dvc.api.read()

Returns the contents of a tracked file.

def read(path: str,
         repo: str = None,
         rev: str = None,
         remote: str = None,
         mode: str = "r",
         encoding: str = None)

Usage

import dvc.api

modelpkl = dvc.api.read(
    'model.pkl',
    repo='https://github.com/iterative/example-get-started',
    mode='rb'
)

Description

This function wraps dvc.api.open(), for a simple way to return the complete contents of a file tracked in a DVC project. The file can be tracked by DVC (as an output) or by Git.

The returned contents can be a string or a bytearray. These are loaded to memory directly (without using any disc space).

Parameters

• path (required) - location and file name of the target to read, relative to the root of the project (repo).

• repo - specifies the location of the DVC project. It can be a URL or a file system path. Both HTTP and SSH protocols are supported for online Git repos (e.g. [user@]server:project.git). Default: The current project is used (the current working directory tree is walked up to find it).

• rev - Git commit (any revision such as a branch or tag name, commit hash, or experiment name). If repo is not a Git repo, this option is ignored. Default: None (current working tree will be used)

• remote - name of the DVC remote to look for the target data. Default: The default remote of repo is used if a remote argument is not given. For local projects, the cache is tried before the default remote.

• mode - specifies the mode in which the file is opened. Defaults to "r" (read). Mirrors the namesake parameter in builtin open().

• encoding - codec used to decode the file contents to a string. This should only be used in text mode. Defaults to "utf-8". Mirrors the namesake parameter in builtin open().

Exceptions

• dvc.exceptions.FileMissingError - file in path is missing from repo.

• dvc.exceptions.PathMissingError - path cannot be found in repo.

• dvc.exceptions.NoRemoteError - no remote is found.

Example: Load data from a DVC repository

Any file tracked in a DVC project (and stored remotely) can be loaded directly in your Python code with this API. For example, let's say that you want to load and unserialize a binary model from a repo on GitHub:

import pickle
import dvc.api

data = dvc.api.read(
    'model.pkl',
    repo='https://github.com/iterative/example-get-started'
    mode='rb'
)
model = pickle.loads(data)

We're using 'rb' mode here for compatibility with pickle.loads().