Python package installation
Note
CatBoost Python package supports only CPython Python implementation.
Alert
Installation is only supported by the 64-bit version of Python.
Dependencies:
graphviz
(if you want to useplot_tree
function)matplotlib
numpy (>=1.16.0)
pandas (>=0.24)
plotly
scipy
six
Note
Note that in most cases dependencies will be installed automatically using mechanisms built into setuptools
, pip
or conda
.
To install the Python package:
-
Choose an installation method:
-
(Optionally) Install additional packages for data visualization support.
-
(Optionally) Additional setup if user-defined functions are used:
If you want to use custom metrics or objectives implemented in your own python code you should install
numba
package to speed up the code execution using JIT compilation.If you want to use custom metrics or objectives on GPUs with CUDA support you must install
numba
package for JIT compilation of CUDA code.
Installation ofnumba-cuda
package is also encouraged.
CUDA itself (not only drivers) must be installed on machines where this code is executed.
Seenumba
CUDA support documentation for more details.These packages are not listed in package requirements that are installed automatically because they are not needed for other functionality.
-
(Optionally) Test CatBoost.
Note that there are additional system requirements if training on GPU is required.
GPU system requirements
The versions of CatBoost for Linux and Windows available from pip install and conda install have CUDA-enabled GPU support out-of-the-box.
As of CatBoost 1.2.8, devices with CUDA compute capability >= 3.5 are supported in released packages.
All necessary CUDA libraries are statically linked in the released Linux and Windows binaries, the only installation necessary is the appropriate version of the CUDA driver.
Training or inference on CUDA-enabled GPUs requires NVIDIA Driver of version 450.80.02 or higher.