dhis2-dummydataagg

dhis2-dummydataagg

Tool box to generate and manage dummy data in Tracker

Tools for dummy data generation in Aggregated

Python 3.6+ is required.

Installation

Use the package manager pip to install required packages.

pip install -r requirements.txt

Create/modify auth.json file containing the credentials of the default server to use. Use a Superuser account and provide the full URL without the /api part. See example below:

{
  "dhis": {
    "baseurl": "https://who-dev.dhis2.org/dev",
    "username": "admin",
    "password": "district"
  }
}

Usage

positional mandatory arguments:
   dataset_param         UIDs of dataSets to generate for separated by commas, or a prefix to filter the dataSets by name, e.g. HIV
optional arguments:
  -h, --help             show the help message and exit
      -i   instance          to provide a URL that overrides the one provided in baseurl of auth.json. Credentials are still taken from auth file
  -sd  START_DATE        data generated will start from start date
  -ed  END_DATE          data will be generated until end date, being today the default date to use if not specified
  -ptf PERIOD_TYPE_FILTER can be d, w, m, q, y    this options allows processing only dataSets for a specific time frequency from all the dataSets which will match the prefix search
  -ous TYPE VALUE        this parameters is used to specify the OUs which data will be generated for. From all the options available:
      type=uid           value is a comma separated list of OU uids to use
      type=uid_children  uses the children OUs of OU specified by a list of parent UIDs separated by commas
      type=name          uses the OU given by a list of names separated by commas
      type=ilike         uses a keyword to search for OUs by name (not case sensitive)
      type=code          a list of one or more OU codes to use separated by commas
      type=group         uses all OU in an OU group identied by UID. If providing a list of OU group UIDs (separated by comma), then uses OUs within any of those groups.
      -ours                  Specify the size of the random OUs to use, i.e. if the selection of OUs returned by -ous parameter is greater than the size value specified after -ours, a random subset is choseh of size specified
      type=level         all OUs in a specific OU level
  -cf [FILE_NAME]        create a flat file with DEs and COCs to allow specifying value ranges.The file name can be specified as parameter. This operation won't create any dummy data
  -uf FILE_NAME          uses a previously created (using cf) spreadsheet with value ranges to generate the dummy data

Examples:

python create_data.py Lt6P15ps7f6 -sd=2021-01-01 -ed=2021-04-30 -ous level 4 -ours 30

python create_data.py HIV -sd=2021-01-01 -ous name "Health facility" -uf test.csv

python create_data.py HIV -cf hiv_dataset_value_ranges.csv -i=https://metadata.dev.dhis2.org/dev