If you need to export data from Next Matter to an external tool or file it away, you can use one of the three possible options:
Download data as CSV file (Data > Workflow data )
Use Next Matter API and apply the script provided below
Use an integration step to export data to a 3rd party tool, such as Google Sheets, Redshift, or PostgreSQL
Custom export - click Contact us (top-right corner), and tell us what you need
Download as CSV With the CSV file, you can download the workflow metadata and values fetched or provided in the workflow. The exported data are the following:
ID
name
priority
tags
deadline
started time
completed time
last updated time (see below to learn what triggers updates)
aborted time
lead user
stage ID
stage name
data for each step: activated time, assigned time, completed time, completed by
additionally for integration steps: integration step error, integration step success, integration step debug errors, analytics info (execution duration), user variables, output summary
If a field doesn’t apply, then its value field is empty.
You can only export data from one workflow per hour.
What affects the Last updated time Only the following events affect the Last updated time:
retry step
assign step
complete instance
abort instance
activate step
Note that updating a deadline or completing a step doesn’t result in the time being updated.
How to download a CSV Export only selected data You can’t select the data to export, however, you can do the following to filter out the data in the exported file:
Download the CSV Export.
Import the file to Excel. Make sure to import the file and not just open it. imported instead of just opened. See Microsoft documentation for details.
Delete all columns except for the data you need.
Download with a script The script downloads data and exports them to a CSV file. The script creates columns for workflow ID, instance ID, instance name, and the names of the form fields to be exported. All the data from the form fields are also exported.
To run this script, you need to get the following:
Next Matter API key Workflow ID of the workflow you want to export
Step ID of the step to export
Form field ID of the step you want to export, the name of the field, and its value type
import requests import pandas as pd import time # Constants API_KEY = "API KEY" ROOT_URL = "https://core.nextmatter.com/api" HEADERS = { "Content-Type" : "application/json" , "Authorization" : f "Api-Key { API_KEY } " } def fetch_data ( session , workflow_id , step_id , form_field_id ): """ Fetch data from the API for a given workflow, step, and form field. """ request_url = f " { ROOT_URL } /processes/ { workflow_id } /steps/ { step_id } /actions/ { form_field_id } /" response = session.get(request_url) return response.json() def process_response ( response , form_field_type ): """ Process the response to extract needed values. """ data_values = [] for result in response[ 'results' ]: instance_id = result[ 'instance_id' ] instance_name = result[ 'instance_name' ] value = str (result[ 'value' ][form_field_type]) data_values.append((instance_id, instance_name, value)) return data_values def update_dataframe ( df , workflow_id , form_field_names , instance_id , instance_name , form_field_name , value ): """ Update the DataFrame with new values or add new rows. """ if instance_id in df[ 'Instance Id' ].values: df.loc[df[ 'Instance Id' ] == instance_id, form_field_name] = value else : new_row = { 'Workflow Id' : workflow_id, 'Instance Id' : instance_id, 'Instance Name' : instance_name, form_field_name: value} for field_name in form_field_names: if field_name != form_field_name: new_row[field_name] = None df.loc[ len (df)] = new_row return df def main (): data_to_export = [ { "workflow_id" : WORKLOW_ID , //** replace with workflow ID **// "inputs_to_export" : [ { "step_id" : STEP_ID , //** replace with step ID **// "form_field_id" : FORM_FIELD_ID , //** replace with form field ID **// "form_field_name" : "FIELD1_NAME" , //** replace with name of the field **// "form_field_type" : "inputValue" }, { "step_id" : STEP_ID , "form_field_id" : FORM_FIELD_ID , "form_field_name" : "FIELD2_NAME" , "form_field_type" : "inputValue" } ] } ] session = requests.Session() session.headers.update( HEADERS ) # Extract all unique form_field_names and create the DataFrame form_field_names = [field[ 'form_field_name' ] for workflow in data_to_export for field in workflow[ 'inputs_to_export' ]] columns = [ 'Workflow Id' , 'Instance Id' , 'Instance Name' ] + form_field_names df = pd.DataFrame( columns = columns) for workflow_to_export in data_to_export: workflow_id = workflow_to_export[ "workflow_id" ] datapoints = workflow_to_export[ "inputs_to_export" ] for field in datapoints: step_id = field[ "step_id" ] form_field_id = field[ "form_field_id" ] form_field_name = field[ "form_field_name" ] form_field_type = field[ "form_field_type" ] response = fetch_data(session, workflow_id, step_id, form_field_id) data_values = process_response(response, form_field_type) for instance_id, instance_name, value in data_values: df = update_dataframe(df, workflow_id, form_field_names, instance_id, instance_name, form_field_name, value) time.sleep( 1 ) df.to_csv( "output.csv" , index = False ) if __name__ == "__main__" : main() Export using integration steps You can send workflow input values and workflow metadata such as workflow name, deadline, lead, tags, or start time directly from each workflow.
