tf.io.gfile.copy  |  TensorFlow v2.16.1 (original) (raw)

tf.io.gfile.copy

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Copies data from src to dst.

View aliases

Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.io.gfile.copy

tf.io.gfile.copy(
    src, dst, overwrite=False
)

Used in the notebooks

Used in the tutorials
Federated Reconstruction for Matrix Factorization

with open("/tmp/x", "w") as f: f.write("asdf") `` 4 tf.io.gfile.exists("/tmp/x") True tf.io.gfile.copy("/tmp/x", "/tmp/y") tf.io.gfile.exists("/tmp/y") True tf.io.gfile.remove("/tmp/y")

You can also specify the URI scheme for selecting a different filesystem:

with open("/tmp/x", "w") as f: f.write("asdf") `` 4 tf.io.gfile.copy("/tmp/x", "file:///tmp/y") tf.io.gfile.exists("/tmp/y") True tf.io.gfile.remove("/tmp/y")

Note that you need to always specify a file name, even if moving into a new directory. This is because some cloud filesystems don't have the concept of a directory.

with open("/tmp/x", "w") as f: f.write("asdf") `` 4 tf.io.gfile.mkdir("/tmp/new_dir") tf.io.gfile.copy("/tmp/x", "/tmp/new_dir/y") tf.io.gfile.exists("/tmp/new_dir/y") True tf.io.gfile.rmtree("/tmp/new_dir")

If you want to prevent errors if the path already exists, you can useoverwrite argument:

with open("/tmp/x", "w") as f: f.write("asdf") `` 4 tf.io.gfile.copy("/tmp/x", "file:///tmp/y") tf.io.gfile.copy("/tmp/x", "file:///tmp/y", overwrite=True) tf.io.gfile.remove("/tmp/y")

Note that the above will still result in an error if you try to overwrite a directory with a file.

Note that you cannot copy a directory, only file arguments are supported.

Args
src string, name of the file whose contents need to be copied
dst string, name of the file to which to copy to
overwrite boolean, if false it's an error for dst to be occupied by an existing file.
Raises
errors.OpError If the operation fails.