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This repository was archived by the owner on Jun 7, 2023. It is now read-only.

Commit 6411aac

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kushalbakshikushalbakshi
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Merge pull request #104 from kabilar/main
Add GitHub Codespace environment
2 parents 4904022 + 887b53c commit 6411aac

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‎.devcontainer/Dockerfile‎

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# Note: You can use any Debian/Ubuntu based image you want.
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FROM mcr.microsoft.com/devcontainers/python:3.7-bullseye
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FROM mcr.microsoft.com/devcontainers/python:3.9-bullseye
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COPY ./requirements.txt /tmp/
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RUN \
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# dev setup
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apt update && \
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apt-get install bash-completion graphviz default-mysql-client s3fs procps -y && \
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pip install flake8 black faker ipykernel pytest pytest-cov datajoint
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pip install --no-cache-dir --upgrade pip && \
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pip install --no-cache-dir flake8 black pre-commit && \
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# workflow dependencies
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apt-get install gcc ffmpeg libsm6 libxext6 -y && \
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# Commented out CaImAn installation due to Docker image size limits on Codespace
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# pip install --no-cache-dir Pygments==2.14.0 && \
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# git clone https://github.com/datajoint/CaImAn.git && \
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# pip install --no-cache-dir -r ./CaImAn/requirements.txt && \
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# pip install --no-cache-dir ./CaImAn && \
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pip install --no-cache-dir -r /tmp/requirements.txt && \
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# clean up
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# rm -rf /tmp/CaImAn && \
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rm /tmp/requirements.txt && \
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apt-get clean
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ENV DJ_HOST fakeservices.datajoint.io
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ENV DJ_USER root
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ENV DJ_PASS simple
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ENV DJ_PASS simple
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ENV DJ_PUBLIC_S3_MOUNT_PATH /workspaces/workflow-calcium-imaging/example_data

‎.devcontainer/devcontainer.json‎

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// For format details, see https://aka.ms/devcontainer.json. For config options, see the
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// For format details, see https://aka.ms/devcontainer.json.
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{
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"name": "Development",
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"name": "Remote Demo",
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"dockerComposeFile": "docker-compose.yaml",
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"service": "app",
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"workspaceFolder": "/workspaces/${localWorkspaceFolderBasename}",
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"ghcr.io/eitsupi/devcontainer-features/jq-likes:1": {},
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"ghcr.io/guiyomh/features/vim:0": {}
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},
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// "onCreateCommand": "pip install -e .",
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"postStartCommand": "mkdir -p example_data && s3fs djhub.vathes.datapub.elements:/workflow-calcium-imaging-data-v2 example_data -o multipart_size=530,endpoint=us-east-1,url=http://s3.amazonaws.com,public_bucket=1 && MYSQL_VER=8.0 docker compose down && MYSQL_VER=8.0 docker compose up --build --wait",
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"onCreateCommand": "mkdir -p ${DJ_PUBLIC_S3_MOUNT_PATH} && pip install -e .",
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"postStartCommand": "docker volume prune -f && s3fs ${DJ_PUBLIC_S3_LOCATION} ${DJ_PUBLIC_S3_MOUNT_PATH} -o nonempty,multipart_size=530,endpoint=us-east-1,url=http://s3.amazonaws.com,public_bucket=1 && MYSQL_VER=8.0 docker compose down && MYSQL_VER=8.0 docker compose up --build --wait",
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"hostRequirements": {
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"cpus": 2,
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"memory": "4gb"
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"cpus": 4,
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"memory": "8gb"
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},
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"forwardPorts": [
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3306,
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8080
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3306
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],
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"customizations": {
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"vscode": {

‎.devcontainer/docker-compose.yaml‎

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version: "3"
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services:
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app:
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build: .
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extra_hosts:
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- fakeservices.datajoint.io:127.0.0.1
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volumes:
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- ../..:/workspaces:cached
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entrypoint: /usr/local/share/docker-init.sh
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command: tail -f /dev/null
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extends:
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file: ./local/docker-compose.yaml
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service: app
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environment:
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- DJ_PUBLIC_S3_LOCATION=djhub.vathes.datapub.elements:/workflow-calcium-imaging-data-v2
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devices:
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- /dev/fuse
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cap_add:
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- SYS_ADMIN
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security_opt:
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- apparmor:unconfined
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- apparmor:unconfined

‎.devcontainer/local/devcontainer.json‎

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// For format details, see https://aka.ms/devcontainer.json.
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{
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"name": "Local Demo",
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"dockerComposeFile": "docker-compose.yaml",
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"service": "app",
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"workspaceFolder": "/workspaces/${localWorkspaceFolderBasename}",
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// Use this environment variable if you need to bind mount your local source code into a new container.
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"remoteEnv": {
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"LOCAL_WORKSPACE_FOLDER": "${localWorkspaceFolder}"
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},
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// https://containers.dev/features
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"features": {
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"ghcr.io/devcontainers/features/docker-in-docker:2": {},
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"ghcr.io/devcontainers/features/git:1": {},
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"ghcr.io/eitsupi/devcontainer-features/jq-likes:1": {},
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"ghcr.io/guiyomh/features/vim:0": {}
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},
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"onCreateCommand": "pip install -e .",
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"postStartCommand": "docker volume prune -f && MYSQL_VER=8.0 docker compose down && MYSQL_VER=8.0 docker compose up --build --wait",
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"hostRequirements": {
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"cpus": 4,
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"memory": "8gb"
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},
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"forwardPorts": [
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3306
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],
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"customizations": {
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"vscode": {
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"extensions": [
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"ms-python.python"
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]
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}
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}
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}

‎.devcontainer/local/docker-compose.yaml‎

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version: "3"
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services:
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app:
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cpus: 4
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mem_limit: 8g
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build:
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context: ../..
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dockerfile: ./.devcontainer/Dockerfile
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extra_hosts:
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- fakeservices.datajoint.io:127.0.0.1
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volumes:
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- ../../..:/workspaces:cached
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entrypoint: /usr/local/share/docker-init.sh
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command: tail -f /dev/null

‎.vscode/settings.json‎

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"editor.formatOnPaste": false,
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"editor.formatOnSave": true,
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"editor.rulers": [
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],
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"python.formatting.provider": "black",
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"[python]": {

‎README.md‎

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DataJoint Workflow for functional calcium imaging combines multiple DataJoint Elements to process data acquired with [ScanImage](http://scanimage.vidriotechnologies.com), [Scanbox](https://scanbox.org), `Nikon
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NIS`, or `PrairieView` acquisition software, using [Suite2p](https://github.com/MouseLand/suite2p) or [CaImAn](https://github.com/flatironinstitute/CaImAn) analysis software. DataJoint Elements collectively standardize and automate data collection and analysis for neuroscience experiments. Each Element is a modular pipeline for data storage and processing with corresponding database tables that can be combined with other Elements to assemble a fully functional pipeline.
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Installation and usage instructions can be found at the
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[Element documentation](https://datajoint.com/docs/elements/element-calcium-imaging).
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To get started, see below for an [interactive tutorial](#interactive-tutorial) on GitHub Codespaces. More information can be found at the
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[Element documentation page](https://datajoint.com/docs/elements/element-calcium-imaging).
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![diagram](https://raw.githubusercontent.com/datajoint/element-calcium-imaging/main/images/diagram_flowchart.svg)
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## Interactive tutorial
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The easiest way to learn about DataJoint Elements is to use the tutorial notebook within a [GitHub Codespace](https://docs.github.com/en/codespaces/overview). Please follow the steps below for the best experience:
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1. Fork this repository to your GitHub account.
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2. Select the green `Code` button.
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3. Within the dropdown menu, select the `Codespaces` tab.
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4. Select the green `Create codespace on main` button.
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5. The environment is ready when a Visual Studio Code window is rendered within your browser. This takes ~5 minutes the first time being launched, and ~1 minute if you revisit this Codespace.
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6. Navigate to the `notebooks` directory on the left panel and open the `tutorial.ipynb` Jupyter notebook. Execute the cells in this notebook to begin your walk through the tutorial.
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7. Once you are done, GitHub will automatically terminate the Codespace after 30 minutes of inactivity or you can manually terminate the Codespace.
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+ If you are new to GitHub and run into any errors, please contact us via email at [email protected]. If you are experienced with GitHub, please create an issue on the upstream repository or issue a pull request with a thorough explanantion of the error and proposed solution.
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**Please Note:**
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+ GitHub Codespaces are limited to 120 core-hours per month for free users. Once you exceed this limit, you will have to wait for the hours to reset or pay to use Codespaces.

‎docker-compose.yaml‎

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version: "2.4"
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services:
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db:
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restart: always
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image: datajoint/mysql:${MYSQL_VER}
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environment:
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- MYSQL_ROOT_PASSWORD=${DJ_PASS}
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ports:
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- "3306:3306"
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# To persist MySQL data
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# volumes:
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# - ./mysql/data:/var/lib/mysql
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healthcheck:
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test: [ "CMD", "mysqladmin", "ping", "-h", "localhost" ]
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timeout: 15s
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retries: 5
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interval: 15s
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retries: 10
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interval: 15s

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