Search hundreds of datasets from the City and County of San Francisco
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
The San Francisco Open Data - DataSF API unlocks a wealth of government data spanning multiple domains such as transportation, housing, and public health. It provides developers with access to rich datasets, which can be integrated into applications to derive insights, inform decision-making, and power data-driven solutions. Pipedream's serverless platform amplifies this potential by enabling users to create automated workflows that leverage this data in concert with other apps and services.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
san_francisco_open_data_datasf: {
type: "app",
app: "san_francisco_open_data_datasf",
}
},
async run({steps, $}) {
// Below, we fetch a range of COVID-19 case data from DataSF. You can
// run this to see how the results are displayed on Pipedream, or modify it
// in any way to fetch data from another dataset or modify the Socrata
// query. See the docs below for Socrata docs and examples.
// COVID-19 Cases Summarized by Date, Transmission and Case Disposition
// https://dev.socrata.com/foundry/data.sfgov.org/tvq9-ec9w
return await axios($, {
url: `https://data.sfgov.org/resource/tvq9-ec9w.json`,
headers: {
"X-App-Token": `${this.san_francisco_open_data_datasf.$auth.app_token}`,
},
params: {
"$where": `date between '2020-05-18T00:00:00' and '2020-05-20T00:00:00'`,
},
})
},
})
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)
}