List Datapoints

beeminder.list_datapoints
ActionBusiness appsconnection required

Calls the Beeminder API with the connection's credentials.

Read a goal's datapoints, newest first, optionally one page at a time.

Connection

Required
Yes — the node will not save without one
Auth type
API key
Providers
Beeminder
Secret shape
the personal auth token, or {"auth_token": "…"} / {"access_token": "…"}
Config it needs
username
Resolved by
config.connection_id, else node.connection_id

Configuration

5 fields, 1 required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.

FieldTypeRequiredDefaultConstraintsExample
goal
The goal's slug — the last segment of its Beeminder URL, e.g. 'weight'.
stringYes——weight
sort
Which datapoint attribute to sort on, descending.
stringNoidone of "id", "timestamp", "daystamp", "value", "updated_at", "created_at"—
count
Return at most this many datapoints. Ignored when a page is given; leave empty for every datapoint on the goal.
numberNo—≥ 0—
page
Which page of results to return, counting from 1.
numberNo—≥ 1—
per
How many datapoints one page holds. Ignored unless a page is given.
numberNo25≥ 0—

Example configuration

Every value below is the contract’s own example or default — nothing invented.

{
  "goal": "weight",
  "per": 25,
  "sort": "id"
}

Output

One shape.

result

FieldTypeExample
datapoints[].id
Unique id of the datapoint.
string—
datapoints[].timestamp
Unix time the datapoint belongs to.
number—
datapoints[].daystamp
The datapoint's date as YYYYMMDD.
string—
datapoints[].value
The value recorded for that day.
number—
datapoints[].comment
The note stored with the datapoint.
string—
count
How many datapoints the response carried.
number—
goal
The goal slug the datapoints belong to.
string—
{
  "count": 0,
  "datapoints": [
    {
      "comment": "",
      "daystamp": "",
      "id": "",
      "timestamp": 0,
      "value": 0
    }
  ],
  "goal": ""
}

See List Datapoints run in a workflow.

In a technical demo we add the Beeminder connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.