ATA Datasets — Product Documentation

1) What Datasets Are

Datasets let you create a named bundle of environment variables (a finite selection you choose) and reuse that bundle across API requests and test runs. Datasets are based on your existing API environment variables and provide a clean way to run the same requests with consistent, scoped configuration.

Key property: After you create a dataset from selected variables (say, 5 vars), the dataset’s membership stays fixed. Adding new environment variables later does not automatically add them to existing datasets. If you want newer variables in a dataset, you explicitly update that dataset.

2) How Datasets Relate to Environment Variables

• Source of truth: Environment variables remain the canonical store of keys and values per environment (Development, Staging, Production, etc.).
• Dataset = selection: A dataset is a curated subset of those variables (e.g., exactly 5 variables needed for a scenario).
• No surprise growth: When new environment variables are added later, existing datasets are not affected. You decide when to revise a dataset.
• Resolution: Requests keep using {\{variableName\}} placeholders; when a dataset is attached, variables referenced in the request resolve from the dataset’s selected keys.

3) Quick Start (TL;DR)

1. Go to API Env Variables → Datasets → New Dataset.
2. Give it a name and optional description.
3. Select variables from your existing environment variables (check 5 keys, for example).
4. Save — the dataset now contains exactly those keys.
5. In your request runner or collection, choose the dataset before sending requests.
6. Use variables as usual in requests ({\{base_url\}}, {\{access_token\}}, etc.).

4) Creating a Dataset

1. Navigate: API Env Variables → Datasets → New Dataset.

2. Name & Describe: Choose a clear, scenario‑oriented name (e.g., Checkout-Smoke, PartnerA-SIT).

3. Pick Variables: Select the exact environment variable keys to include. Examples:

   • base_url
   • access_token
   • tenant_id
   • session_cookie
   • feature_flag_checkout_new

4. Save: The dataset now holds only these keys. Later additions to environment variables won’t appear here unless you edit the dataset.

Tip: Keep datasets minimal—only include keys used by the requests in that flow.

5) Using a Dataset in API Requests

1. In the API request runner (or collection run), select your dataset from the dataset picker.

2. Author requests exactly the same way you do with environment variables:

   • URL: {\{base_url\}}/orders?tenant={\{tenant_id\}}

   • Header: Authorization: {\{access_token\}}

   • Body (JSON):

     {
       "session_id": "{\{session_cookie\}}",
       "flags": { "checkout_new": "{\{feature_flag_checkout_new\}}" }
     }

3. Send the request—placeholders resolve using the selected dataset’s keys.

6) Behavior & Scope

• Membership‑locked: The set of keys in a dataset is fixed at creation (editable only by you later). New environment variables do not appear automatically.
• Environment aware: Values still come from your active environment’s variable store; the dataset defines which keys are in play for a run.
• Collections: Attach datasets to collection or folder runs to keep configuration consistent across a suite of requests.
• Cloning: Duplicate a dataset to quickly create a variant (e.g., Checkout-Smoke → Checkout-ErrorPaths) and tweak just one or two keys.

7) Examples

7.1 Minimal Dataset (5 Vars)

Dataset: Checkout-Smoke
Keys: base_url, access_token, tenant_id, session_cookie, feature_flag_checkout_new

Request

GET {\{base_url\}}/health?tenant={\{tenant_id\}}
Authorization: {\{access_token\}}

Request

POST {\{base_url\}}/checkout
Authorization: {\{access_token\}}
Content-Type: application/json

{
  "session": "{\{session_cookie\}}",
  "features": ["{\{feature_flag_checkout_new\}}"]
}

7.2 Add New Env Variable Later (Unaffected Dataset)

• You later create a new env var inventory_base_url for