Local display of a jupyter notebook running at CC-IN2P3
Project description
Introduction
LSST stack + Jupyter -> stackyter
This script will allow you to run a jupyter notebook (or lab) at CC-IN2P3 while displaying it localy in your local brower. It is mainly intended to help LSST members to interact with the datasets already available at CC-IN2P3 using Python, but can be use for other purposes that need an anaconda environment.
Installation
Latest stable version can be installed with pip:
pip install stackyter
To upgrade to a newer version:
pip install --upgrade stackyter
To install in a local directory:
pip install --user stackyter # in your home directory pip install --prefix mypath stackyter # in 'mypath'
Usage
stackyter.py [options]
Options
The configuration file can contain any (or all) options available through command line. An example of such a file can be found here. The only option that you must use is the --username option.
Optional arguments are:
-h, --help show this help message and exit --config CONFIG Configuration file containing a set of option values. The content of this file will be overwritten by any given command line options. (default: None) --username USERNAME Your CC-IN2P3 user name. Mandatory either from command line or in the configuration file. (default: None) --workdir WORKDIR Your working directory at CC-IN2P3 (default: /pbs/throng/lsst/users/<username>/notebooks) --vstack VSTACK Version of the stack you want to set up. (E.g. v14.0, w_2017_43 or w_2017_43_py2) (default: v14.0) --packages PACKAGES A list of packages you want to setup. Coma separated from command line, or a list in the config file. You can use the `lsst_distrib` package to set up all available packages from a given distrib. (default: lsst_distrib) --jupyter JUPYTER Either launch a jupiter notebook or a jupyter lab. (default: notebook) --cca CCA Either connect to ccage or cca7. ccage might be used for old or local install of the stack, whereas all newer versions (>= v13.0, installed for the LSST group) must be set up on centos7 (cca7). (default: cca7) --libs LIBS Path(s) to local Python librairies. Will be added to your PYTHONPATH. Coma separated to add more than one paths, or a list in the config file. A default path for jupyter will be choose if not given. (default: None) --bins BINS Path(s) to local binaries. Will be added to your PATH. Coma separated to add more than one paths, or a list in the config file. A default path for jupyter will be choose if not given. (default: None) --labpath LABPATH You must provide the path in which jupyterlab has been installed in case it differs from the (first) path you gave to the --libs option. A default path for jupyterlab will be choose if not given. (default: None)
Note: ds9 is available since version 0.9.
Version of the LSST stack
All available versions of the LSST stack at CC-IN2P3 can be found under:
/sps/lsst/software/lsst_distrib/
These versions (and all the others) have been built under CentOS7, and must be used under a compatible system (CentOS7 or Ubuntu). To connect to a CentOS7 machine on CC-IN2P3, use cca7 instead of ccage (default value of this script).
Python 2 (2.7) and 3 (>3.4) are available for almost all weeklies, with the following nomencalture:
Version |
< w_2017_27 |
w_2017_27 |
---|---|---|
Python 2 |
w_2017_XX |
w_2017_XX_py2 |
Python 3 |
w_2017_XX_py3 |
w_2017_XX |
Latest releases of the LSST stack, as of 11-07-2017, are:
Version |
Comment |
---|---|
v14.0 |
Current stable version of the stack (Python 3 only) |
w_2017_43_py2 |
Latest weekly release for Python 2 |
w_2017_44 |
Latest weekly release for Python 3 |
Keep in mind that using Python 2 in an LSST context is not encouraged by the community, and will not be supported anymore. The latest weekly for which Python 2 has been installed at CC-IN2P3 is w_2017_4 (see online documentation).
Note: Since version w_2017_40, the ipython module is included in the stack installation at CC-IN2P3 as an add-on. This module is not part of the officiel LSST distribution and will not be set up with the lsst_distrib package.
Use the LSST stack
Many examples on how to use the LSST stack and how to work with its outputs are presented there.
A few data sets have already been created using the LSST stack, and their outputs are already available for analysis at different places on CC-IN2P3:
SXDS data from HSC: /sps/lsst/dev/lsstprod/hsc/SXDS/output
CFHT data (containing clusters): /sps/lsst/data/clusters
list to be completed.
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