gs-wrap 1.0.0

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 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 environment. Each project needs a separate client. Operations between two different projects are not supported.

import gswrap

client = gswrap.Client() # project is optional

List objects in your bucket

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).

Copy file within Google Cloud Storage

# 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

# 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

# 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

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

# 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

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

# 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

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

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

# 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)

Pre-commit Checks

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

Namely, we use:

• yapf to check the formatting.

• The style of the docstrings is checked with pydocstyle.

• Static type analysis is performed with mypy.

• isort to sort your imports for you.

• Various linter checks are done with pylint.

• Doctests are executed using the Python doctest module.

• pyicontract-lint lints contracts in Python code defined with icontract library.

• 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:

./precommit.py

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

./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:

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

Here are some of our benchmark results:

Benchmark list 10000 files:

Benchmark upload 10000 files:

Benchmark upload-many-to-many 500 files:

Benchmark download 10000 files:

Benchmark download-many-to-many 500 files:

Benchmark copy on remote 1000 files:

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

Benchmark remove 1000 files:

Benchmark read 100 files:

Benchmark write 30 files:

Benchmark stat 100 files:

All results of our benchmarks can be found here.