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with Placekey and Python?
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Popular Placekey and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Placekey#
The Placekey API is a powerful tool for standardizing and enriching location data. With Placekey, you can translate addresses or points of interest into a unique, universal location identifier, making it easier to integrate and compare data across different databases or platforms. On Pipedream, you can leverage this API to automate tasks that require precise location matching, enrichment, and deduplication, thus enhancing data analysis, business intelligence, marketing campaigns, and logistic operations.
Connect Placekey#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
placekey: {
type: "app",
app: "placekey",
}
},
async run({steps, $}) {
const data = {
query: {
city: [CITY],
region: [REGION],
street_address: [STREET_ADDRESS],
postal_code: [POSTAL_CODE],
iso_country_code: [ISO_COUNTRY_CODE]
},
options: {
strict_name_match: false,
},
}
return await axios($, {
method: "post",
url: `https://api.placekey.io/v1/placekey`,
headers: {
"apikey": `${this.placekey.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
Overview of Python#
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow
This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
Connect Python#
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies