the Locations field in Stitch.

Note: The units data points are returned in is determined by the value entered into the Units field in Stitch. For example: If us is entered, data will be returned in Imperial units.

Replication Method

Key-based Incremental

Primary Keys

forecast_date

latitude

longitude

Replication Key

forecast_date
Useful links

Darksky documentation

forecast schema on GitHub

Darksky API method

forecast table schema

daily

OBJECT

Click to expand daily

apparent_temperature_high

NUMBER

apparent_temperature_high_time

DATE-TIME

apparent_temperature_low

NUMBER

apparent_temperature_low_time

DATE-TIME

apparent_temperature_max

NUMBER

apparent_temperature_max_time

DATE-TIME

apparent_temperature_min

NUMBER

apparent_temperature_min_time

DATE-TIME

cloud_cover

NUMBER

dew_point

NUMBER

humidity

NUMBER

icon

STRING

moon_phase

NUMBER

precip_accumululation

NUMBER

precip_intensity

NUMBER

precip_intensity_max

NUMBER

precip_intensity_max_time

DATE-TIME

precip_probability

NUMBER

precip_type

STRING

pressure

NUMBER

summary

STRING

sunrise_time

DATE-TIME

sunset_time

DATE-TIME

temperature_high

NUMBER

temperature_high_time

DATE-TIME

temperature_low

NUMBER

temperature_low_time

DATE-TIME

temperature_max

NUMBER

temperature_max_time

DATE-TIME

temperature_min

NUMBER

temperature_min_time

DATE-TIME

time

DATE-TIME

uv_index

INTEGER

uv_index_time

DATE-TIME

visibility

NUMBER

wind_bearing

INTEGER

wind_speed

NUMBER

end_time

DATE-TIME

flags

OBJECT

Click to expand flags

nearest_station

NUMBER

sources

ARRAY

units

STRING

forecast_date

DATE-TIME

hourly

OBJECT

Click to expand hourly

data

ARRAY

Click to expand data

apparent_temperature

DATE-TIME

cloud_cover

NUMBER

dew_point

NUMBER

humidity

NUMBER

icon

STRING

ozone

NUMBER

precip_intensity

NUMBER

precip_probability

NUMBER

precip_type

STRING

pressure

NUMBER

summary

STRING

temperature

NUMBER

time

DATE-TIME

uv_index

INTEGER

visibility

NUMBER

wind_bearing

INTEGER

wind_gust

NUMBER

wind_speed

NUMBER

icon

STRING

summary

STRING

latitude

NUMBER

local_date

STRING

longitude

NUMBER

offset

NUMBER

start_time

DATE-TIME

timezone

STRING

Related Troubleshooting
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