A simple CLI wrapper for the Adobe Analytics Data Sources API

It is critical for analysts to be able to consume, analyze, and visualize all of their marketing data in one place, and Adobe's data sources API is a powerful tool to help import and merge disparate marketing data for use in the Analytics tool. However, it's not always clear how to get started and use the API, so I wanted to build a simple interface that allows beginners/non-technical users to start managing and importing 3rd party data into Adobe Analytics.

• Adobe Data Sources GitHub
• Adobe Data Sources User Guide (PDF)
• Adobe Data Sources Help

$ git clone https://github.com/394e608c/adscli.git
$ cd adscli
$ pip install -r requirements.txt
$ cd scripts

Note - now that Adobe has rolled out Service Account Integration and OAuth integration via the new console, I'll be looking to add additional authentication methods in the near future.

You need to generate a client id and client secret via Adobe's Legacy OAuth Applications:

1. Log in to Adobe Analytics
2. Admin > User Management (Legacy)
3. Click to Legacy OAuth Applications tab
4. Add application
5. Give it a name and select 'Data Sources' under Scopes

Next, open config.txt and paste your id/secret:

[CONFIG]
client_id = *paste client id here*
client_secret = *paste client secret here*
grant_type = client_credentials

1. DataSources.Get
2. DataSources.Delete
3. DataSources.GetJobs
4. DataSources.UploadData

Returns list of data sources. Simply pass in a reposrt suite ID with --rsid.

Usage:

$ python get_sources.py --rsid=mytestreportsuite

python get_sources.py --help

Options:
  --rsid TEXT  The report suite ID  [required]
  --help       Show this message and exit.

{
    "id": int,
    "processing_type": string,
    "name": string,
    "email": string,
    "activatedDate": date,
    "ftp": {
      "path": string,
      "loginID": string,
      "password": string
    },
    "haltOnWarning": boolean,
    "haltOnError": boolean,
    "lockedByError": boolean 
  }

Deletes a given data source. Pass in report suite ID (--rsid) and a data soure ID to delete (--dsid)

Usage:

$ python delete_source.py --rsid=mytestreportsuite --dsid=2

python delete_source.py --help

Options:
  --dsid TEXT  The dataSourceID  [required]
  --rsid TEXT  The report suite ID  [required]
  --help       Show this message and exit.

You will be prompted to confirm before actually making the request to delete the source:

You are about to permenantly delete dataSourceID: 2. Are you sure you want to proceed? [y/N]: 

Data source 2 successfully deleted

Returns a list of every job run for a particular data source. Pass in report suite ID (--rsid) and a data soure ID (--dsid)

Usage:

$ python get_jobs.py --rsid=mytestreportsuite --dsid=2

python get_jobs.py --help

Options:
  --dsid TEXT  The dataSourceID  [required]
  --rsid TEXT  The report suite ID  [required]
  --help       Show this message and exit.

[
  {
    "id": int,
    "fileName": string,
    "startDate": date,
    "finishDate":date,
    "size": int,
    "rows": int,
    "errors": [],
    "warnings": [],
    "receivedDate": date,
    "status": string
  }
]
2 jobs found for dataSourceID 2

Uploads data to a particular data source. Per usual, pass in a report suite ID (--rsid) and a data soure ID (--dsid). Additional required fields:

• --job-name: A name for the job (will be used in the fileName field in the response from GetJobs)
• --file: The path of a valid CSV with your data to load (no column headers). Make sure to move the csv into the scripts directory
• --cols: A comma delimited list (wrapped in quotes) of columns which should match the column names of your data source. Example: 'Event 1,Event 5,Evar 20'

Important: The order of column headers passed with --cols MUST match the order of the columns in your CSV to load. If --cols='Event 1,Event 5,Evar 20', then your CSV should have event1 in col A, event5 in col B and evar20 in col C.

Usage:

$ python upload_data.py --rsid=mytestreportsuite --dsid=2 --columns='Event 1,Evar 30' --file=file_to_load.csv --job-name=test

python upload_data.py --help

  --job-name TEXT  A name for the job  [required]
  --cols TEXT      Column delimited list of column names (Ex: 'Evar 1,Event 1')  [required]
  --file TEXT      The path for the CSV to load [required]
  --dsid TEXT      The dataSourceID  [required]
  --rsid TEXT      The report suite ID  [required]
  --help           Show this message and exit.

You will be prompted to confirm before actually making the request to POST the data:

Data is formatted and ready to load. Would you like to proceed? [y/N]: 

Data successfully loaded!