Installation¶
Installing with conda
¶
schedview
can be installed using conda
.
If you want to add it to an existing conda
environment:
$ conda install -c conda-forge schedview
or, to use a dedicated environment for schedview
:
$ conda create --name schedview -c conda-forge schedview
conda
will take care of installing the needed python module dependencies,
but some of the data needed by some of its dependencies are not installed
automatically by conda
.
To download the necessary data, see the data download pages
for rubin_scheduler
and for rubin_sim
Note: at present, there are some dependencies which are not listed in the conda recipe, either because there is no conda package or we are determining whether it is safe to include them for installation in an LSST Stack metapackage. To add these additional packages, please install the following into your environment:
$ pip install lsst-resources
$ conda install -c conda-forge lsst-efd-client
Installing with pip
¶
schedview
can be installed using pip
.
Starting with whatever python
environment you want to use active:
$ pip install schedview
pip
will take care of installing the needed python module dependencies,
but some of the data needed by some of its dependencies are not installed
automatically by pip
.
To download the necessary data, see the data download pages
for rubin_scheduler
and for rubin_sim
For developer use¶
First, get the code by cloning the github project:
$ git clone git@github.com:lsst/schedview.git
$ cd schedview
Create a conda
environment with the appropriate dependencies, and activate it:
$ conda create --channel conda-forge --name rubin_sim --file requirements.txt python=3.11
$ conda activate schedview
Install the (development) schedview
in your new environment:
$ pip install -e . --no-deps
Some additional packages are required to run the tests. To install the tests, install the dependenices, then run the tests:
$ conda install -f test-requirements.txt
$ pytest .
Building the documentation requires the installation of documenteer[guide]
:
$ pip install "documenteer[guide]"
$ cd docs
$ package-docs build
The root of the local documentation will then be docs/_build/html/index.html
.
Using the schedview S3 bucket¶
If a user has appropriate credentials, schedview
can read data from an
S3
bucket. To have the prenight
dashboard read data from as S3
bucket, a few steps are needed to prepare the environment in which the
dashboard will be run.
First, the bucket credentials with access to the the endpoint and bucket
in which the archive resides need to be added to .lsst/aws-credentials.ini
file in the account that will be running the dashboard.
For the pre-night S3
bucket at the USDF, the endpoint is
https://s3dfrgw.slac.stanford.edu/
and the bucket name is
rubin-scheduler-prenight
. Access to this bucket must be
coordinated with the USDF administrators and the Rubin Observatory
survey scheduling team.
For example, if the USDF S3
bucket is to be used anth the section with
the aws_access_key_id
and aws_secret_access_key
with access to this
endpoint and bucket is prenight
, then the following environment variables
need to be set in the process running the dashboard:
$ export S3_ENDPOINT_URL='https://s3dfrgw.slac.stanford.edu/'
$ export AWS_PROFILE=prenight
The first of these (S3_ENDPOINT_URL
) might have been set up automatically
for you if you are running on the USDF.