aind-data-transfer 0.9.1

Services for compression and transfer of aind-data to the cloud

aind-data-transfer

Tools for transferring large data to and between cloud storage providers.

Installation

To upload data to aws s3, you may need to install and configure awscli. To upload data to gcp, you may need to install and configure gsutil.

Generic upload

You may need to first install pyminizip from conda if getting errors on Windows: conda install -c mzh pyminizip

• From PyPI: pip install aind-data-transfer
• From source: pip install -e .

Imaging

• Run pip install -e .[imaging]
• Run ./post_install.sh

Ephys

• From PyPI: pip install aind-data-transfer[ephys]
• From source pip install -e .[ephys]

Full

• Run pip install -e .[full]
• Run ./post_install.sh

Development

• Run pip install -e .[dev]
• Run ./post_install.sh

MPI

To run scripts on a cluster, you need to install dask-mpi. This requires compiling mpi4py with the MPI implementation used by your cluster (Open MPI, MPICH, etc). The following example is for the Allen Institute HPC, but should be applicable to other HPC systems.

SSH into your cluster login node

ssh user.name@hpc-login

On the Allen cluster, the MPI modules are only available on compute nodes, so SSH into a compute node (n256 chosen arbitrarily).

ssh user.name@n256

Now load the MPI module and compiler. It is important that you use the latest MPI version and compiler, or else dask-mpi may not function properly.

module load gcc/10.1.0-centos7 mpi/mpich-3.2-x86_64

Install mpi4py

python -m pip install --no-cache-dir mpi4py

Now install dask-mpi

python -m pip install dask_mpi --upgrade

Usage

Generic Upload Job

This job will copy the contents of a data_folder to a bucket and s3 folder with the format modality_subject_id_date_time. It will also attempt to create and upload metadata for the subject_id and register the s3 folder to a code ocean platform.

Required arguments

python -m aind_data_transfer.jobs.s3_upload_job --data-source "path_to_data_folder" --s3-bucket "s3_bucket" --subject-id "12345" --modality "test_phys" --acq-date "2022-12-21" --acq-time "12-00-00"
python -m aind_data_transfer.jobs.s3_upload_job -d "path_to_data_folder" -b "s3_bucket" -s "12345" -m "test_phys" -a "2022-12-21" -t "12-00-00"

Optional aws region (defaults to us-west-2)

python -m aind_data_transfer.jobs.s3_upload_job ... --s3-region "us-east-1"
python -m aind_data_transfer.jobs.s3_upload_job ... -r "us-east-1"

Optional service endpoints (defaults to retrieving from AWS Secrets Manager. None if not found.)

python -m aind_data_transfer.jobs.s3_upload_job ... --service-endpoints '{"metadata_service_url":"http://something","codeocean_domain":"https://codeocean.acme.org","codeocean_trigger_capsule":"abc-123"}'
python -m aind_data_transfer.jobs.s3_upload_job ... -e '{"metadata_service_url":"http://something","codeocean_domain":"https://codeocean.acme.org","codeocean_trigger_capsule":"abc-123"}'

Optional behavior directory (None if not set). This will upload files from this directory to a folder called {s3_bucket}/{s3_prefix}/behavior in s3. The uploaded video files will be encrypted.

python -m aind_data_transfer.jobs.s3_upload_job ... --behavior-dir "/home/some_folder"
python -m aind_data_transfer.jobs.s3_upload_job ... -v "/home/some_folder"

Optional metadata directory (None if not set). This will upload files from this directory to a folder called {s3_bucket}/{s3_prefix} in s3. Files generated by aind-metadata-service will take precedence by default.

python -m aind_data_transfer.jobs.s3_upload_job ... --metadata-dir "/home/some_metadata_folder"
python -m aind_data_transfer.jobs.s3_upload_job ... -x "/home/some_metadata_folder"

Optional metadata directory force (False if not set). Force job to use metadata files defined in metadata-dir over the ones generated by aind-metadata-service.

python -m aind_data_transfer.jobs.s3_upload_job ... --metadata-dir "/home/some_metadata_folder" --metadata-dir-force
python -m aind_data_transfer.jobs.s3_upload_job ... -x "/home/some_metadata_folder" --metadata-dir-force

Optional dry run (defaults to False.) If flag is set, dry-run is set to True. It will perform the operations without actually uploading or triggering the codeocean capsule. It will check that the job can hit the endpoints correctly and give a preview of the upload/trigger results:

python -m aind_data_transfer.jobs.s3_upload_job ... --dry-run

The CodeOcean API Token can be set as an env var CODEOCEAN_API_TOKEN. Otherwise, it will be retrieved from AWS Secrets.

Multiple Generic Upload Jobs

You can also define the job parameters in a csv file.

python -m aind_data_transfer.jobs.s3_upload_job --jobs-csv-file "path_to_jobs_list"
python -m aind_data_transfer.jobs.s3_upload_job -j "path_to_jobs_list"
python -m aind_data_transfer.jobs.s3_upload_job ... --dry-run

The csv file should look something like:

data-source, s3-bucket, subject-id, modality, acq-date, acq-time
dir/data_set_1, some_bucket, 123454, test_phys, 2020-10-10, 14-10-10
dir/data_set_2, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10

Alternatively, you can define the behavior directories also (leave the field blank to ignore the setting. Also, it's fine if it's a subfolder of the data-source)

data-source, s3-bucket, subject-id, modality, acq-date, acq-time, behavior-dir
dir/data_set_1, some_bucket, 123454, test_phys, 2020-10-10, 14-10-10, dir/data_set_1/Videos
dir/data_set_2, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10, dir/alt_dir
dir/data_set_3, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10,

Alternatively, you can define the metadata directories also (leave the field blank to ignore the setting. Also, it's fine if it's a subfolder of the data-source)

data-source, s3-bucket, subject-id, modality, acq-date, acq-time, metadata-dir
dir/data_set_1, some_bucket, 123454, test_phys, 2020-10-10, 14-10-10, dir/metadata_dir1
dir/data_set_2, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10, dir/metadata_dir2
dir/data_set_3, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10,

Another example with mixing and matching optional directories:

data-source, s3-bucket, subject-id, modality, acq-date, acq-time, behavior-dir, metadata-dir, metadata-dir-force
dir/data_set_1, some_bucket, 123454, test_phys, 2020-10-10, 14-10-10, dir/data_set_1/Videos, dir/metadata_dir1, True
dir/data_set_2, some_bucket, 123456, test_phys, 2020-10-11, 13-10-10, dir/alt_dir, dir/metadata_dir2, False
dir/data_set_3, some_bucket, 123456, test, 2020-10-11, 13-10-10, , dir/metadata_dir3
dir/data_set_4, some_bucket, 123457, mri, 2020-10-12, 15-10-10, , dir/metadata_dir4, True
dir/data_set_5, some_bucket, 123458, test, 2020-10-12, 16-10-10, dir/behavior_dir_5

Contributing

Linters and testing

There are several libraries used to run linters, check documentation, and run tests.

• Please test your changes using the coverage library, which will run the tests and log a coverage report:

coverage run -m unittest discover && coverage report

• Use interrogate to check that modules, methods, etc. have been documented thoroughly:

interrogate .

• Use flake8 to check that code is up to standards (no unused imports, etc.):

flake8 .

• Use black to automatically format the code into PEP standards:

black .

• Use isort to automatically sort import statements:

isort .

Pull requests

For internal members, please create a branch. For external members, please fork the repo and open a pull request from the fork. We'll primarily use Angular style for commit messages. Roughly, they should follow the pattern:

<type>(<scope>): <short summary>

where scope (optional) describes the packages affected by the code changes and type (mandatory) is one of:

• build: Changes that affect the build system or external dependencies (example scopes: pyproject.toml, setup.py)
• ci: Changes to our CI configuration files and scripts (examples: .github/workflows/ci.yml)
• docs: Documentation only changes
• feat: A new feature
• fix: A bug fix
• perf: A code change that improves performance
• refactor: A code change that neither fixes a bug nor adds a feature
• test: Adding missing tests or correcting existing tests