list
Aliased to
dvc ls
.
List project contents, including files, models, and directories tracked by DVC and by Git.
Useful to find data to
dvc get
,dvc import
, or fordvc.api
functions.
Synopsis
usage: dvc list [-h] [-q | -v] [-R|-T] [-L depth] [--dvc-only]
[--json] [--rev [<commit>]]
[--config <path>] [--remote <name>]
[--remote-config [<name>=<value> ...]]
[--size] [--show-hash]
url [path]
positional arguments:
url Location of DVC or Git repository to list from
path Path to a file or directory in the repository
Description
Produces a view of a DVC repository (usually online), listing data
files and directories tracked by DVC alongside the remaining Git repo contents.
This is useful because when you browse a hosted repository (e.g. on GitHub or
with git ls-remote
), you only see the dvc.yaml
and .dvc
files with your
code (files tracked by Git).
This command's output is equivalent to cloning the repo and pulling the data (except that nothing is downloaded), like this:
$ git clone <url> example
$ cd example
$ dvc pull
$ ls <path>
The url
argument specifies the address of the DVC or Git repository containing
the data source. Both HTTP and SSH protocols are supported (e.g.
[user@]server:project.git
). url
can also be a local file system path
(including the current project e.g. .
). Any path inside a DVC project will be
resolved to the project's root.
The optional path
argument specifies a file or directory to list (paths inside
tracked directories are supported). It should be relative to the root of the
repo (absolute paths are supported when url
is local). This is similar to
providing a path to listing commands such as ls
or aws s3 ls
.
Only the root directory is listed by default, but the -R
option can be used to
list files recursively.
Note that dvc list
doesn't check whether the listed data (tracked by DVC)
actually exists in remote storage, so it's not guaranteed whether it can be
accessed with dvc get
, dvc import
, or dvc.api
.
Options
-
-R
,--recursive
- recursively list files in all subdirectories. -
-T
,--tree
- recurse into directories as a tree. -
-L
,--level <depth>
- limit the depth of recursion. -
--dvc-only
- show only DVC-tracked files and directories (outputs). -
--rev <commit>
- commit hash, branch or tag name, etc. (any Git revision) of the repository to list content for. The latest commit (in the default branch) is used by default when this option is not specified. -
--json
- prints the command's output in easily parsable JSON format, instead of a human-readable table. -
--config <path>
- path to a config file that will be merged with the config in the target repository. -
--remote <name>
- name of thedvc remote
to set as a default in the target repository. -
--remote-config [<name>=<value> ...]
-dvc remote
config options to merge with a remote's config (default or one specified by--remote
) in the target repository. -
--size
- show sizes. -
--show-hash
- show hash value of each item. -
-h
,--help
- prints the usage/help message, and exit. -
-q
,--quiet
- do not write anything to standard output. Exit with 0 if no problems arise, otherwise 1. -
-v
,--verbose
- displays detailed tracing information. when this option is not specified.
Example: Find files to download from a repository
We can use this command for getting information about a repository before using
other commands like dvc get
or dvc import
to reuse any file or directory
found in it. This includes files (or directories) tracked by DVC or by Git:
$ dvc list https://github.com/iterative/example-get-started
.dvcignore
.gitignore
README.md
data
dvc.lock
dvc.yaml
model.pkl
params.yaml
prc.json
scores.json
src
If you open the
example-get-started
project's page, you will see a similar list but not the model.pkl
file. It's
tracked by DVC and not visible to Git. It's exported in the dvc.yaml
file as
an output of the train
stage (in the outs
field).
We can now, for example, download the model file with:
$ dvc get https://github.com/iterative/example-get-started model.pkl
Example: List all files in a data registry
Let's imagine a DVC repo used as a
data registry, structured with
different datasets in separate directories. We can do this recursively, using
-R
option:
$ dvc list -R https://github.com/iterative/dataset-registry
.gitignore
README.md
get-started/.gitignore
get-started/data.xml
get-started/data.xml.dvc
images/.gitignore
images/dvc-logo-outlines.png
images/dvc-logo-outlines.png.dvc
images/owl_sticker.png
...
Example: Create an archive of your DVC project
Just like you can use git archive
to make a quick bundle (ZIP) file of the
current code, dvc list
can be easily complemented with simple archive tools to
bundle the current data files in the project.
For example, here's a TAR archive of the entire workspace (Linux/GNU):
$ dvc list . -R | tar -cvf project.tar
Or separate ZIP archives of code and DVC-tracked data (POSIX terminal with
zip
):
$ git archive -o code.zip HEAD
$ dvc list . -R --dvc-only | zip -@ data.zip
ZIP alternative for POSIX on Windows (Python installed):
$ dvc list . -R --dvc-only | xargs python -m zipfile -c data.zip
Example: Set AWS profile for default remote
$ dvc list https://github.com/iterative/example-get-started-s3 data/prepared --remote-config profile=myprofile
Example: Set default remote
$ dvc list https://github.com/iterative/example-get-started-s3 data/prepared --remote myremote