pm4py.objects.log.util package

Submodules

• pm4py.objects.log.util.activities_to_alphabet module
  • Parameters
    • Parameters.ACTIVITY_KEY
    • Parameters.RETURN_MAPPING
  • apply()
• pm4py.objects.log.util.artificial module
  • Parameters
    • Parameters.ACTIVITY_KEY
    • Parameters.TIMESTAMP_KEY
    • Parameters.PARAM_ARTIFICIAL_START_ACTIVITY
    • Parameters.PARAM_ARTIFICIAL_END_ACTIVITY
  • insert_artificial_start_end()
• pm4py.objects.log.util.basic_filter module
  • Parameters
    • Parameters.ATTRIBUTE_KEY
    • Parameters.POSITIVE
  • filter_log_events_attr()
  • filter_log_traces_attr()
• pm4py.objects.log.util.dataframe_utils module
  • Parameters
    • Parameters.PARTITION_COLUMN
    • Parameters.CASE_ID_KEY
    • Parameters.CASE_PREFIX
    • Parameters.CASE_ATTRIBUTES
    • Parameters.CONSIDER_ALL_ATTRIBUTES
    • Parameters.MANDATORY_ATTRIBUTES
    • Parameters.MAX_NO_CASES
    • Parameters.MIN_DIFFERENT_OCC_STR_ATTR
    • Parameters.MAX_DIFFERENT_OCC_STR_ATTR
    • Parameters.TIMESTAMP_KEY
    • Parameters.ACTIVITY_KEY
    • Parameters.PARAM_ARTIFICIAL_START_ACTIVITY
    • Parameters.PARAM_ARTIFICIAL_END_ACTIVITY
    • Parameters.INDEX_KEY
    • Parameters.CASE_INDEX_KEY
    • Parameters.USE_EXTREMES_TIMESTAMP
    • Parameters.ADD_CASE_IDENTIFIER_COLUMN
    • Parameters.DETERMINISTIC
    • Parameters.COUNT_OCCURRENCES
    • Parameters.ENABLE_NUMERIC_ATTRIBUTE_STATISTICS
    • Parameters.NUMERIC_ATTRIBUTE_AGGREGATIONS
  • insert_partitioning()
  • legacy_parquet_support()
  • table_to_stream()
  • table_to_log()
  • convert_timestamp_columns_in_df()
  • sample_dataframe()
  • insert_artificial_start_end()
  • dataframe_to_activity_case_table()
• pm4py.objects.log.util.df_extra_utils module
  • Parameters
    • Parameters.CASE_ID_KEY
    • Parameters.START_TIMESTAMP_KEY
    • Parameters.TIMESTAMP_KEY
    • Parameters.COMPUTE_EXTRA_TEMPORAL_FEATURES
  • compute_extra_columns()
• pm4py.objects.log.util.df_features_utils module
  • automatic_feature_selection_df()
  • select_number_column()
  • select_string_column()
  • get_features_df()
  • automatic_feature_extraction_df()
• pm4py.objects.log.util.filtering_utils module
  • keep_one_trace_per_variant()
  • keep_only_one_attribute_per_event()
• pm4py.objects.log.util.get_class_representation module
  • get_class_representation_by_str_ev_attr_value_presence()
  • get_class_representation_by_str_ev_attr_value_value()
  • get_class_representation_by_trace_duration()
• pm4py.objects.log.util.get_log_encoded module
  • get_log_encoded()
• pm4py.objects.log.util.get_prefixes module
  • get_prefixes_from_log()
  • get_log_with_log_prefixes()
  • get_log_traces_to_activities()
  • get_log_traces_until_activity()
• pm4py.objects.log.util.index_attribute module
  • insert_event_index_as_event_attribute()
  • insert_trace_index_as_event_attribute()
• pm4py.objects.log.util.insert_classifier module
  • search_act_class_attr()
  • insert_activity_classifier_attribute()
  • insert_trace_classifier_attribute()
• pm4py.objects.log.util.interval_lifecycle module
  • Parameters
    • Parameters.TIMESTAMP_KEY
    • Parameters.START_TIMESTAMP_KEY
    • Parameters.TRANSITION_KEY
    • Parameters.ACTIVITY_KEY
    • Parameters.LIFECYCLE_INSTANCE_KEY
    • Parameters.BUSINESS_HOURS
    • Parameters.BUSINESS_HOUR_SLOTS
    • Parameters.WORKCALENDAR
  • to_interval()
  • to_lifecycle()
  • assign_lead_cycle_time()
• pm4py.objects.log.util.log module
  • get_event_labels()
  • get_event_labels_counted()
  • get_trace_variants()
  • project_traces()
  • derive_and_lift_trace_attributes_from_event_attributes()
  • add_artficial_start_and_end()
• pm4py.objects.log.util.log_regex module
  • get_encoded_trace()
  • get_encoded_log()
  • form_encoding_dictio_from_log()
  • form_encoding_dictio_from_two_logs()
• pm4py.objects.log.util.move_attrs_to_trace module
  • Parameters
    • Parameters.ENABLE_DEEPCOPY
  • apply()
• pm4py.objects.log.util.pandas_log_wrapper module
  • Parameters
    • Parameters.CASE_ID_KEY
    • Parameters.CASE_ATTRIBUTE_PREFIX
  • PandasTraceWrapper
  • PandasLogWrapper
• pm4py.objects.log.util.pandas_numpy_variants module
  • Parameters
    • Parameters.CASE_ID_KEY
    • Parameters.ACTIVITY_KEY
    • Parameters.TIMESTAMP_KEY
    • Parameters.INDEX_KEY
  • apply()
• pm4py.objects.log.util.pl_lazy_extra_utils module
  • Parameters
    • Parameters.CASE_ID_KEY
    • Parameters.START_TIMESTAMP_KEY
    • Parameters.TIMESTAMP_KEY
    • Parameters.COMPUTE_EXTRA_TEMPORAL_FEATURES
  • compute_extra_columns()
• pm4py.objects.log.util.pl_lazy_fea_utils module
  • automatic_feature_selection_df()
  • select_number_column()
  • select_number_columns()
  • select_string_column()
  • select_string_columns()
  • get_features_df()
  • automatic_feature_extraction_df()
• pm4py.objects.log.util.sampling module
  • sample_stream()
  • sample_log()
  • sample()
• pm4py.objects.log.util.sorting module
  • sort_timestamp_trace()
  • sort_timestamp_stream()
  • sort_timestamp_log()
  • sort_timestamp()
  • sort_lambda_log()
  • sort_lambda_stream()
  • sort_lambda()
• pm4py.objects.log.util.split_train_test module
  • split()
• pm4py.objects.log.util.xes module

Module contents

PM4Py – A Process Mining Library for Python Copyright (C) 2026 Process Intelligence Solutions GmbH

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

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