This graphic was created using data-visuals-create 7.3.0 on 2022-08-18.
-Link to your project
-Link to your doc
Before your embedded graphic or feature goes live, here's the editing steps you need to take:
- Spell check and self-edit — does everything make sense?
- Data visuals editor for a visual edit
- Design feedback channel (optional for more complex graphics or apps)
- Story reporter, if a collaboration
- Story or beat editor for a line edit to check facts
- DV team in the secret channel (for a final gut check)
- Copy editor
- Be available the night before publication for any last-minute changes, or let other DV teammates know how to make edits
All project templates share the same build commands.
The main command for development. This will build your HTML pages, prepare your SCSS files and compile your JavaScript. A local server is set up so you can view the project in your browser.
The main command for deployment. It will always run npm run build first to ensure the compiled version is up-to-date. Use this when you want to put your project online. This will use the bucket and folder values in the project.config.js file to determine where it should be deployed on S3. Make sure those are set the appropriate values!
This command uses the array of files listed under the files key in project.config.js to download data to the project. This data will be processed and made available in the data folder in the root of the project.
You can also set dataDir in project.config.js to change the location of that directory if necessary.
This pushes all the raw files found in the app/assets directory to S3 to a raw_assets directory. This makes it possible for collaborators on the project to sync up with your assets when they run npm run assets:pull. This prevents potentially large assets like photos and audio clips from ending up in GitHub. This also runs automatically when npm run deploy is used.
Pulls any raw assets that have been pushed to S3 back down to the project's app/assets directory. Good for ensuring you have the same files as anyone else who is working on the project.
The workspace directory is for storing all of your analysis, production and raw data files. It's important to use this directory for these files (instead of assets or data) so we can keep them out of GitHub. This command will push the contents of the workspace directory to S3.
Pulls any workspace files that have been pushed to S3 back down to the project's local workspace directory. This is helpful for ensuring you're in sync with another developer.
Any projects created with data-visuals-create assume you're working within a Texas Tribune environment, but it is possible to point AWS (used for deploying the project and assets to S3) and Google's API (used for interfacing with Google Drive) at your own credentials.
Projects created with data-visuals-create support two of the built-in ways that aws-sdk can authenticate. If you are already set up with the AWS shared credentials file (and those credentials are allowed to interact with your S3 buckets), you're good to go. aws-sdk will also recognize the AWS credential environmental variables.
The interface with Google Drive within data-visuals-create projects currently only supports using Oauth2 credentials to speak to the Google APIs. This requires a set of OAuth2 credentials that will be used to generate and save an access token to your computer. data-visuals-create projects have hardcoded locations for the credential file and token file, but you may override those with environmental variables.
default: ~/.tt_kit_google_client_secrets.json
default: ~/.google_drive_fetch_token
default: /Applications/Google Chrome.app/Contents/MacOS/Google Chrome
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