Configuration for step-by-step transition analytics on taxonomy assignments. Enables analysis of how documents progress through taxonomy labels as a temporal sequence, answering questions like: - How long from "inquiry" to "closed_won"? - What % of "inquiry" emails reach "proposal"? - Which sender domains correlate with faster progression? Use Cases: 1. Email Thread Analysis: - Track progression: inquiry → followup → proposal → closed_won - Identify which subject lines correlate with faster closure 2. Content Workflow Tracking: - Monitor: draft → review → approved → published - Find bottlenecks and optimization opportunities 3. Safety Compliance Monitoring: - Trace: violation_detected → investigated → resolved - Track resolution times and success rates Attributes: timestamp_field: Document field containing event timestamp sequence_id_field: Field that groups related documents into sequences step_key_source: How to extract the step identifier (label/node_id/custom field) step_key_field_path: Required if step_key_source='field_path' covariates: List of predictor variables to analyze for conversion lift max_sequence_duration_days: Filter out sequences longer than this (data quality) Example: python # Email thread analysis configuration StepAnalyticsConfig( timestamp_field=\"Date\", # Email timestamp sequence_id_field=\"Thread-Index\", # Groups emails in same thread step_key_source=\"assignment_label\", # Use taxonomy label as step covariates=[ CovariateConfig( field_path=\"sender_domain\", covariate_type=\"categorical\", name=\"Sender Domain\" ), CovariateConfig( field_path=\"word_count\", covariate_type=\"numeric\", name=\"Email Length\" ) ], max_sequence_duration_days=90 # Ignore threads >90 days )
| Name | Type | Description | Notes |
|---|---|---|---|
| timestamp_field | str | Document field containing event timestamp (e.g., 'Date', 'created_at', 'metadata.timestamp') | |
| sequence_id_field | str | Document field that groups related items into a sequence (e.g., 'Thread-Index', 'session_id', 'user_id') | |
| step_key_source | StepKeySource | How to determine the 'step' for each document (label, node_id, or custom field) | [optional] |
| step_key_field_path | str | Required if step_key_source='field_path'. Dot-notation path to step value in document. | [optional] |
| covariates | List[CovariateConfig] | Predictor fields to analyze for conversion lift (categorical, numeric, embedding, cluster) | [optional] |
| max_sequence_duration_days | int | Maximum allowed duration for a sequence. Sequences beyond this are flagged as data quality issues. | [optional] |
from mixpeek.models.step_analytics_config_output import StepAnalyticsConfigOutput
# TODO update the JSON string below
json = "{}"
# create an instance of StepAnalyticsConfigOutput from a JSON string
step_analytics_config_output_instance = StepAnalyticsConfigOutput.from_json(json)
# print the JSON string representation of the object
print(StepAnalyticsConfigOutput.to_json())
# convert the object into a dict
step_analytics_config_output_dict = step_analytics_config_output_instance.to_dict()
# create an instance of StepAnalyticsConfigOutput from a dict
step_analytics_config_output_from_dict = StepAnalyticsConfigOutput.from_dict(step_analytics_config_output_dict)