* Bump `base-notebook`
* OS version
* `jupyterlab`
* Bump `scipy-notebook`
* `beautifulsoup4`
* `cloudpickle`
* `dask`
* `numba`
* `xlrd`: version specified (it was not the case)
* Bump `datascience-notebook`
* `r-devtools`
* `r-forecast`
* Julia version
* Test added to check if Julia is correctly installed (`julia --version`)
* Note: A new version of `r-base` is out `4.0.0` however it cannot be installed yet since dependencies with other packages cannot be resolved.
* Bump `r-notebook`
* Same as `datascience-notebook` except Julia.
* Bump `all-spark-notebook`
* `r-sparklyr`
- Bump root container version
- Bump packages of
- scipy-notebook
- r-notebook
- datascience-notebook
- add -y flag to jupyter lab commands in scipy-notebook
- Fix a bug in check outdated packages when packages installed through pip
New Docker Hub UI loses newlines in the env
var settings. Loss of new lines leads ssh-add
to prompt and fail when loading the key.
Base64 encode and decode the key to workaround
the limitation.
This commit adds the additional `-f` force command to all uses of `conda
clean --all` through the repo. Size should be smaller, but still testing
if anything breaks. See issue #861.
This is the latest stable release of Julia.
I also cleaned up the package operations and added `QuantEcon/InstantiateFromURL.jl`, which is a small utility for binding Julia dependency information to a Jupyter notebook.
Builds fine on my local machine.
The `r` channel has been considered part of `defaults` since `conda` version `4.3.0`. So it should already be taken into consideration by `conda` installs without having to explicitly add the channel. Further the `conda-forge` channel has incorporated an ever growing, healthy stack of R packages. As such it appears all of the R packages used in this stack now come from `conda-forge` and not `defaults`. Given all of this, it seems safe to drop the `r` channel from explicit addition to the channel list.
