Skip to content

Latest commit

 

History

History
136 lines (76 loc) · 7.38 KB

README.md

File metadata and controls

136 lines (76 loc) · 7.38 KB
Raw

Datagroom v0.5

Datagroom aims to provide tools to maintain and groom arbitrary datasets with a simple and intuitive user-experience. The data grooming can be done by multiple users simultaneously.

Features

  1. The data is stored in MongoDb at the backend.

  2. The front-end features the wonderful Tabulator (tabulator.info) component.

  3. Shared editing of data with similar user-experience like a Google sheet.

    • Per-cell locking.
    • Dynamic updates to edited cells.
    • Guaranteed to not overwrite a more recent edit by someone else.

  4. Supports markdown in cells. You edit markdown and the html is rendered in the table. Use of codemirror as an editor for markdown is enabled.

  5. Export of all data to xlsx file format.

  6. Paging, Filtering, Searching (regex), Sorting of data. All from the backend, enabling the tool to work with very large datasets.

  7. Import your data from xlsx and csv formats.

  8. Adjust and set views that is visible for everyone.

  9. Easy copy of rendered HTML to clipboard.

  10. Configurable single or multiple selection of preset items on a column.

  11. Configurable conditional values for a column based on other column values.

  12. Right-click menu for useful tools.

  13. Per-column editable controls. Also allows you to hide some columns. Set a few formatting attribute on a per column basis.

  14. Edit-log for every single edit by any user. No danger of losing data.

  15. Hook it up to your company's active-directory for user authentication. Or use a single guest user account to start.

Filters

  1. Click on Show filters checkbox to see additional controls for filtering. With these controls, you can save various column filters (with regex support), column visibility and column widths as well.

  2. Select from the stored filters to immediately reset the view to the stored value. The URL also changes and is directly routable.

Bulk editing

Bulk editing features are now available. Yet to be documented

Installation on VM/Machine

  1. Install MongoDb community edition, if you want local installation. In case of cloud MongoDb installation. Follow the following steps:-

    • Make a new project and a new empty cluster inside that project on mongodb atlas.
    • For the newly connected cluster. Click on connect -> connect your application and copy the url. Sample url:- mongodb+srv://:@.onvfm2f.mongodb.net/?retryWrites=true&w=majority
    • Now go to database access option and add new user with the same username which will be used for login to datagroom. (In case of ldap server, it will be org username. For others, create a guest user.). Give the user readWriteAnyDatabase permission.
    • Now go to network access option and add the ip address of the server where datagroom-gateway will run. Or, otherwise allow access from anywhere.

  2. git clone the datagroom-gateway and datagroom-ui repos. If all of the repos and the mongodb installation is on the same machine, go to next step. Otherwise, in datagroom-gateway, add one .env file and update it with key DATABASE and value as the the mongodb server url. Alternatively, you can tweak this.url in dbAbstraction.js directly if url doesn't consist any sensitive information.

  3. Build react-ui by doing cd datagroom-ui; npm run build. Note that datagroom-gateway and datagroom-ui should be at the same level because datagroom-gateway serves the files built in datagroom-ui.

  4. Start server: cd datagroom-gateway; node ./server.js disableAD=true. Login as guest with guest as password. If you want active-directory integration, update the configuration in ldapSettings.js. (node ./server.js if you have updated ldapSettings.js) If you want to use the JIRA plug-in, update the configuration in jiraSettings.js.

  5. Open a browser and navigate to localhost:8887

Docker installation

Pre-requisites -

  • Make sure that the Docker is installed on your machine.
  • Make sure that both the gateway and UI code is cloned on the same directory level.

Docker installation for deployment

Steps to follow :-

  1. For persistence of mongodb data onto the host - Run docker volume create dg-data. Note- You can skip this step if you want full cleanup of the data if the docker container stops

  2. Run the command docker build -t dg-image -f datagroom-gateway/Dockerfile . from the parent directory of datagroom-gateway.

  3. After the image is created. Just run the command docker run -dit -p 8887:8887/tcp -p 8887:8887/udp -p 443:443/tcp -p 443:443/udp -v dg-data:/var/lib/mongodb --name dg-container dg-image. Note - If you have skipped the first step of docker volume creation, you can omit the -v dg-data:/var/lib/mongodb in the above command.

  4. You can now go to the browser on the link http://<host-ip>:8887 and see the webapp running.

  5. To see the processes running - you can attach to the dg-container image.

Docker installation for development

Steps to follow :-

  1. For persistence of mongodb data onto the host - Run docker volume create dg-data.

  2. Run the command docker build -t dg-image -f datagroom-gateway/Dockerfile . from the parent directory of datagroom-gateway.

  3. After the image is created. Just run the command docker run -dit -p 8887:8887/tcp -p 8887:8887/udp -p 443:443/tcp -p 443:447/udp -v /home/${USER}:/home/${USER} -v dg-data:/var/lib/mongodb --name dg-container dg-image devMode=ON absolutePathToServerFile=<absolute path to the /datagroom-gateway/server.js file>.
    Example command: - docker run -dit -p 8887:8887/tcp -p 8887:8887/udp -p 443:443/tcp -p 443:447/udp -v /home/${USER}:/home/${USER} -v dg-data:/var/lib/mongodb --name dg-container dg-image devMode=ON absolutePathToServerFile=/home/abc_user/DG-development/datagroom-gateway/server.js.
    Note - Here, you can mount any source and target directory while development. By default it is mounting the /home/$USER. You can change this behaviour as you prefer by altering the argument to -v. Make sure that the absolute path to the server file is mounted correctly. If the path is invalid or not mounted correctly, it can lead to unexpected behaviour. (absolutePathToServerFile is necessary to indicate that out of the mounted directory, in which path you are going to develop so that the docker container picks the correct path and run the intended server.js file)

  4. You can now go to the browser on the link http://<host-ip>:8887 and see the webapp running.

  5. You can attach to the container and make the changes in backend code on the host.

Uses

  1. For quick bug lists, scrum todo lists, personal lists, code notes etc.

  2. Light enough for personal use on a single computer.

  3. Any table-like data that can be shared/edited.

Screenshots

  1. A sample table once populated:

  2. Markdown editing in progress

  3. Markdown rendered once editing is done

  4. Right-click menu

  5. Filters in action

  6. Edit-log