Installation#
sktime
currently supports:
Python versions 3.7, 3.8 and 3.9
Operating systems Mac OS X, Unix-like OS, Windows 8.1 and higher
See here for a full list of precompiled wheels available on PyPI.
We appreciate community contributions towards compatibility with python 3.10, or other operating systems.
Release versions#
For frequent issues with installation, consult the Release versions - troubleshooting section.
Installing sktime from PyPI#
sktime
releases are available via PyPI. To install
sktime
with core dependencies, excluding soft dependencies, via pip
type:
pip install sktime
To install sktime
with maximum dependencies, including soft dependencies, install with the all_extras
modifier:
pip install sktime[all_extras]
Installing sktime from conda#
sktime
releases are available via conda
from conda-forge
.
To install sktime
with core dependencies, excluding soft dependencies via conda
type:
conda install -c conda-forge sktime
To install sktime
with maximum dependencies, including soft dependencies, install with the all-extras
recipe:
conda install -c conda-forge sktime-all-extras
Note: currently this does not include the dependency catch-22
.
As this package is not available on conda-forge
, it must be installed via pip
if desired.
Contributions to remedy this situation are appreciated.
Release versions - troubleshooting#
Module not found#
The most frequent reason for module not found errors is installing sktime
with
minimum dependencies and using an estimator which interfaces a package that has not
been installed in the environment. To resolve this, install the missing package, or
install sktime
with maximum dependencies (see above).
Development versions#
To install the latest development version of sktime
, or earlier versions, the sequence of steps is as follows:
Step 1 - git
clone the sktime
repository, the latest version or an earlier version.
Step 2 - ensure build requirements are satisfied
Step 3 - pip
install the package from a git
clone, with the editable
parameter.
Detail instructions for all steps are given below. For brevity, we discuss steps 1 and 3 first; step 2 is discussed at the end, as it will depend on the operating system.
Step 1 - clone the git repository#
The sktime
repository should be cloned to a local directory, using a graphical user interface, or the command line.
Using the git
command line, the sequence of commands to install the latest version is as follows:
git clone https://github.com/alan-turing-institute/sktime.git
cd sktime
git checkout main
git pull
To build a previous version, replace line 3 with:
git checkout <VERSION>
This will checkout the code for the version <VERSION>
, where <VERSION>
is a valid version string.
Valid version strings are the repository’s git
tags, which can be inspected by running git tag
.
You can also download a zip archive of the version from GitHub.
Step 2 - satisfying build requirements#
Before carrying out step 3, the sktime
build requirements need to be satisfied.
Details for this differ by operating system, and can be found in the sktime build requirements section below.
Typically, the set-up steps needs to be carried out only once per system.
Step 3 - building sktime from source#
To build and install sktime
from source, navigate to the local clone’s root directory and type:
pip install .
Alternatively, the .
may be replaced with a full or relative path to the root directory.
For a developer install that updates the package each time the local source code is changed, install sktime
in editable mode, via:
pip install --editable .[dev]
This allows editing and extending the code in-place. See also pip reference on editable installs).
Note
You will have to re-run:
pip install --editable .
every time the source code of a compiled extension is changed (for instance when switching branches or pulling changes from upstream).
Building binary packages and installers#
The .whl
package and .exe
installers can be built with:
pip install build
python -m build --wheel
The resulting packages are generated in the dist/
folder.
sktime build requirements#
This section outlines the sktime
build requirements. These are required for:
installing
sktime
from source, e.g., development versionsthe advanced developer set-up
You now need to set up a new python virtual environment. Our instructions will go through the commands to set up a conda
environment which is recommended for sktime development.
This relies on an anaconda installation. The process will be similar for venv
or other virtual environment managers.
In the anaconda prompt
terminal:
Navigate to your local sktime folder
cd sktime
Create new environment with python 3.8:
conda create -n sktime-dev python=3.8
Warning
If you already have an environment called “sktime-dev” from a previous attempt you will first need to remove this
Activate the environment:
conda activate sktime-dev
Build an editable version of sktime
pip install -e .[all_extras,dev]
If everything has worked you should see message “successfully installed sktime”
Some users have experienced issues when installing NumPy, particularly version 1.19.4.
Note
If step 4. results in a “no matches found” error, it may be due to how your shell handles special characters.
Possible solution: use quotation marks:
pip install -e ."[all_extras,dev]"
Note
Another option under Windows is to follow the instructions for `Unix-like OS`_, using the Windows Subsystem for Linux (WSL). For installing WSL, follow the instructions here.
References#
The installation instruction are adapted from scikit-learn’s advanced installation instructions.