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Process Performance Indicators

A Python library for calculating 310 process performance indicators from event logs. The library supports multiple event log formats and provides indicators across 5 dimensions (Time, Cost, Quality, Flexibility, General) at 4 granularity levels (activities, cases, groups, instances).

Features

  • Comprehensive indicator coverage: 310 indicators across time, cost, quality, flexibility, and general dimensions
  • Multiple granularities: Calculate metrics at activity, case, group, or instance level
  • Flexible input formats: Support for atomic, derivable, production-style, and explicit interval event logs
  • Automatic format detection: The library detects your log format and converts it to the required structure
  • Batch execution: Run all indicators at once or filter by dimension/granularity

Quick Installation

uv add process-performance-indicators

pip install process-performance-indicators

Quick Start

import pandas as pd
from process_performance_indicators import (
    event_log_formatter,
    run_indicators_to_csv,
    StandardColumnMapping,
    IndicatorArguments,
)

# 1. Load your event log
raw_log = pd.read_csv("my_event_log.csv")

# 2. Define column mapping
column_mapping = StandardColumnMapping(
    case_id_key="CaseID",
    activity_key="Activity",
    timestamp_key="Timestamp",
)

# 3. Format the event log
formatted_log = event_log_formatter(raw_log, column_mapping)

# 4. Define indicator arguments
args = IndicatorArguments(
    case_id="CASE-001",
    activity_name="Review Application",
)

# 5. Run indicators and save results
results = run_indicators_to_csv(
    formatted_log,
    args,
    csv_path="results.csv",
    verbose=True,
)

print(results.head())

Next Steps