Run your data science workloads on high-performance cloud infrastructure in the fewest of steps.
You can download and install the CLI for any of the following platforms.
Supported Platform | Download (Latest) |
---|---|
Windows | Link |
Linux | Link |
macOS | Link |
To download a specific version, visit the releases page.
Run the following commands in the directory to make the CLI accessible from your terminal:
mkdir ~/bin
mv phx-linux ~/bin/phx
echo "export PATH=\"\$PATH:\$HOME/bin\"" >> ~/.bashrc
To make the CLI accessible from your terminal, first create a folder called bin
in your home directory,
then open the environment variables settings by searching environment variables
in the Start Menu and
clicking on Edit the system environment variables
and then clicking on Environment Variables
.
In the opened window, find Path
in the User variables
list and double click on it. Then click on New
to create a new entry in the list.
Paste the following line in the newly created entry:
%USERPROFILE%\bin
Lastly, click OK
for all the opened windows.
Run the following commands to make the CLI accessible from your terminal:
mkdir ~/bin
mv phx-darwin ~/bin/phx
echo "export PATH=\"\$PATH:\$HOME/bin\"" >> ~/.zshrc
First you need to initialize Phoenix in your project directory:
phx init
This will create a .phoenix
folder inside your project root directory.
Next you need to login to the Phoenix Platform by running this command and filling out your credentials in the prompts:
phx login
If you need to login with a static token, you can pass the --static
flag to phx login
:
phx login --static
As easily as that, now your project is ready for the cloud.
You can run a job:
phx run --cluster $CLUSTER_NAME --flavor $FLAVOR_NAME --name $YOUR_JOB_NAME $COMMAND $ARGS
You can also run a Jupyter Notebook on-demand and attach it to Google Colab as an external powerful non-interrupting runtime kernel:
phx jupyter create --cluster $CLUSTER_NAME --flavor $FLAVOR_NAME --name $YOUR_JUPYTER_INSTANCE_NAME
phx jupyter attach
Now, as long as your terminal is open, you can connect your Colab to this runtime using the "Connect to a local runtime" button in Colab interface.
You can read more about how to connect Colab to a local runtime here.
If you had any questions or problems, join our server on Discord.