Dailygraphics-next

Tools for writing and deploying daily interactive news graphics. Based substantially on NPR's original daily graphics rig. Built on Express, LESS, Browserify and Google Sheets.

What does it do?

All the good stuff from the classic rig, plus:

Live reload of JS/CSS/HTML in the preview page
Build errors shown in the browser console, to minimize context switching
Create and deploy graphics directly from the web UI, not just the command line
Modern JS tooling, including Babel for new JS features and source maps for easier debugging
Improved Sheets integration, including typecasting for numerical/boolean values

Quickstart

To run this project, you'll need Node 10.0 or higher installed. On OS X and Linux, nvm is a good way to install and update Node.

Once you've done that:

Clone this repo, and run npm i to install its dependencies.
Clone the templates repo to install a selection of premade graphic types.
Clone or create a folder to contain your actual graphic files (by default this is graphics-js, in the same parent folder where you put the rig and template repos).
1. If you're at NPR, we have a private graphics-js repo already created--you should clone that repo and run npm install in that folder to get our current dependencies.
2. For non-NPR users, you should create a package.json in the graphics folder and install the common libraries there: npm init -y && npm install d3-array d3-axis d3-scale d3-selection d3-shape d3-svg.
You should now have three sibling folders: the rig, the templates and a graphics repo. Configure config.json in the rig folder so that the paths for the graphics and template folders match the folders from steps 2 and 3.
Run npm start to begin running the server, and open localhost:8000 in your browser to view the admin UI.

Getting started (in more detail)

Configuration for this project is split between config.json (an example of which is provided) for values that are organization-specific but not sensitive, and environment variables for values that should be confidential.

We recognize that environment variables are not perfectly secure (since installed packages have access to them from the process global), but they're also impossible to check into GitHub accidentally. You should have set:

GOOGLE_OAUTH_CLIENT_ID
GOOGLE_OAUTH_CONSUMER_SECRET

The Google OAuth variables should match the client ID and secret for an API app that can access your account. This post has details on setting that up.

Alternatively, service account authentication is also supported. To create a service account and JSON key file, visit your project's GCP web console to get started.

After creating the service account:

Grant write access on your Drive folder (driveFolder in config.json) to the service account email address.
Set GOOGLE_APPLICATION_CREDENTIALS to the file path of the JSON file containing your credentials.

If you're deploying to S3, which is the default for the rig, you'll also need to set:

AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
AWS_DEFAULT_REGION

In addition to the directory that contains this app, you'll also need two other directories. One is for the templates that are used to create each graphic (in the legacy rig, these were stored in the dailygraphics/graphic_templates folder). We provide a repo of templates used at NPR here, and you should feel free to clone it. In the config.json file, the "templateRoot" value should be the path to this folder.

The other directory is for your graphics themselves, and it should be referenced with the "graphicsPath" key of your config.json file. This folder is also where you should install any libraries used by your graphics via NPM. For example, if you're using our templates, you'll want to run npm install d3-array d3-axis d3-scale d3-selection to get the most common D3 packages.

The server supports a number of command-line arguments to customize its behavior:

--port XXXX - sets the port that the server will listen on to XXXX.
--live-reload XXXX - sets the port for the live reload server.
--force-sheet-cache - forces graphics preview pages to cache Google Sheets, so that you must press the "Refresh sheet" button when data is changed instead of simply reloading the page. Good for slow connections.
--no-live-reload - Turns off live reload when files are edited.
--no-websockets - Turns off the websocket debugging connection. Along with disabling live reload, this may be good in a hosted installation environment.
--disable-headless - Show the Chrome window when capturing fallback images, which can help on some computers
--target - Choose between "stage" and "live" (default of "live") for deployment to S3
--deployTo - Override the deployTo config.json option (see [Deployment](#deployment), below)

Due to the way NPM scripts work, flags must be passed after a -- separator. For example, running the rig on port 7777 would look like npm start -- --port 7777.

Terminal shortcut

Do you use iTerm2 as your terminal app? Here's a sample AppleScript to automatically launch a three-paned terminal window (one for the dailygraphics-next repo, one for the local webserver and another for the graphics repo) and pull the latest code from GitHub. You can save this locally, customize it to match your own configuration and add an alias for it to your .bash_profile.

alias dgnext="osascript ~/PATH-TO-FILE/iterm_dgnext.scpt"

Authorizing Google access

Similar to the original dailygraphics rig, you need to authorize this app's API access to access and create Drive files (for the spreadsheets that back each page). When the initial list page loads, it should redirect you to a Google log-in screen--just follow the instructions to complete the process. You'll need to create a Google API app, enable Drive access and store its authentication values in the GOOGLE_OAUTH_CLIENT_ID and GOOGLE_OAUTH_CONSUMER_SECRET environment variables. Your OAuth tokens are stored in your home directory as .google_oauth_tokens.

To do this step, you must run the rig on port 8000 (the default port). After you've done this step, you can run the rig on a different port.

Creating a graphic

The default view of the rig is a listing of all the graphics in your repository. However, if you're just starting out, there won't be anything in the list. Click the "new()" button in the toolbar, and select an item from the list of templates. You'll also need to provide a slug for the graphic--this will have the current date in YYYYMMDD format appended to it, to prevent collisions.

Once you click through, the rig will create a new folder and copy the template files into it. It will also make a duplicate of the template's assigned Google Sheet, for loading labels and data. Finally, it'll take you to the graphic preview page.

Preview graphic workspace

Each graphic is shown in a preview page, already embedded via Pym.js. The preview adds live reload support--after editing a source file, the embed will reload with your changes, so you don't need to return to the browser to refresh. The toolbar at the top provides access to simulated breakpoints, a link to the Google sheet backing the graphic and a button to refresh data from the source (because of live reload, we don't auto-refresh data). There's also a button to deploy to S3 (more on that later).

As resources are loaded, the server will process them according to their type:

HTML - processed using Lodash templating. Sheets data is available as COPY, just as in the classic rig, and filter functions are available on the t utility collection (e.g., t.classify(row.name) or t.comma(row.value)). You can import template partials using await t.include("filename.html"), where the filename is relative to the template doing the inclusion.
JS - transpiled with Babel to support newer JS features and bundled with Browserify. You can require() NPM modules into your scripts--they'll be loaded first from the graphic subfolder, if there's a node_modules there, and then from any modules installed in the graphics repo itself. Generally, you should use a local node_modules only in cases where your graphic requires a different library version from other graphics.
CSS - compiled from LESS files, based on filename (loading graphics.css will compile and load graphics.less from disk).

Errors detected during JS or LESS compilation will be routed to the dev tools console for easy debugging if your browser supports WebSockets.

Each graphic should also have a manifest.json file in its folder, which is used to store configuration data for Sheets and deployment. The "sheets" key in that file tells the server which Google Sheet to use for loading labels and data. It will also have a snapshot of the Node modules installed when it was created--this isn't used for anything, but is meant as a helpful record when recreating graphics later.

For most graphics, the Google Sheet workbook will contain a "labels" sheet (for headline and chatter text), a "metadata" sheet (which populates the copy edit e-mail on the preview page), and "data" (which actually generates the graphics). However, the rig will download any sheet it finds, unless the name starts with an underscore, like "_scratch". You can use this to hide large working sheets from the rig, preventing them from slowing down the initial preview page with data that's not directly relevant to the graphic itself.

Template creation

For the most part, templates are just folders containing files that should be copied into a graphics directory. So building a template is pretty much just building a graphic, then stripping out anything that isn't generic and copying it into your template directory. The process is recursive, and will copy subfolders as well as any filenames that don't start with a dot.

You will also need to add a "templateSheet" key to your manifest.json in the template folder (for existing graphics, you can often just rename the "sheet" key). When the template is instantiated, the server will duplicate that Sheet into a new copy and add the resulting ID to the manifest for the graphic. Graphics retain the original "templateSheet" key in their manifest when instantiated from a template.

For more details on templates, visit the templates repo.

Deployment

Deployment should be as simple as configuring the bucket and path prefix in your config.json file, and then clicking the "deploy" button when previewing a particular graphic. However, understanding the mechanics of a deployment will help you debug new templates and deployment issues.

When the server runs a deployemnt, it loads the manifest.json file from the graphic folder and uses the "files" array as a set of minimatch globbing patterns to figure out which source files should actually be published. Note that unlike in the browser translation layer, where requests for .css are turned into .less, the files array should actually specify .less filenames (they'll be translated back to CSS during the deploy). A typical deployment "files" array may look something like this, which grabs the main files for the graphic and any images or data that's located in the folder (not including the manifest itself):

"files": [
  "index.html",
  "graphic.less",
  "graphic.js",
  "*.json",
  "*.csv",
  "*.geojson",
  "*.jpg",
  "*.png",
  "!manifest.json"
]

These files are run through the same translation steps as when they're sent to the browser, then uploaded to S3. Your config.json should specify an "s3" object with a bucket, as well as a "prefix" that will be added at the front of the graphics slug. For example, if your bucket and prefix are set to "apps.npr.org" and "dailygraphics/graphics", respectively, a graphic with a slug of "bar-chart-20190101" would be uploaded to s3://apps.npr.org/dailygraphics/graphics/bar-chart-20190101.

In addition to publishing to S3, it's possible to simply deploy to a local folder instead. To do so, add the following items to your config.json:

"deployTo": "local",
"exportPath": "../exports"

With this configuration, when you press the deploy button, the rig will create a subfolder in ../exports for your graphic, and write all the files from the graphic into it, including the preview page. Graphics folders created this way can be distributed via FTP, packaged in a ZIP, or synced to network storage, since they're self-contained units.

As a final convenience feature, the rig will automatically spin up a headless browser and capture a "fallback.png" image for you prior to deployment. This happens automatically and can't be disabled at this time. If you prefer hand-crafted fallback images, you may want to save them as a different filename and update the templates to point there instead.

Using the CLI

It's possible to perform all necessary tasks from the web interface, but if you want to use the command line (say, for scripting multiple deployments), the CLI interface uses the same service code as the web does. From the project root, you can run node cli COMMAND to perform a given task.

For example, node cli create bar_chart testgraphic will create a graphic from the "bar_chart" template with the name "testgraphic". node cli or node cli help will list available commands and their arguments. Currently, commands exist for creating, copying and deploying graphics, but others will be added as the rig becomes more capable.

Migrating from the original dailygraphics rig

When moving graphics and templates over from the classic rig, there are three changes you'll need to make:

Add a manifest.json with the sheet/template sheet (formerly defined as COPY_GOOGLE_DOC_KEY in graphic_config.py)
Copy your child template into a _content.html file, which is (by default) loaded in the base template's index.html.
Convert the Jinja2 templating to EJS templates. This is usually pretty straightforward translation of tags:
- {{ key }} becomes <%= key %>
- {% if condition %} ... {% endif %} becomes <% if (condition) { %> ... <% } %>
- {% for item in list %} ... {% endfor %} becomes <% list.forEach(item => { %> ... <% }) %>
Load scripts using Browserify instead of the JS.include template helpers:
- Create a normal script tag that points toward the "base" script, which will load the others. This is usually graphic.js.
- For scripts that load onto the global object, you can just require their relative path, such as require("./lib/pym.js")
- Scripts that are module-aware can be imported to a variable, such as var d3 = require("./lib/d3.min")
- Scripts that relied on global scope, such as helpers.js, will need their functions assigned to the window object (e.g., var classify = window.classify = ...).

Since most classic dailygraphics already bundled their own JS libraries, you shouldn't need to worry about NPM for these.

Troubleshooting

My chart doesn't appear, and I see an error like "ERROR: Cannot find module 'd3-axis' from 'graphics-js/lots-of-dots-20181130'"

This usually means your graphic requires a library that you don't have installed. In the case above, we're missing d3-axis. To fix it, open a terminal in the graphics folder and install the module from NPM (e.g., npm install d3-axis).

I updated the rig, and now it's complaining that it can't find a module when it starts up

Oops! Looks like we added a dependency, and didn't let you know about it. Run npm i in the dailygraphics-next directory to install whatever was missing.

When I try to start the rig, it complains about "EMFILE: too many open files"

This is a problem that can occur on OS X due to the way it handles watching files. Update to the latest version of the rig and run an npm install, or npm i fsevents to install a helper module if you're unable to update.

Known issues

There's currently a fair amount of missing feedback when errors occur, such as if you don't have Google API access authorized yet. We're working on it.
There's no current support for falling back to the base template's "index.html" if one doesn't exist in the current graphic, which would be useful for implementing large-scale changes to graphics, but it does make individual graphics a bit more robust.

wbez/dailygraphics-next