tap-google-sheets

This is a Singer tap that produces JSON-formatted data following the Singer spec.

This tap:

• Pulls raw data from the Google Sheets v4 API
• Extracts the following endpoints:
  • File Metadata
  • Spreadsheet Metadata
  • Spreadsheet Values
• Outputs the following metadata streams:
  • File Metadata: Name, audit/change info from Google Drive
  • Spreadsheet Metadata: Basic metadata about the Spreadsheet: Title, Locale, URL, etc.
  • Sheet Metadata: Title, URL, Area (max column and row), and Column Metadata
    • Column Metadata: Column Header Name, Data type, Format
  • Sheets Loaded: Sheet title, load date, number of rows
• For each Sheet:
  • Outputs the schema for each resource (based on the column header and datatypes of row 2, the first row of data)
  • Outputs a record for all columns that have column headers, and for each row of data
  • Emits a Singer ACTIVATE_VERSION message after each sheet is complete. This forces hard deletes on the data downstream if fewer records are sent.
  • Primary Key for each row in a Sheet is the Row Number: __sdc_row
  • Each Row in a Sheet also includes Foreign Keys to the Spreadsheet Metadata, __sdc_spreadsheet_id, and Sheet Metadata, __sdc_sheet_id.

API Endpoints

file (GET)

• Endpoint: https://www.googleapis.com/drive/v3/files/${spreadsheet_id}?fields=id,name,createdTime,modifiedTime,version
• Primary keys: id
• Replication strategy: Incremental (GET file audit data for spreadsheet_id in config)
• Process/Transformations: Replicate Data if Modified

metadata (GET)

• Endpoint: https://sheets.googleapis.com/v4/spreadsheets/${spreadsheet_id}?includeGridData=true&ranges=1:2
• This endpoint eturns spreadsheet metadata, sheet metadata, and value metadata (data type information)
• Primary keys: Spreadsheet Id, Sheet Id, Column Index
• Foreign keys: None
• Replication strategy: Full (get and replace file metadata for spreadshee_id in config)
• Process/Transformations:
  • Verify Sheets: Check sheets exist (compared to catalog) and check gridProperties (available area)
    • sheetId, title, index, gridProperties (rowCount, columnCount)
  • Verify Field Headers (1st row): Check field headers exist (compared to catalog), missing headers (columns to skip), column order/position, and column name uniqueness
  • Create/Verify Datatypes based on 2nd row value and cell metadata
    • First check:
      • effectiveValue: key
        • Valid types: numberValue, stringValue, boolValue
        • Invalid types: formulaValue, errorValue
    • Then check:
      • effectiveFormat.numberFormat.type
        • Valid types: UNEPECIFIED, TEXT, NUMBER, PERCENT, CURRENCY, DATE, TIME, DATE_TIME, SCIENTIFIC
        • Determine JSON schema column data type based on the value and the above cell metadata settings.
        • If DATE, DATE_TIME, or TIME, set JSON schema format accordingly

values (GET)

• Endpoint: https://sheets.googleapis.com/v4/spreadsheets/${spreadsheet_id}/values/'${sheet_name}'!${row_range}?dateTimeRenderOption=SERIAL_NUMBER&valueRenderOption=UNFORMATTED_VALUE&majorDimension=ROWS
• This endpoint loops through sheets and row ranges to get the unformatted values (effective values only), dates and datetimes as serial numbers
• Primary keys: _sdc_row
• Replication strategy: Full (GET file audit data for spreadsheet_id in config)
• Process/Transformations:
  • Loop through sheets (compared to catalog selection)
    • Send metadata for sheet
  • Loop through ALL columns for columns having a column header
  • Loop through ranges of rows for ALL rows in sheet available area max row (from sheet metadata)
  • Transform values, if necessary (dates, date-times, times, boolean).
    • Date/time serial numbers converted to date, date-time, and time strings. Google Sheets uses Lotus 1-2-3 Serial Number format for date/times. These are converted to normal UTC date-time strings.
  • Process/send records to target

Authentication

The Google Sheets Setup & Authentication Google Doc provides instructions show how to configure the Google Cloud API credentials to enable Google Drive and Google Sheets APIs, configure Google Cloud to authorize/verify your domain ownership, generate an API key (client_id, client_secret), authenticate and generate a refresh_token, and prepare your tap config.json with the necessary parameters.

• Enable Googe Drive APIs and Authorization Scope: https://www.googleapis.com/auth/drive.metadata.readonly
• Enable Google Sheets API and Authorization Scope: https://www.googleapis.com/auth/spreadsheets.readonly
• Tap config.json parameters:
  • client_id: identifies your application
  • client_secret: authenticates your application
  • refresh_token: generates an access token to authorize your session
  • spreadsheet_id: unique identifier for each spreadsheet in Google Drive
  • start_date: absolute minimum start date to check file modified
  • user_agent: tap-name and email address; identifies your application in the Remote API server logs

Quick Start

1. 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-google-sheets
   > pip install .

2. Dependent libraries The following dependent libraries were installed.

   > pip install target-json
   > pip install target-stitch
   > pip install singer-tools
   > pip install singer-python

   • singer-tools
   • target-stitch

3. Create your tap's config.json file. Include the client_id, client_secret, refresh_token, site_urls (website URL properties in a comma delimited list; do not include the domain-level property in the list), start_date (UTC format), and user_agent (tap name with the api user email address).

   {
       "client_id": "YOUR_CLIENT_ID",
       "client_secret": "YOUR_CLIENT_SECRET",
       "refresh_token": "YOUR_REFRESH_TOKEN",
       "spreadsheet_id": "YOUR_GOOGLE_SPREADSHEET_ID",
       "start_date": "2019-01-01T00:00:00Z",
       "user_agent": "tap-google-sheets <[email protected]>",
       "request_timeout": 300
   }

   Optionally, also create a state.json file. currently_syncing is 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. Only the performance_reports uses a bookmark. The date-time bookmark is stored in a nested structure based on the endpoint, site, and sub_type.The request_timeout is an optional paramater to set timeout for requests. Default: 300 seconds

   {
       "currently_syncing": "file_metadata",
       "bookmarks": {
           "file_metadata": "2019-09-27T22:34:39.000000Z"
       }
   }

4. Run the Tap in Discovery Mode This creates a catalog.json for selecting objects/fields to integrate:

   tap-google-sheets --config config.json --discover > catalog.json

   See the Singer docs on discovery mode here.

5. Run the Tap in Sync Mode (with catalog) and write out to state file

   For Sync mode:

   > tap-google-sheets --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-google-sheets --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-google-sheets --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

6. Test the Tap

   While developing the Google Search Console tap, the following utilities were run in accordance with Singer.io best practices: Pylint to improve code quality:

   > pylint tap_google_sheets -d missing-docstring -d logging-format-interpolation -d too-many-locals -d too-many-arguments

   Pylint test resulted in the following score:

   Your code has been rated at 9.78/10

   To check the tap and verify working:

   > tap-google-sheets --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

   Check tap resulted in the following:

   The output is valid.
   It contained 3881 messages for 13 streams.
   
       13 schema messages
     3841 record messages
       27 state messages
   
   Details by stream:
   +----------------------+---------+---------+
   | stream               | records | schemas |
   +----------------------+---------+---------+
   | file_metadata        | 1       | 1       |
   | spreadsheet_metadata | 1       | 1       |
   | Test-1               | 9       | 1       |
   | Test 2               | 2       | 1       |
   | SKU COGS             | 218     | 1       |
   | Item Master          | 216     | 1       |
   | Retail Price         | 273     | 1       |
   | Retail Price NEW     | 284     | 1       |
   | Forecast Scenarios   | 2681    | 1       |
   | Promo Type           | 91      | 1       |
   | Shipping Method      | 47      | 1       |
   | sheet_metadata       | 9       | 1       |
   | sheets_loaded        | 9       | 1       |
   +----------------------+---------+---------+

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