Author: Fernando Pérez.
A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.
This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.
See the companion notebook for data preparation and setup.
| denali[~]> conda create -n iptest ipython -vvv | |
| DEBUG conda.cli.main:_main(143): verbosity set to 3 | |
| DEBUG conda.core.index:fetch_index(349): channel_urls=OrderedDict([('https://repo.continuum.io/pkgs/free/osx-64', ('defaults', 0)), ('https://repo.continuum.io/pkgs/free/noarch', ('defaults', 0)), ('https://repo.continuum.io/pkgs/r/osx-64', ('defaults', 0)), ('https://repo.continuum.io/pkgs/r/noarch', ('defaults', 0)), ('https://repo.continuum.io/pkgs/pro/osx-64', ('defaults', 0)), ('https://repo.continuum.io/pkgs/pro/noarch', ('defaults', 0))]) | |
| Fetching package metadata ...DEBUG requests.packages.urllib3.util.retry:from_int(191): Converted retries value: 3 -> Retry(total=3, connect=None, read=None, redirect=None) | |
| DEBUG conda.core.index:fetch_repodata(284): Using cached repodata for https://repo.continuum.io/pkgs/free/osx-64 at /Users/fperez/usr/conda/pkgs/cache/840cf1fb.json. Timeout in 284 sec | |
| .DEBUG conda.core.index:fetch_repodata(284): Using cached repodata for https://repo.continuum.io/pkgs/free/noarch at / |
| (master)denali[jupyter-js-widgets]> cat /Users/fperez/dev/ipython/ipywidgets/jupyter-js-widgets/npm-debug.log | |
| 0 info it worked if it ends with ok | |
| 1 verbose cli [ '/usr/local/Cellar/node/6.0.0/bin/node', | |
| 1 verbose cli '/usr/local/bin/npm', | |
| 1 verbose cli 'install', | |
| 1 verbose cli '--save', | |
| 1 verbose cli 'jupyter-js-widgets' ] | |
| 2 info using [email protected] | |
| 3 info using [email protected] | |
| 4 silly loadCurrentTree Starting |