Metadata-Version: 2.4
Name: flowmine
Version: 0.1.4
Summary: Library that is intended to operate with various process mining tasks.
Author: FlowMine Contributors
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dataclassy==1.0.*
Requires-Dist: joblib==1.4.*
Requires-Dist: loguru==0.7.*
Requires-Dist: StrEnum==0.4.*
Requires-Dist: threadpoolctl==3.5
Requires-Dist: typing_extensions==4.12.*
Requires-Dist: eval-type-backport==0.2.*
Requires-Dist: pydantic==2.9.*
Requires-Dist: pydantic-numpy==5.0.2
Requires-Dist: openpyxl==3.1.*
Requires-Dist: numba==0.60.*
Requires-Dist: numpy==1.26.*
Requires-Dist: pandas==2.2.*
Requires-Dist: pandas-downcast==1.2.*
Requires-Dist: pandarallel==1.6.*
Requires-Dist: pyarrow==17.*
Requires-Dist: dateparser==1.2
Requires-Dist: scipy==1.13.*
Requires-Dist: XlsxWriter==3.2.*
Requires-Dist: translatepy==2.3
Requires-Dist: Faker==26.3.*
Requires-Dist: tqdm==4.66.*
Requires-Dist: nbformat==5.10.*
Requires-Dist: ipywidgets==8.1.*
Requires-Dist: matplotlib==3.9.*
Requires-Dist: seaborn==0.13.*
Requires-Dist: plotly==5.23.*
Requires-Dist: pillow>=10.1
Requires-Dist: grandalf==0.8
Requires-Dist: networkx==3.2.*
Requires-Dist: pydotplus==2.0.*
Requires-Dist: graphviz==0.20.*
Requires-Dist: mlxtend==0.23.*
Requires-Dist: scikit-learn==1.5.*
Requires-Dist: shap==0.46.*
Requires-Dist: pymorphy3==2.0.*
Requires-Dist: bpemb==0.3.*
Requires-Dist: catboost==1.2.*
Requires-Dist: statsmodels==0.14.*
Requires-Dist: torch==2.2.*
Requires-Dist: transformers==4.44.*
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

# FlowMine – Process Mining Python framework

FlowMine is an open-source Python library for conducting a comprehensive analysis of business processes with the use of process mining and machine learning techniques. By implementing this tool, objective and deep insights into the process on all levels can be revealed. These insights are then used to detect problems such as bottlenecks and deviations and identify potential opportunities for process improvement and optimization.

# Installation

To install FlowMine from PyPI:
```bash
pip install flowmine
```
To install from sources:
```bash
pip install .
```

Additionally, you have to install graphviz executables and add the path to the executables to your PATH variable:
https://graphviz.org/download/

# Quick start

There are some steps for quick start for your process log analysis:
* Create a DataHolder object:
```python
from flowmine import DataHolder, SuccessInputs, DurationUnits

path = "example_data.xlsx"
data_holder = DataHolder(
    data=path,
    col_case="id",
    col_stage="action",
    col_start_time="start_time",
    col_end_time="end_time",
    col_user="user_id",
    col_text="text",
    success_inputs=SuccessInputs(entries={"Подписание документов ", "Принято"}),
)

data_holder.data.head()
```
* Apply AutoInsights:
```python
from flowmine.autoinsights import AutoInsights

auto_insights = AutoInsights(data_holder, successful_stage="Принято")
auto_insights.apply()
```

# License

This project is released under the MIT License.
