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gs-wrap

gs-wrap wraps Google Cloud Storage API for multi-threaded data manipulations.

1.0.5
PyPI

Maintainers: 2

gs-wrap

.. image:: https://badges.frapsoft.com/os/mit/mit.png?v=103 :target: https://opensource.org/licenses/mit-license.php :alt: MIT License

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gs-wrap wraps Google Cloud Storage API <https://cloud.google.com/storage/>_ for multi-threaded data manipulation including copying, reading, writing and hashing.

Originally, we used our gsutilwrap <https://github.com/Parquery/gsutilwrap/>_, a thin wrapper around gsutil command-line interface, to simplify the deployment and backup tasks related to Google Cloud Storage. However, gsutilwrap was prohibitively slow at copying many objects into different destinations.

Therefore we developed gs-wrap to accelerate these operations while keeping it equally fast or faster than gsutilwrap at other operations.

While the google-cloud-storage <https://github.com/googleapis/google-cloud-python/tree/master/storage/>_ library provided by Google offers sophisticated features and good performance, its use cases and behavior differ from gsutil. Since we wanted the simplicity and usage patterns of gsutil, we created gs-wrap, which wraps google-cloud-storage in its core and with its interface set to behave like gsutil.

gs-wrap is not the first Python library wrapping Google Cloud Storage API. cloud-storage-client <https://github.com/Rakanixu/cloud-storage-client/>_ takes a similar approach and aims to manage both Amazon's S3 and Google Cloud Storage. Parts of it are also based on google-cloud-storage, however the library's behaviour differs from gsutil which made it hard to use as an in-place replacement for gsutilwrap. Additionally, the library did not offer all needed operations, for example copying to many destinations, reading, writing and hashing.

The main strength of gs-wrap is the ability to copy many objects from many different paths to multiple destinations, while still mimicking gsutil interface. A direct comparison of performance between gs-wrap and gsutilwrap can be found in the section Benchmarks <https://github.com/Parquery/gs-wrap#benchmarks>_.

Usage

You need to create a Google Cloud Storage bucket to use this client library. Follow along with the official Google Cloud Storage documentation <https://cloud.google.com/storage/docs/cloud-console#_creatingbuckets>_ to learn how to create a bucket.

Connect to your Google Cloud Storage bucket

First a client for interacting with the Google Cloud Storage API needs to be created. This one uses internally the Storage Client <https://googleapis.github.io/google-cloud-python/latest/storage/client.html#google.cloud.storage.client.Client/>_ from google-cloud-storage.

One parameter can be passed to the client:

The Google Cloud Storage project which the client acts on behalf of. It will be passed when creating the internal client. If not passed, falls back to the default inferred from the locally authenticated Google Cloud SDK <http://cloud.google.com/sdk>_ environment. Each project needs a separate client. Operations between two different projects are not supported.

.. code-block:: python

import gswrap

client = gswrap.Client() # project is optional

List objects in your bucket

.. warning::

Wildcards (\*, \*\*, \?, \[chars\], \[char range\]) are not supported by
Google Cloud Storage API and neither by ``gs-wrap`` at the moment
[2019-01-16]. Reasons are that the ``gsutil`` with wildcards can hardly be
equivalently reconstructed and that the toplevel search is extremely
inefficient. More information about ``gsutil`` wildcards can be found here:
`<https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames>`_

.. code-block:: python

client.ls(gcs_url="gs://your-bucket/your-dir", recursive=False)
# gs://your-bucket/your-dir/your-subdir1/
# gs://your-bucket/your-dir/your-subdir2/
# gs://your-bucket/your-dir/file1

client.ls(gcs_url="gs://your-bucket/your-dir", recursive=True)
# gs://your-bucket/your-dir/your-subdir1/file1
# gs://your-bucket/your-dir/your-subdir1/file2
# gs://your-bucket/your-dir/your-subdir2/file1
# gs://your-bucket/your-dir/file1

Copy objects within Google Cloud Storage

If both the source and destination URL are cloud URLs from the same provider, gsutil copies data "in the cloud" (i.e. without downloading to and uploading from the machine where you run gs-wrap).

.. note:: client.cp() runs single-threaded by default. When multi-threading is activated, the maximum number of workers is the number of processors on the machine, multiplied by 5. This is the multi-threading default of the ThreadPoolExecuter from the concurrent.futures library <https://docs.python.org/3.5/library/concurrent.futures.html#concurrent.futures.ThreadPoolExecutor>_.

Copy file within Google Cloud Storage

.. code-block:: python

# your-bucket before:
# gs://your-bucket/file1
client.cp(src="gs://your-bucket/file1",
          dst="gs://your-bucket/your-dir/",
          recursive=True)
# your-bucket after:
# gs://your-bucket/file1
# gs://your-bucket/your-dir/file1

# your-backup-bucket before:
# "empty"
client.cp(src="gs://your-bucket/file1",
          dst="gs://your-backup-bucket/backup-file1",
          recursive=False)
# your-backup-bucket after:
# gs://your-backup-bucket/backup-file1

Copy directory within Google Cloud Storage

.. code-block:: python

# your-bucket before:
# "empty"
client.cp(src="gs://your-bucket/some-dir/",
dst="gs://your-bucket/another-dir/", recursive=False)
# google.api_core.exceptions.GoogleAPIError: No URLs matched

# your-bucket before:
# gs://your-bucket/some-dir/file1
# gs://your-bucket/some-dir/dir1/file11

# Destination URL without slash
client.cp(src="gs://your-bucket/some-dir/",
dst="gs://your-bucket/another-dir", recursive=True)
# your-bucket after:
# gs://your-bucket/another-dir/file1
# gs://your-bucket/another-dir/dir1/file11

# Destination URL with slash
client.cp(src="gs://your-bucket/some-dir/",
dst="gs://your-bucket/another-dir/", recursive=True)
# your-bucket after:
# gs://your-bucket/another-dir/some-dir/file1
# gs://your-bucket/another-dir/some-dir/dir1/file11

# Choose to copy multi-threaded. (default=False)
client.cp(src="gs://your-bucket/some-dir/",
dst="gs://your-bucket/another-dir", recursive=True, multithreaded=True)
# your-bucket after:
# gs://your-bucket/another-dir/file1
# gs://your-bucket/another-dir/dir1/file11

Upload objects to Google Cloud Storage

.. note::

**recursive** causes directories, buckets, and bucket subdirectories to be
copied recursively. If you upload from local disk to Google Cloud Storage
and set recursive to ``False``, ``gs-wrap``
will raise an exception and inform you that no URL matched.
This mimicks the behaviour of ``gsutil`` when no wildcards are used.

.. code-block:: python

# Your local directory:
# /home/user/storage/file1
# /home/user/storage/file2
# your-bucket before:
# "empty"

client.cp(src="/home/user/storage/",
          dst="gs://your-bucket/local/",
          recursive=True)
# your-bucket after:
# gs://your-bucket/local/storage/file1
# gs://your-bucket/local/storage/file2

Download objects from Google Cloud Storage

.. note::

**recursive** causes directories, buckets, and bucket subdirectories to be
copied recursively. If you upload from local disk to Google Cloud Storage
and set recursive to ``False``, ``gs-wrap``
will raise an exception and inform you that no URL matched.
This mimicks the behaviour of ``gsutil`` when no wildcards are used.

.. code-block:: python

import os
# Current your-bucket:
# gs://your-bucket/file1

client.cp(
    src="gs://your-bucket/file1", 
    dst="/home/user/storage/file1")

# Your local directory:
# /home/user/storage/file1

Copy, download and upload with parameters

.. note::

All parameters can be used for any kind of ``cp`` operation.

.. code-block:: python

# Parameter: no_clobber example:
import os

# File content before: "hello"
os.stat("/home/user/storage/file1").st_mtime # 1537947563

client.cp(
    src="gs://your-bucket/file1",
    dst="/home/user/storage/file1",
    no_clobber=True)

# no_clobber option stops from overwriting.
# File content after: "hello"
os.stat("/home/user/storage/file1").st_mtime # 1537947563

client.cp(
    src="gs://your-bucket/file1",
    dst="/home/user/storage/file1",
    no_clobber=False)

# File content after: "hello world"
os.stat("/home/user/storage/file1").st_mtime # 1540889799

# Parameter: recursive and multi-threaded example:
# Your local directory:
# /home/user/storage/file1
# ...
# /home/user/storage/file1000
# your-bucket before:
# "empty"

# Execute normal recursive copy in multiple threads.
client.cp(src="/home/user/storage/",
          dst="gs://your-bucket/local/",
          recursive=True, multithreaded=True)
# your-bucket after:
# gs://your-bucket/local/storage/file1
# ...
# gs://your-bucket/local/storage/file1000

# Parameter: preserve_posix example:
# Your file before:
# /home/user/storage/file1
# e.g. file_mtime: 1547653413 equivalent to 2019-01-16 16:43:33

client.cp(src="/home/user/storage/file1",
          dst="gs://your-backup-bucket/file1",
          preserve_posix=False)
# your-backup-bucket after:
# gs://your-backup-bucket/file1 e.g. "no metadata file_mtime"

# Preserve the POSIX attributes. POSIX attributes are the metadata of a file.
client.cp(src="/home/user/storage/file1",
          dst="gs://your-backup-bucket/file1",
          preserve_posix=True)
# your-backup-bucket after:
# gs://your-backup-bucket/file1 e.g. file_mtime: 2019-01-16 16:43:33

Perform multiple copy operations in one call

.. code-block:: python

sources_destinations = [
    # Copy on Google Cloud Storage
    ('gs://your-bucket/your-dir/file',
     'gs://your-bucket/backup-dir/file'),
    
    # Copy from gcs to local
    ('gs://your-bucket/your-dir/file',
     pathlib.Path('/home/user/storage/backup-file')),
    
    # Copy from local to gcs
    (pathlib.Path('/home/user/storage/new-file'),
     'gs://your-bucket/your-dir/new-file'),
    
    # Copy locally
    (pathlib.Path('/home/user/storage/file'),
     pathlib.Path('/home/user/storage/new-file'))]

client.cp_many_to_many(srcs_dsts=sources_destinations)

Remove files from Google Cloud Storage

.. code-block:: python

# your-bucket before:
# gs://your-bucket/file
client.rm(url="gs://your-bucket/file")
# your-bucket after:
# "empty"

# your-bucket before:
# gs://your-bucket/file1
# gs://your-bucket/your-dir/file2
# gs://your-bucket/your-dir/sub-dir/file3
client.rm(url="gs://your-bucket/your-dir", recursive=True)
# your-bucket after:
# gs://your-bucket/file1

Read and write files in Google Cloud Storage

.. code-block:: python

client.write_text(url="gs://your-bucket/file",
                  text="Hello, I'm text",
                  encoding='utf-8')

client.read_text(url="gs://your-bucket/file", 
                 encoding='utf-8')
# Hello I'm text

client.write_bytes(url="gs://your-bucket/data",
                   data="I'm important data".encode('utf-8'))

data = client.read_bytes(url="gs://your-bucket/data")
data.decode('utf-8')
# I'm important data

Copy os.stat() of a file or metadata of a blob

.. note::

POSIX attributes include meta information about a file. When copying a file
locally or copying a file within Google Cloud Storage, the POSIX attributes
are always preserved. On the other hand, when downloading or uploading file
to Google Cloud Storage, the POSIX attributes is only preserved when
**preserve_posix** is set to True.

.. code-block:: python

file = pathlib.Path('/home/user/storage/file')
file.touch()
print(file.stat())
# os.stat_result(st_mode=33204, st_ino=19022665, st_dev=64769, st_nlink=1,
# st_uid=1000, st_gid=1000, st_size=0, st_atime=1544015997,
# st_mtime=1544015997, st_ctime=1544015997)

# Upload does not preserve POSIX attributes.
client.cp(src=pathlib.Path('/home/user/storage/file'),
          dst="gs://your-bucket/file")

stats = client.stat(url="gs://your-bucket/file")
stats.creation_time  # 2018-11-21 13:27:46.255000+00:00
stats.update_time  # 2018-11-21 13:27:46.255000+00:00
stats.content_length  # 1024 [bytes]
stats.storage_class  # REGIONAL
stats.file_atime  # None
stats.file_mtime  # None
stats.posix_uid  # None
stats.posix_gid  # None
stats.posix_mode  # None
stats.md5  # b'1B2M2Y8AsgTpgAmY7PhCfg=='
stats.crc32c  # b'AAAAAA=='

# Upload with preserve_posix also copy POSIX attributes to blob.
# POSIX attributes are the metadata of a file.
# It also works for downloading.

client.cp(src=pathlib.Path('/home/user/storage/file'),
            dst="gs://your-bucket/file", preserve_posix=True)

stats = client.stat(url="gs://your-bucket/file")
stats.creation_time  # 2018-11-21 13:27:46.255000+00:00
stats.update_time  # 2018-11-21 13:27:46.255000+00:00
stats.content_length  # 1024 [bytes]
stats.storage_class  # REGIONAL
stats.file_atime  # 2018-11-21 13:27:46
stats.file_mtime  # 2018-11-21 13:27:46
stats.posix_uid  # 1000
stats.posix_gid  # 1000
stats.posix_mode  # 777
stats.md5  # b'1B2M2Y8AsgTpgAmY7PhCfg=='
stats.crc32c  # b'AAAAAA=='

Check correctness of copied file

.. code-block:: python

# Check modification time when copied with preserve_posix.
client.same_modtime(path='/home/user/storage/file',
                    url='gs://your-bucket/file')

# Check md5 hash to ensure content equality.
client.same_md5(path='/home/user/storage/file', url='gs://your-bucket/file')

# Retrieve hex digests of MD5 checksums for multiple URLs.
urls = ['gs://your-bucket/file1', 'gs://your-bucket/file2']
client.md5_hexdigests(urls=urls, multithreaded=False)

Documentation

The documentation is available on readthedocs <https://gs-wrap.readthedocs.io/en/latest/>_.

Setup

In order to use this library, you need to go through the following steps:

Select or create a Cloud Platform project. <https://console.cloud.google.com/project>_
Enable billing for your project. <https://console.cloud.google.com/project>_
Enable the Google Cloud Storage API. <https://cloud.google.com/storage>_
Setup Authentication using the Google Cloud SDK. <https://googlecloudplatform.github.io/google-cloud-python/latest/core/auth.html>_

Installation

Install gs-wrap with pip:

.. code-block:: bash

pip3 install gs-wrap

Development

Check out the repository.
In the repository root, create the virtual environment:

.. code-block:: bash

python3 -m venv venv3

Activate the virtual environment:

.. code-block:: bash

source venv3/bin/activate

Install the development dependencies:

.. code-block:: bash

pip3 install -e .[dev]

We use tox for testing and packaging the distribution. Assuming that the virtual environment has been activated and the development dependencies have been installed, run:

.. code-block:: bash

tox

Pre-commit Checks

We provide a set of pre-commit checks that lint and check code for formatting.

Namely, we use:

yapf <https://github.com/google/yapf>_ to check the formatting.
The style of the docstrings is checked with pydocstyle <https://github.com/PyCQA/pydocstyle>_.
Static type analysis is performed with mypy <http://mypy-lang.org/>_.
isort <https://github.com/timothycrosley/isort>_ to sort your imports for you.
Various linter checks are done with pylint <https://www.pylint.org/>_.
Doctests are executed using the Python doctest module <https://docs.python.org/3.5/library/doctest.html>_.
pyicontract-lint <https://github.com/Parquery/pyicontract-lint/>_ lints contracts in Python code defined with icontract library <https://github.com/Parquery/icontract/>_.
twine <https://pypi.org/project/twine/>_ to check the README for invalid markup which prevents it from rendering correctly on PyPI.

Run the pre-commit checks locally from an activated virtual environment with development dependencies:

.. code-block:: bash

./precommit.py

The pre-commit script can also automatically format the code:

.. code-block:: bash

./precommit.py  --overwrite

Benchmarks

Assuming that the virtual environment has been activated, the development dependencies have been installed and the PYTHONPATH has been set to the project directory, run the benchmarks with:

.. code-block:: bash

./benchmark/main.py *NAME OF YOUR GCS BUCKET*

Here are some of our benchmark results:

Benchmark list 10000 files:

+------------+--------+---------+ | TESTED | TIME | SPEEDUP | +------------+--------+---------+ | gswrap | 3.22 s | - | +------------+--------+---------+ | gsutilwrap | 3.98 s | 1.24 x | +------------+--------+---------+

Benchmark upload 10000 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 45.12 s | - | +------------+---------+---------+ | gsutilwrap | 34.85 s | 0.77 x | +------------+---------+---------+

Benchmark upload-many-to-many 500 files:

+------------+--------+---------+ | TESTED | TIME | SPEEDUP | +------------+--------+---------+ | gswrap | 2.14 s | - | +------------+--------+---------+ | gsutilwrap | 65.2 s | 30.49 x | +------------+--------+---------+

Benchmark download 10000 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 43.92 s | - | +------------+---------+---------+ | gsutilwrap | 43.01 s | 0.98 x | +------------+---------+---------+

Benchmark download-many-to-many 500 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 5.85 s | - | +------------+---------+---------+ | gsutilwrap | 62.93 s | 10.76 x | +------------+---------+---------+

Benchmark copy on remote 1000 files:

+------------+--------+---------+ | TESTED | TIME | SPEEDUP | +------------+--------+---------+ | gswrap | 5.09 s | - | +------------+--------+---------+ | gsutilwrap | 4.47 s | 0.88 x | +------------+--------+---------+

Benchmark copy-many-to-many-on-remote 500 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 6.55 s | - | +------------+---------+---------+ | gsutilwrap | 62.76 s | 9.57 x | +------------+---------+---------+

Benchmark remove 1000 files:

+------------+--------+---------+ | TESTED | TIME | SPEEDUP | +------------+--------+---------+ | gswrap | 3.16 s | - | +------------+--------+---------+ | gsutilwrap | 3.66 s | 1.16 x | +------------+--------+---------+

Benchmark read 100 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 16.56 s | - | +------------+---------+---------+ | gsutilwrap | 64.73 s | 3.91 x | +------------+---------+---------+

Benchmark write 30 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 2.67 s | - | +------------+---------+---------+ | gsutilwrap | 32.55 s | 12.17 x | +------------+---------+---------+

Benchmark stat 100 files:

+------------+---------+---------+ | TESTED | TIME | SPEEDUP | +------------+---------+---------+ | gswrap | 6.39 s | - | +------------+---------+---------+ | gsutilwrap | 48.15 s | 7.53 x | +------------+---------+---------+

All results of our benchmarks can be found here <https://github.com/Parquery/gs-wrap/blob/master/benchmark/benchmark_results>_.

Versioning

We follow Semantic Versioning <http://semver.org/spec/v1.0.0.html>_. The version X.Y.Z indicates:

X is the major version (backward-incompatible),
Y is the minor version (backward-compatible), and
Z is the patch version (backward-compatible bug fix).

Keywords

gsutil google cloud storage wrap

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Install

gs-wrap

gs-wrap

Usage

Connect to your Google Cloud Storage bucket

List objects in your bucket

Copy objects within Google Cloud Storage

Copy file within Google Cloud Storage

Copy directory within Google Cloud Storage

Upload objects to Google Cloud Storage

Download objects from Google Cloud Storage

Copy, download and upload with parameters

Perform multiple copy operations in one call

Remove files from Google Cloud Storage

Read and write files in Google Cloud Storage

Copy os.stat() of a file or metadata of a blob

Check correctness of copied file

Documentation

Setup

Installation

Development

Pre-commit Checks

Benchmarks

Versioning

Keywords

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