Bulk upload of POIs
The Import POIs button in the Places Service can be used to bulk upload new POIs using a CSV file. A sample spreadsheet template is provided to show which data columns are required and how to add optional custom metadata.
See this video showing the process for bulk import and bulk edit:
Python API scripts
A set of Python scripts have been created to simplify the batch import of POIs from a .csv file into a POI database by using the Web Service APIs. These scripts can be downloaded from this open source git repo .
Before you run these scripts, to access the web service APIs, see Prerequisites for user access in Integration overview and prerequisites .
Here is some information about the scripts:
This information is also included in a readme file in the git repo .
A sample .csv file, places_sample.csv , is part of this package and includes the required headers and a row of sample data. These headers are all lower case and correspond to the reserved metadata keys that are used in the Places database. Columns that you add to the .csv file will be added to the POI database in a separate metadata section for each POI as key/value pairs, and the header value is used as the key.
Here is a list of the columns and the values that you need to use:
- lib_idA valid library ID that is obtained from the POI database.
- typePoint is currently the only valid value.
- longitudeA value between -180 and 180.
- latitudeA value between -85 and 85.
- radiusA value between 10 and 20,000.
The values of the following columns are used in the Places Service UI:
- color, which is used as the color of the pin that represents the location of the POI in the Places Service UI map.
- The valid values are "", #3E76D0, #AA99E8, #DC2ABA, #FC685B, #FC962E, #F6C436, #BECE5D, #61B56B, and #3DC8DE, and "".
- If the value is left blank, the Places Service UI uses blue as the default color.The values correspond to blue (#3E76D0), purple (#AA99E8), fuschia (#DC2ABA), orange (#FC685B), light orange (#FC962E), yellow (#F6C436), light green (#BECE5D), green (#61B56B), and light blue (#3DC8DE), respectively.
- icon, which is used as the icon on the pin that represents the location of the POI on the Places Service UI map.
- The valid values are "", shop, hotelbed, car, airplane, train, ship, stadium, amusementpark, anchor, beaker, bell, bid, book, box, briefcase, browse, brush, building, calculator, camera, clock, education, flashlight, follow, game, female, male, gift, hammer, heart, home, key, launch, lightbulb, mailbox, money, pin, promote, ribbon, shoppingCart, star, target, teapot, thumbDown, thumbUp, trap, trophy, wrench.The icon values are listed in the order in which they appear in the following illustration:
- If the value is left blank, the UI uses star as the default icon.
- Columns that are not mentioned can be left blank.
Running the Script
- Download files from the git repo to your local directory.
- In a text editor, open the config.py file and complete the following tasks:a. Edit the following variable values as strings:
b. Save your changes.
- csv_file_pathThis is the path to your .csv file.
- access_codeThis is your access code that was obtained from the call to Adobe IMS. For information about how to obtain this access code, see Prerequisites for user access in Integration overview and prerequisites .
- org_idThe Experience Cloud orgID into which the POIs are to be imported. For information about how to obtain the org ID, see Prerequisites for user access in Integration overview and prerequisites .
- api_keyThis is your Places REST API key obtained from your Adobe I/O Places Integration. For information about how to obtain the API key, see Prerequisites for user access in Integration overview and prerequisites .
- In a terminal window, navigate to the …/places-scripts/import/ directory.
- Enter python ./places_import.py and press the enter ( return ) key.
Pre-import CSV checks
The script initially completes the following checks on the .csv file:
- Whether a .csv file was specified.
- Whether the file path is valid.
- Whether the reserved metadata headers are included.The reserved metadata headers are lib_id, name, description, type, longitude, latitude, radius, country, state, city, street, category, icon, and color.The headers are all lower case and can be listed in any order.
- Verifies the values of the columns specified in the CSV file section.
If errors are found, the script prints out the errors and is aborted. If no errors are found, the script attempts to import the POIs in batches of 1000. If the batch is successfully imported, the script reports a status code of 200. If the batch is not successfully imported, errors are reported.
Unit tests are in the tests.py file, should be run before each pull request, and should all pass. Additional tests should be added with new code. To run the tests, navigate to the …/places-scripts/import/ directory, and enter python ./places_import.py in terminal.