You will run everything through an ssh terminal, using a command line interface. It is much bigger: lsdtt-alpine is an 88 Mb download and ~240Mb unpacked. All of them can be conda installed. Note that we use --yes to automatically answer y if and when conda asks for user confirmation For various reasons that I'll outline more fully below, this will not generally work if you want to use these installed packages from the current notebook, though it may work in the simplest cases. Use Docker to package your Python Flask app and your Conda environment.
We also want to copy files such as our code and environment. Or if you have GitHub Desktop, you can use that instead. It is a package manager that is both cross-platform and language agnostic it can play a similar role to a pip and virtualenv combination. If we want to modify the original Dockerfile we must skip the first line. Conda attempts to install the newest versions of the requested packages. This isn't super important for this image, but becomes more important if multiple rounds of conda install commands are used.
This makes it totally unusable so we are going to have to add some stuff to the docker file. The following lines copy the file into the Docker image. In line with , all pandas releases through December 31, 2018 will support Python 2. Otherwise you would adjust iptables for this. We can see this by printing the sys.
I have a few ideas, some of which might even be useful: Potential Changes to Jupyter As I mentioned, the fundamental issue is a mismatch between Jupyter's shell environment and compute kernel. Click Open Workbench and launch a session. Not all base boxes work! Take care to install the 64 bits version of Python, since we will be going to compile for 64 bits. Therefore, we want to run a production-ready webserver which Gunicorn is. We have updated the vagrantfiles to Ubuntu 14 so you should use the new vagrantfiles this will require downloading a new vagrant box if you were using the old vagrantfile. In other words, the Jupyter notebook, like all abstractions, is leaky.
If this fails with a message about not finding caffe2. Note the troubleshooting info below… the install path with Python can get difficult. Just note that you might have issues with package location and versioning with Anaconda. Almost all flavours of Linux come with python installed as default the Ubuntu system installed by our vagrantfiles is one example so we will assume you have python. However, through the either virtualisation or containers you can build a Linux environment within any operating system.
You can read more about Conda. The second run command activates the created Conda environment. . First you will need to be installed and downloading and running the will do this for you. Our instructions assume you are using virtual box. The setup script is a python script so you need python to run it. It is big: the download is 644 Mb and built it is over 2 Gb.
It is an 88 Mb download and when built, it is a but under 300 Mb. This post will focus on two approaches to installing Python packages: and. This server will run even if you are using a different operating system e. Start the Docker image by running the following command. Conda as a package manager helps you find and install packages. The exception is the special case where you run jupyter notebook from the same Python environment to which your kernel points; in that case the simple installation approach should work.
These are things that are included in a conda package, but you may not need and end up just taking up space. New Jupyter Magic Functions Even if the above changes to the stack are not possible or desirable, we could simplify the user experience somewhat by introducing %pip and %conda magic functions within the Jupyter notebook that detect the current kernel and make certain packages are installed in the correct location. As of 01-Nov-2017 Vagrant does not work with VirtualBox 5. We will start with an incredibly simple one. Usually over 500Mb each is a fully operational linux operating system. If you do not wish to use Anaconda, then you must build Caffe2 from. Make sure that folder is in the correct place and is spelled correctly remember it should be case sensitive!! The installation instructions for will probably also work in most cases.
Then, the defaults or channels from. This can be done on a Mac via brew install automake libtool or on Ubuntu via sudo apt-get install automake libtool. The name of the environment when it is created, what channels the libraries will be downloaded from and finally what Python version and libraries to install. These packages are built on Ubuntu 16. Download Caffe2 Source If you have not done so already, download the Caffe2 source code from GitHub 1 2 cd caffe2.
You can also install Anaconda system wide, which does require administrator permissions. Make sure you download Virtualbox 5. The much easier path it to use from the wonderful people at. You now have a functioning Vagrant box!! They are several hundred Mb each! I probably missed something with the configuration for automated dependencies install. Here i'm making some tests with the bedtools, without manual installation of the bedtools, and my jobs are red saying that the tool is not found. But that leaves us in an undesireable place, as it increases the learning curve for novice users who may want to do something they rightly presume should be simple: install a package and then use it.