Command-Line Usage

Interactive Prompt

The interactive prompt offers a number of excellent opportunities for exploration of data. While there are challenges for repeatability, and some operations will be more challenging to operate in parallel, interactive prompts can be exceptionally useful for debugging, exploring, and tweaking plots.

You can start up an empty shell, with a handful of useful yt utilities (such as tab-completion and pre-imported modules) by executing:


The other option, which is shorthand for “iyt plus dataset loading” is to use the command-line tool (see Command-Line Usage) with the load subcommand and to specify a dataset. For instance:

yt load cosmoSim_coolhdf5_chk_0026


yt load DD0030/DD0030

This will spawn iyt, but the dataset given on the command line will already be in the namespace as ds. With interactive mode, you can use the pylab module to interactively plot.

Command-line Functions

The yt command-line tool allows you to access some of yt’s basic functionality without opening a python interpreter. The tools is a collection of subcommands. These can quickly making plots of slices and projections through a dataset, updating yt’s codebase, print basic statistics about a dataset, launch an IPython notebook session, and more. To get a quick list of what is available, just type:

yt -h

This will print the list of available subcommands,

help                Print help message
bootstrap_dev       Bootstrap a yt development environment
bugreport           Report a bug in yt
hub_register        Register a user on the Hub:
hub_submit          Submit a mercurial repository to the yt Hub
                    (, creating a BitBucket
                    repo in the process if necessary.
instinfo            Get some information about the yt installation
version             Get some information about the yt installation (this
                    is an alias for instinfo).
load                Load a single dataset into an IPython instance
mapserver           Serve a plot in a GMaps-style interface
pastebin            Post a script to an anonymous pastebin
pastebin_grab       Print an online pastebin to STDOUT for local use.
upload_notebook     Upload an IPython notebook to
plot                Create a set of images
rpdb                Connect to a currently running (on localhost) rpd
                    session. Commands run with --rpdb will trigger an rpdb
                    session with any uncaught exceptions.
notebook            Run the IPython Notebook
stats               Print stats and max/min value of a given field (if
                    requested), for one or more datasets (default field is
update              Update the yt installation to the most recent version
delete_image        Delete image from
upload_image        Upload an image to Must be PNG.

To execute any such function, simply run:

yt <subcommand>

Finally, to identify the options associated with any of these subcommand, run:

yt <subcommand> -h

Plotting from the command line

First, we’ll discuss plotting from the command line, then we will give a brief summary of the functionality provided by each command line subcommand. This example uses the DD0010/moving7_0010 dataset distributed in the yt mercurial repository.

First let’s see what our options are for plotting:

$ yt plot --help

There are many! We can choose whether we want a slice (default) or a projection (-p), the field, the colormap, the center of the image, the width and unit of width of the image, the limits, the weighting field for projections, and on and on. By default the plotting command will execute the same thing along all three axes, so keep that in mind if it takes three times as long as you’d like! The center of a slice defaults to the center of the domain, so let’s just give that a shot and see what it looks like:

$ yt plot DD0010/moving7_0010

Well, that looks pretty bad! What has happened here is that the center of the domain only has some minor shifts in density, so the plot is essentially incomprehensible. Let’s try it again, but instead of slicing, let’s project. This is a line integral through the domain, and for the density field this becomes a column density.:

$ yt plot -p DD0010/moving7_0010

Now that looks much better! Note that all three axes’ projections appear nearly indistinguishable, because of how the two spheres are located in the domain. We could center our domain on one of the spheres and take a slice, as well. Now let’s see what the domain looks like with grids overlaid, using the --show-grids option.:

$ yt plot --show-grids -p DD0010/moving7_0010

We can now see all the grids in the field of view.

Command-line subcommand summary


Help lists all of the various command-line options in yt.


Encountering a bug in your own code can be a big hassle, but it can be exponentially worse to find it in someone else’s. That’s why we tried to make it as easy as possible for users to report bugs they find in yt. After you go through the necessary channels to make sure you’re not just making a mistake (see What to do if you run into problems), you can submit bug reports using this nice utility.

instinfo and version

This gives information about where your yt installation is, what version and changeset you’re using and more.


This will start the iyt interactive environment with your specified dataset already loaded. See Interactive Prompt for more details.


Ever wanted to interact with your data using the google maps interface? Now you can by using the yt mapserver. See Mapserver - A Google-Maps-like Interface to your Data for more details.

pastebin and pastebin_grab

The pastebin is an online location where you can anonymously post code snippets and error messages to share with other users in a quick, informal way. It is often useful for debugging code or co-developing. By running the pastebin subcommand with a text file, you send the contents of that file to an anonymous pastebin;

yt pastebin

By running the pastebin_grab subcommand with a pastebin number (e.g. 1768), it will grab the contents of that pastebin (e.g. the website ) and send it to STDOUT for local use. See Pastebin for more information.

yt pastebin_grab 1768


This command generates one or many simple plots for a single dataset. By specifying the axis, center, width, etc. (run yt help plot for details), you can create slices and projections easily at the command-line.


This command will accept the filename of a .ipynb file (generated from an IPython notebook session) and upload it to the yt hub <> where others will be able to view it, and download it. This is an easy method for recording a sequence of commands, their output, narrative information, and then sharing that with others. These notebooks will be viewable online, and the appropriate URLs will be returned on the command line.


Connect to a currently running (on localhost) rpd session.


Launches an IPython notebook server and prints out instructions on how to open an ssh tunnel to connect to the notebook server with a web browser. This is most useful when you want to run an IPython notebook using CPUs on a remote host.


This subcommand provides you with some basic statistics on a given dataset. It provides you with the number of grids and cells in each level, the time of the dataset, the resolution, and the maximum density in a variety of units. It is tantamount to performing the print_stats() inside of yt.


This subcommand updates the yt installation to the most recent version for your repository (e.g. stable, 2.0, development, etc.). Adding the --all flag will update the dependencies as well.


Images are often worth a thousand words, so when you’re trying to share a piece of code that generates an image, or you’re trying to debug image-generation scripts, it can be useful to send your co-authors a link to the image. This subcommand makes such sharing a breeze. By specifying the image to share, upload_image automatically uploads it anonymously to the website and provides you with a link to share with your collaborators. Note that the image must be in the PNG format in order to use this function.


The image uploaded using upload_image is assigned with a unique hash that can be used to remove it. This subcommand provides an easy way to send a delete request directly to the