aind-metadata-service

REST service to retrieve metadata from databases.

Installation

Server Installation

Can be pip installed using pip install "aind-metadata-service[server]".

Installing pyodbc.

• You may need to install unixodbc-dev. You can follow this https://learn.microsoft.com/en-us/sql/connect/odbc/linux-mac/installing-the-microsoft-odbc-driver-for-sql-server?view=sql-server-ver16 for instructions depending on your os.

• You may need to run docker system prune before building the docker image if you're getting errors running apt-get:

#10 23.69 Err:1 http://deb.debian.org/debian bullseye/main amd64 libodbc1 amd64 2.3.6-0.1+b1
#10 23.69   Could not connect to debian.map.fastlydns.net:80 (146.75.42.132). - connect (111: Connection refused) Unable to connect to deb.debian.org:http:

Running Locally with Docker

Build the container

docker build . -t aind-metadata-service-local:latest

Option 1: Using AWS Credentials from Local Machine

If your AWS credentials are already configured on your machine (~/.aws/credentials on Linux/macOS or %USERPROFILE%\.aws\credentials on Windows), you can mount your credentials directly into the container:

1. Run the container with AWS credentials mounted:

docker run -v ~/.aws:/root/.aws -e AWS_PROFILE={profile} -e AWS_PARAM_STORE_NAME={param name} -p 58350:58350 -p 5000:5000 aind-metadata-service-local:latest

This allows the container to use your locally configured AWS credentials without needing to pass them explicitly.

This will start the service on port 5000. You can access it at:

http://localhost:5000

Client Installation

Installing the client allows you to interact with the metadata service programmatically.

The client can be installed with pip:

pip install "aind-metadata-service[client]"

Using the client

The client provides a simple interface to the API:

from aind_metadata_service.client import AindMetadataServiceClient

# Initialize client with the server domain
# If you're at the Allen Institute, use one of these domains:
client = AindMetadataServiceClient(domain="http://aind-metadata-service")  # production
# client = AindMetadataServiceClient(domain="http://aind-metadata-service-dev")  # development

# Subject and procedures
subject_data = client.get_subject("775745").json()
procedures_data = client.get_procedures("775745").json()

# Intended measurements and other data
measurements = client.get_intended_measurements("775745").json()
injection_materials = client.get_injection_materials("VT3214G").json()
ecephys_sessions = client.get_ecephys_sessions("775745").json()
perfusions = client.get_perfusions("775745").json()

# Protocol and funding information 
protocol_info = client.get_protocols("Protocol-123").json()
funding_info = client.get_funding("Project-ABC").json()
project_names = client.get_project_names().json()

# SLIMS data
imaging_data = client.get_smartspim_imaging(
    subject_id="775745",
    start_date_gte="2023-01-01",
    end_date_lte="2023-12-31"
).json()

histology_data = client.get_histology(subject_id="775745").json()

For Development

In the root directory, run

pip install -e ".[dev]"

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

Documentation

To generate the rst files source files for documentation, run

sphinx-apidoc -o doc_template/source/ src 

Then to create the documentation html files, run

sphinx-build -b html doc_template/source/ doc_template/build/html

More info on sphinx installation can be found here: https://www.sphinx-doc.org/en/master/usage/installation.html

Responses

There are 6 possible status code responses for aind-metadata-service:

• 200: successfully retrieved valid data without any problems.
• 406: successfully retrieved some data, but failed to validate against pydantic models.
• 404: found no data that matches query.
• 300: queried the server, but more items were returned than expected.
• 503: failed to connect to labtracks/sharepoint servers.
• 500: successfully connected to labtracks/sharepoint, but some other server error occurred. These status codes are defined in StatusCodes enum in response_handler.py