AiiDAlab Launch makes it easy to run AiiDAlab on your own workstation or laptop.
To use AiiDAlab launch you will have to
Install Docker on your workstation or laptop. (you can also use Podman, see below)
Install AiiDAlab launch with pipx (recommended):
pipx install aiidalab-launch
Or directly with pip (pip install aiidalab-launch
).
Start AiiDAlab with
aiidalab-launch start
Follow the instructions on screen to open AiiDAlab in the browser.
See aiidalab-launch --help
for detailed help.
You can inspect the status of all configured AiiDAlab profiles with:
aiidalab-launch status
The tool allows to manage multiple profiles, e.g., with different home directories or ports.
See aiidalab-launch profile --help
for more information.
By default AiiDAlab will store all of its data in a Docker volume defined in the profile configuration option home_mount
.
You can also provide an absolute path to the AiiDAlab home directory on the host system (so called bind mount).
If this directory does not exist, AiiDAlab launch will try to create it on startup.
Additional volumes to be mounted to the the AiiDAlab container can be specified via the extra_mounts
option using the "docker-compose "short syntax" source:target:mode
.
source
is either a volume name or an absolute path to an existing directory on the host system,
target
is a path within the AiiDAlab container,
and mode is either rw
for read-write volume (default) or ro
for read-only volume.
As an example, here's how you can mount a quantum chemistry program installed on the host system to make it accessible to AiiDA inside the AiiDAlab container:
extra_mounts = ["/path/to/qcprogram:/opt/qcprogram:ro",]
Finally, AiiDAlab launch will create a dedicated volume for the local conda environment (~/.conda
).
That is because some conda packages are not compatible with non-linux file systems, meaning that they cannot be installed if the home directory was, for example, bound to a Mac OS-X file system on the host.
Please see here for instructions on how to run AiiDAlab on a remote machine and then forward it to your local terminal.
This package follows the Python compatibility and deprecation schedule specified by NEP 29.
You should be able to use Podman as as a drop-in replacement for Docker, with just a little extra setup. The following was tested on Fedora 39 which comes with Podman pre-installed.
systemctl --user enable podman.socket
systemctl --user start podman.socket
systemctl --user status podman.socket
export DOCKER_HOST=unix:///run/user/$UID/podman/podman.sock
To develop this package, first clone it and then install the development dependencies with pip install -e '.[dev]'
.
We recommend to install the pre-commit hooks to avoid unnecessary iterations when pushing new changes.
To install the pre-commit hooks, switch into the repository root directly and execute:
pre-commit install
To run the automated tests suite, clone the repository, install test dependencies with pip install -e '.[tests]'
, and then execute tests with
pytest
for all standard tests, and
pytest --slow
to run the full test suite, including tests that will start docker instances and may take multiple minutes.
The continuous integration workflow will run all tests, including the "slow" ones.
Note: On Mac OS-X you may have to override the standard temporary base directory to successfully run all tests (e.g. pytest --basetemp=$HOME/tmp
) since the default base directory may not be accessible to the Docker runtime.
To create a new release, clone the repository, install development dependencies with pip install -e '.[dev]'
, and then execute bumpver update
.
This will:
Additional notes:
--dry
option to preview the release change.main
branch,
and as such you need special permissions for writing to it.--tag
option to switch the release tag.See also the list of contributors.
Users of AiiDAlab are kindly asked to cite the following publication in their own work:
A. V. Yakutovich et al., Comp. Mat. Sci. 188, 110165 (2021). DOI:10.1016/j.commatsci.2020.110165
aiidalab@materialscloud.org
Contributions in any form are very welcome. Please see CONTRIBUTING.md for contribution guidelines.
Copyright (c) 2021 Carl Simon Adorf (EPFL)
All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This work is supported by the MARVEL National Centre for Competency in Research funded by the Swiss National Science Foundation, the MARKETPLACE project funded by Horizon 2020 under the H2020-NMBP-25-2017 call (Grant No. 760173), as well as by the MaX European Centre of Excellence funded by the Horizon 2020 EINFRA-5 program, Grant No. 676598.