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Merge pull request #18 from stanfordnmbl/treadmill_gait_analysis
Add treadmill gait analysis
2 parents 9a5a424 + 1e821e9 commit f1c9f7e

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‎.github/workflows/treadmill_gait_analysis-dev.yml

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# This workflow will build and push a new container image to Amazon ECR,
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# and then will deploy a new task definition to Amazon ECS, on every push
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# to the master branch.
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#
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# To use this workflow, you will need to complete the following set-up steps:
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#
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# 1. Create an ECR repository to store your images.
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# For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-2`.
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# Replace the value of `ECR_REPOSITORY` in the workflow below with your repository's name.
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# Replace the value of `aws-region` in the workflow below with your repository's region.
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#
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# 2. Create an ECS task definition, an ECS cluster, and an ECS service.
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# For example, follow the Getting Started guide on the ECS console:
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# https://us-east-2.console.aws.amazon.com/ecs/home?region=us-east-2#/firstRun
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# Replace the values for `service` and `cluster` in the workflow below with your service and cluster names.
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#
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# 3. Store your ECS task definition as a JSON file in your repository.
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# The format should follow the output of `aws ecs register-task-definition --generate-cli-skeleton`.
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# Replace the value of `task-definition` in the workflow below with your JSON file's name.
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# Replace the value of `container-name` in the workflow below with the name of the container
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# in the `containerDefinitions` section of the task definition.
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#
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# 4. Store an IAM user access key in GitHub Actions secrets named `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
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# See the documentation for each action used below for the recommended IAM policies for this IAM user,
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# and best practices on handling the access key credentials.
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on:
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push:
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branches:
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- dev
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paths:
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- 'treadmill_gait_analysis/**'
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workflow_dispatch:
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name: DEV Analysis "treadmill gait analysis" build & deployment
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jobs:
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deploy:
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name: Deploy
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v1
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: us-west-2
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- name: Login to Amazon ECR
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id: login-ecr
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uses: aws-actions/amazon-ecr-login@v1
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- name: Build, tag, and push image to Amazon ECR
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id: build-image
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env:
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IMAGE_TAG: latest # ${{ github.sha }}
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run: |
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# Build a docker container and
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# push it to ECR so that it can
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# be deployed to ECS.
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cd treadmill_gait_analysis
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docker build -f Dockerfile -t 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis-dev:$IMAGE_TAG .
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docker push 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis-dev:$IMAGE_TAG
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echo "::set-output name=image::660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis-dev:$IMAGE_TAG"
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- name: Force deployment
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env:
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IMAGE_TAG: latest # ${{ github.sha }}
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run: |
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aws lambda update-function-code --function-name treadmill-gait-analysis-dev --image-uri 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis-dev:$IMAGE_TAG | jq 'if .Environment.Variables.API_TOKEN? then .Environment.Variables.API_TOKEN = "REDACTED" else . end'

‎.github/workflows/treadmill_gait_analysis.yml

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# This workflow will build and push a new container image to Amazon ECR,
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# and then will deploy a new task definition to Amazon ECS, on every push
3+
# to the master branch.
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#
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# To use this workflow, you will need to complete the following set-up steps:
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#
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# 1. Create an ECR repository to store your images.
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# For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-2`.
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# Replace the value of `ECR_REPOSITORY` in the workflow below with your repository's name.
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# Replace the value of `aws-region` in the workflow below with your repository's region.
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#
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# 2. Create an ECS task definition, an ECS cluster, and an ECS service.
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# For example, follow the Getting Started guide on the ECS console:
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# https://us-east-2.console.aws.amazon.com/ecs/home?region=us-east-2#/firstRun
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# Replace the values for `service` and `cluster` in the workflow below with your service and cluster names.
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#
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# 3. Store your ECS task definition as a JSON file in your repository.
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# The format should follow the output of `aws ecs register-task-definition --generate-cli-skeleton`.
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# Replace the value of `task-definition` in the workflow below with your JSON file's name.
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# Replace the value of `container-name` in the workflow below with the name of the container
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# in the `containerDefinitions` section of the task definition.
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#
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# 4. Store an IAM user access key in GitHub Actions secrets named `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
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# See the documentation for each action used below for the recommended IAM policies for this IAM user,
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# and best practices on handling the access key credentials.
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on:
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push:
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branches:
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- main
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paths:
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- 'treadmill_gait_analysis/**'
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workflow_dispatch:
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name: PROD Analysis "treadmill gait analysis" build & deployment
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jobs:
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deploy:
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name: Deploy
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v1
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: us-west-2
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- name: Login to Amazon ECR
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id: login-ecr
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uses: aws-actions/amazon-ecr-login@v1
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- name: Build, tag, and push image to Amazon ECR
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id: build-image
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env:
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IMAGE_TAG: latest # ${{ github.sha }}
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run: |
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# Build a docker container and
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# push it to ECR so that it can
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# be deployed to ECS.
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cd treadmill_gait_analysis
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docker build -f Dockerfile -t 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis:$IMAGE_TAG .
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docker push 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis:$IMAGE_TAG
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echo "::set-output name=image::660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis:$IMAGE_TAG"
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- name: Force deployment
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env:
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IMAGE_TAG: latest # ${{ github.sha }}
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run: |
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aws lambda update-function-code --function-name treadmill-gait-analysis --image-uri 660440363484.dkr.ecr.us-west-2.amazonaws.com/opencap-analysis/treadmill_gait_analysis:$IMAGE_TAG | jq 'if .Environment.Variables.API_TOKEN? then .Environment.Variables.API_TOKEN = "REDACTED" else . end'

‎treadmill_gait_analysis/.dockerignore

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.git
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Data/
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.env
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docker

‎treadmill_gait_analysis/.gitignore

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__pycache__
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.env
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*.log
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*.ipynb_checkpoints
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Data/*
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*DS_Store

‎treadmill_gait_analysis/Dockerfile

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FROM stanfordnmbl/opensim-python:4.3
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ARG FUNCTION_DIR="/function"
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RUN apt-get update && \
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apt-get install -y \
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build-essential \
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python3-dev \
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g++ \
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make \
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cmake \
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unzip \
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libcurl4-openssl-dev
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# Copy function code
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RUN mkdir -p ${FUNCTION_DIR}
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COPY ./requirements.txt /requirements.txt
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# Install the requirements.txt
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RUN python3.8 -m pip install --no-cache-dir -r /requirements.txt
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RUN python3.8 -m pip install --target ${FUNCTION_DIR} awslambdaric
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ADD https://github.com/aws/aws-lambda-runtime-interface-emulator/releases/latest/download/aws-lambda-rie /usr/bin/aws-lambda-rie
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RUN chmod +x /usr/bin/aws-lambda-rie
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COPY ./function ${FUNCTION_DIR}
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RUN chmod +x ${FUNCTION_DIR}/entrypoint
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WORKDIR ${FUNCTION_DIR}
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ENTRYPOINT ["./entrypoint"]
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CMD ["handler.handler"]

‎treadmill_gait_analysis/docker-compose.yml

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version: '3.8'
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services:
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gait_analysis:
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# platform: linux/amd64
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build:
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context: .
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dockerfile: ./Dockerfile
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ports:
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- 9005:8080
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env_file:
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- ./.env

‎treadmill_gait_analysis/function/entrypoint

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#!/bin/bash
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if [ -z "${AWS_LAMBDA_RUNTIME_API}" ]; then
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exec /usr/bin/aws-lambda-rie /usr/bin/python3.8 -m awslambdaric $@
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else
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exec /usr/bin/python3.8 -m awslambdaric $@
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fi

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