This is a Singer tap that produces JSON-formatted data following the Singer spec.
This tap:
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Pulls raw data from the [Amazon_Ads API].
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Extracts the following resources:
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Outputs the schema for each resource
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Incrementally pulls data based on the input state
** invoices**
- Data Key = invoiceSummaries
- Primary keys: ['id']
- Replication strategy: INCREMENTAL
** portfolios**
- Data Key = portfolios
- Primary keys: ['portfolioId']
- Replication strategy: INCREMENTAL
** profiles**
- Primary keys: ['profileId']
- Replication strategy: FULL_TABLE
** sponsored_brands_ad_creatives**
- Data Key = creatives
- Primary keys: ['adId']
- Replication strategy: INCREMENTAL
** sponsored_brands_ad_groups**
- Data Key = adGroups
- Primary keys: ['adGroupId']
- Replication strategy: INCREMENTAL
** sponsored_brands_ads**
- Data Key = ads
- Primary keys: ['adId']
- Replication strategy: INCREMENTAL
** sponsored_brands_bid_recommendations**
- Primary keys: ['recommendationId']
- Replication strategy: FULL_TABLE
** sponsored_brands_budget_rules_campaigns**
- Data Key = associatedCampaigns
- Primary keys: ['campaignId']
- Replication strategy: FULL_TABLE
** sponsored_brands_budget_rules**
- Data Key = budgetRulesForAdvertiserResponse
- Primary keys: ['ruleId']
- Replication strategy: INCREMENTAL
** sponsored_brands_campaigns_budget_rules**
- Data Key = associatedRules
- Primary keys: ['ruleId']
- Replication strategy: INCREMENTAL
** sponsored_brands_campaigns**
- Data Key = campaigns
- Primary keys: ['campaignId']
- Replication strategy: INCREMENTAL
** sponsored_brands_keywords**
- Primary keys: ['keywordId']
- Replication strategy: FULL_TABLE
** sponsored_brands_negative_keywords**
- Primary keys: ['keywordId']
- Replication strategy: FULL_TABLE
** sponsored_brands_negative_targets**
- Data Key = negativeTargets
- Primary keys: ['targetId']
- Replication strategy: FULL_TABLE
** sponsored_brands_product_targets**
- Primary keys: ['targetId']
- Replication strategy: FULL_TABLE
** sponsored_brands_store_assets**
- Primary keys: ['assetID']
- Replication strategy: FULL_TABLE
** sponsored_display_ad_groups**
- Primary keys: ['adGroupId']
- Replication strategy: INCREMENTAL
** sponsored_display_brand_safety_list**
- Data Key = requestStatusList
- Primary keys: ['requestId']
- Replication strategy: FULL_TABLE
** sponsored_display_budget_rules_campaigns**
- Data Key = associatedCampaigns
- Primary keys: ['campaignId']
- Replication strategy: FULL_TABLE
** sponsored_display_budget_rules**
- Data Key = budgetRulesForAdvertiserResponse
- Primary keys: ['ruleId']
- Replication strategy: INCREMENTAL
** sponsored_display_campaigns_budget_rules**
- Data Key = associatedRules
- Primary keys: ['ruleId']
- Replication strategy: INCREMENTAL
** sponsored_display_campaigns**
- Primary keys: ['campaignId']
- Replication strategy: INCREMENTAL
** sponsored_display_creatives**
- Primary keys: ['creativeId']
- Replication strategy: FULL_TABLE
** sponsored_display_negative_targeting_clauses**
- Primary keys: ['targetId']
- Replication strategy: INCREMENTAL
** sponsored_display_product_ads**
- Primary keys: ['adId']
- Replication strategy: INCREMENTAL
** sponsored_display_targetings**
- Primary keys: ['targetId']
- Replication strategy: INCREMENTAL
** sponsored_products_ad_groups**
- Data Key = adGroups
- Primary keys: ['adGroupId']
- Replication strategy: INCREMENTAL
- Data Key = productAds
- Primary keys: ['adId']
- Replication strategy: INCREMENTAL
** sponsored_products_budget_rules**
- Data Key = budgetRulesForAdvertiserResponse
- Primary keys: ['ruleId']
- Replication strategy: INCREMENTAL
** sponsored_products_campaigns**
- Data Key = campaigns
- Primary keys: ['campaignId']
- Replication strategy: INCREMENTAL
** sponsored_products_keywords**
- Data Key = keywords
- Primary keys: ['keywordId']
- Replication strategy: INCREMENTAL
** sponsored_products_negative_keywords**
- Data Key = negativeKeywords
- Primary keys: ['keywordId']
- Replication strategy: INCREMENTAL
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Install
Clone this repository, and then install using setup.py. We recommend using a virtualenv:
> virtualenv -p python3 venv > source venv/bin/activate > python setup.py install OR > cd .../tap-amazon-ads > pip install -e .
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Dependent libraries. The following dependent libraries were installed.
> pip install singer-python > pip install target-stitch > pip install target-json
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Create your tap's
config.jsonfile. The tap config file for this tap should include these entries:start_date- the default value to use if no bookmark exists for an endpoint (rfc3339 date string)user_agent(string, optional): Process and email for API logging purposes. Example:tap-amazon-ads <api_user_email@your_company.com>request_timeout(integer,300): Max time for which request should wait to get a response. Default request_timeout is 300 seconds.
{ "" "client_id": "the_client_id", "client_secret": "the_client_secret", "refresh_token": "the_refresh_token", "profiles": "0123456789", "start_date": "2019-01-01T00:00:00Z", "user_agent": "tap-amazon-ads <api_user_email@your_company.com>", "request_timeout": 300 }Optionally, also create a
state.jsonfile.currently_syncingis an optional attribute used for identifying the last object to be synced in case the job is interrupted mid-stream. The next run would begin where the last job left off.{ "currently_syncing": "engage", "bookmarks": { "export": "2019-09-27T22:34:39.000000Z", "funnels": "2019-09-28T15:30:26.000000Z", "revenue": "2019-09-28T18:23:53Z" } } -
Run the Tap in Discovery Mode This creates a catalog.json for selecting objects/fields to integrate:
tap-amazon-ads --config config.json --discover > catalog.jsonSee the Singer docs on discovery mode here.
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Run the Tap in Sync Mode (with catalog) and write out to state file.
For Sync mode:
> tap-amazon-ads --config tap_config.json --catalog catalog.json > state.json > tail -1 state.json > state.json.tmp && mv state.json.tmp state.json
To load to json files to verify outputs:
> tap-amazon-ads --config tap_config.json --catalog catalog.json | target-json > state.json > tail -1 state.json > state.json.tmp && mv state.json.tmp state.json
To pseudo-load to Stitch Import API with dry run:
> tap-amazon-ads --config tap_config.json --catalog catalog.json | target-stitch --config target_config.json --dry-run > state.json > tail -1 state.json > state.json.tmp && mv state.json.tmp state.json
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Test the Tap
While developing the amazon_ads tap, the following utilities were run in accordance with Singer.io best practices: Pylint to improve code quality.
> pylint tap-amazon-ads -d missing-docstring -d logging-format-interpolation -d too-many-locals -d too-many-argumentsPylint test resulted in the following score:
Your code has been rated at 9.67/10
To check the tap.
> tap-amazon-ads --config tap_config.json --catalog catalog.json | singer-check-tap > state.json > tail -1 state.json > state.json.tmp && mv state.json.tmp state.json
Unit tests may be run with the following.
python -m pytest --verboseNote, you may need to install test dependencies.
pip install -e .'[dev]'
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