This service utilizes separate containers for REST API management, job processing, and datastorage with MongoDB, ensuring scalable and robust performance.
**The REST API can be accessed via Swagger UI here: https://biochecknet.biosimulations.org/docs
This application ("BioCompose") uses a microservices architecture which presents the following libraries:
api
: This library handles all requests including saving uploaded files, pending job creation, fetching results, and contains the user-facing endpoints.worker
: This library handles all job processing tasks for verification services such as job status adjustment, job retrieval, and comparison execution.
The simulators used by this application consist of multiple python language bindings of C/C++ libraries. Given this fact, is it helpful to be aware of the dependency network required by each simulator. See the following documentation for simulators used in this application:
- AMICI
- COPASI(basico)
- PySCes
- Tellurium
- Simulator-specific implementations of the Biosimulators-Utils interface
- Smoldyn
- (Coming soon:) ReaDDy
- Anaconda via
environment.yml
- the closest to local development at root level which mimics what actually happens in the containers (conda deps tend to break more frequently than poetry.)
Remotely in microservice containers:
- Remote microservice container management is handled by
conda
viaenvironment.yml
files for the respective containers.
-
git clone https://github.com/biosimulators/bio-check.git
-
cd assets
-
touch .env_dev
-
Enter the following fields into the
.env_dev
file:MONGO_URI=<uri of your mongo instance. In this case we use the standard mongodb image with the app name bio-check> GOOGLE_APPLICATION_CREDENTIALS=<path to your gcloud credentials .json file. Contact us for access> BUCKET_NAME=bio-check-requests-1 # name of the bucket used in this app
-
cd ..
-
Pull and run the latest version of Mongo from the Docker Hub. (
docker run -d -it mongo:latest
or similar.) -
Create a conda env from the environment file at the root of this repo:
conda env create -f environment.yml -y && conda activate bio-composer-server-dev
-
Install pysces with conda and amici with pip:
conda install -c conda-forge -c pysces pysces conda run pip3 install biosimulators-amici # installs both biosimulators and amici
-
If using Smoldyn, there is a arm-based mac installation script in
assets/dev/
calledinstall-smoldyn-mac-silicon.sh
. So run the following:sudo chmod +x ./assets/dev/scripts/install-smoldyn-mac-silicon.sh # or whichever method you are using to install ./assets/dev/scripts/install-smoldyn-mac-silicon.sh # conda is configured to install Smoldyn into its environment
- This application currently uses MongoDB as the database store in which jobs are read/written. Database access is given to both the
api
andworker
libraries. Such database access is executed/implemented with the use of aSupervisor
singleton.