Find Cities & Towns with GeoDB Cities API.
Find cities, filtering by optional criteria. If no criteria are set, you will get back all known cities with a population of at least 1000. See the docs.
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Get the details for a specific country, including number of regions. See the docs.
Get the details of a specific country region, including number of cities. See the docs.
The GeoDB Cities API lets you tap into a rich dataset of worldwide cities, their attributes, and related data. On Pipedream, you can use this API to create workflows that automate location-based tasks, enrich data with geographical context, or power apps with location intelligence. For instance, you could trigger a workflow whenever a new city is added to a database, gather demographic information based on city names, or even integrate with travel platforms to plan itineraries.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
geodb_cities: {
type: "app",
app: "geodb_cities",
}
},
async run({steps, $}) {
const data = {
"query": `{country(id:"US"){name region(code:"CA"){name populatedPlaces(first:10){totalCount pageInfo{startCursor endCursor hasNextPage}edges{node{name}}}}}}`,
}
return await axios($, {
method: "post",
url: `http://geodb-free-service.wirefreethought.com/graphql`,
headers: {
"x-rapidapi-key": `${this.geodb_cities.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}