Import rows and run searches

Rows arrive in a sheet two ways. Import a CSV when you already have the list. Run a search when you don't. Both fill input columns that pipe columns can read.

Import a CSV

Upload a CSV and map its columns to canonical field names like name, company_domain, or linkedin_url. Canonical names matter because pipes find their inputs by field name. A pipe that needs company_domain will not read a column called website, so map at import time rather than renaming later.

Imported rows land as input columns. If the sheet already has pipe columns, the new rows show pending cells, and the next run fills them.

Run a search

A search creates rows from filters. Describe who you want ("Heads of Marketing at robotics companies in Europe"), pick a source, set a limit, and run. One row per result, with the source's fields as input columns.

Sources fall into two groups:

Prospecting datasets for people and companies you don't know yet: Amplemarket, Crustdata, and Parallel, which accepts a natural-language description.
Systems you already run: HubSpot, Salesforce, and Attio objects, Postgres and Databricks queries, Luma event guests, and Google Calendar events.

Browse the full list in the search catalog.

Searches into your own systems make a sheet a working surface for CRM data. Pull contacts from HubSpot, enrich them, and write the results back. The write-back is a pipe, covered in Export and CRM sync.

Add rows over the API

Sheets accept rows from outside pipe0 too. The row:append:sheet@1 pipe appends its input record to a sheet, so anything that can make an HTTP request can feed a sheet: a signup webhook, a backend job, a script.

import { Pipe0 } from "@pipe0/client";

const pipe0 = new Pipe0({ apiKey: process.env.PIPE0_API_KEY });

const result = await pipe0.pipes.pipe({
  pipes: [
    {
      pipe_id: "row:append:sheet@1",
      connector: {
        strategy: "first",
        connections: [
          {
            type: "vault",
            connection: "pipe0_123",
          },
        ],
      },
      config: {
        project: "gtm",
        sheet: "inbound-signups",
        write_fields: [
          {
            field_name: "name",
          },
          {
            field_name: "email",
          },
        ],
      },
    },
  ],
  input: [
    {
      id: "1",
      name: "Jane Doe",
      email: "jane@pipe0.com",
    },
  ],
});
console.log(result);

import requests

response = requests.post(
    "https://api.pipe0.com/v1/pipes/run/sync",
    headers={"Authorization": f"Bearer {API_KEY}"},
    json={
        "pipes": [
            {
                "pipe_id": "row:append:sheet@1",
                "connector": {
                    "strategy": "first",
                    "connections": [
                        {
                            "type": "vault",
                            "connection": "pipe0_123",
                        },
                    ],
                },
                "config": {
                    "project": "gtm",
                    "sheet": "inbound-signups",
                    "write_fields": [
                        {
                            "field_name": "name",
                        },
                        {
                            "field_name": "email",
                        },
                    ],
                },
            },
        ],
        "input": [
            {
                "id": "1",
                "name": "Jane Doe",
                "email": "jane@pipe0.com",
            },
        ],
    },
)
print(response.json())

curl -X POST "https://api.pipe0.com/v1/pipes/run/sync" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "pipes": [
    {
      "pipe_id": "row:append:sheet@1",
      "connector": {
        "strategy": "first",
        "connections": [
          {
            "type": "vault",
            "connection": "pipe0_123"
          }
        ]
      },
      "config": {
        "project": "gtm",
        "sheet": "inbound-signups",
        "write_fields": [
          {
            "field_name": "name"
          },
          {
            "field_name": "email"
          }
        ]
      }
    }
  ],
  "input": [
    {
      "id": "1",
      "name": "Jane Doe",
      "email": "jane@pipe0.com"
    }
  ]
}'

The destination is addressed by project and sheet slug, and write_fields lists exactly the columns the destination consumes. By default the destination sheet runs its own pipes over the new row on arrival, so appending a signup means the sheet enriches it without anyone opening the app. The pipe needs a pipe0 connection.

Appends are not idempotent. Sending the same request twice adds the row twice; deduplicate with an effect or gate the request upstream. If a workflow only sometimes needs a sheet, see When you don't need a sheet.

Search again without fear

Running the same search twice does not duplicate work you paid for. Deduplication runs as an effect, so repeated pulls converge instead of piling up. That behavior is covered in Clean up rows with effects.

A single search run adds at most 1,000,000 rows. Set the limit lower than the maximum while you tune filters; you can always run again.

Next steps

Enrich rows

Add pipe columns over the rows you brought in.

Clean up rows

Deduplicate and filter with effects.