# Libraries the benchmark's tasks need at evaluation time.
#
# Ships with the package, so anyone evaluating against DataFrameBench can build
# the environment its tasks were validated in:
#
#   dfbench-setup                          (installs this file + your library choice)
#   pip install -r $(python -c "import dataframebench, pathlib; \
#       print(pathlib.Path(dataframebench.__file__).parent / 'data/requirements.txt')")
#
# No dataframe library is listed. Which one you install is the choice this
# benchmark exists to measure, so requiring one here would contradict the whole
# premise - install whichever you are evaluating. The two the reference solutions
# were validated with are given below, commented out:
#
#   pandas>=2
#   polars>=1
#
# Versions are minimums, taken from the releases the tasks were validated against.
# Generated by benchmark/pipeline/07_build.py from the `libs` of the shipped tasks -
# edit that stage rather than this file.
beautifulsoup4>=4.15
faker>=40.36
folium>=0.20
geopy>=2.5
holidays>=0.102
lxml>=6.1
matplotlib>=3.11
numpy>=2.4
openpyxl>=3.1
python-dateutil>=2.9
pytz>=2026.3
regex>=2026.7
requests>=2.34
scikit-learn>=1.9
scipy>=1.17
seaborn>=0.13
statsmodels>=0.14
