Reward Sciences
Reward Sciences is an easy-to-use platform that enables organizations to incentivize and reward human behaviors wherever and whenever they benefit the business.
Integrate the Reward Sciences API with the Python API
Setup the Reward Sciences API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Reward Sciences and Python remarkably fast. Free for developers.
Popular Reward Sciences 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 Reward Sciences#
The Reward Sciences API enables the integration of loyalty and rewards functionalities into your services. With it, you can create and manage rewards programs, automate point distribution, track user activities, and redeem rewards. On Pipedream, you can tap into these capabilities to build automated workflows that interact with other apps, trigger actions based on events, and manipulate data to enhance customer engagement.
Connect Reward Sciences#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
reward_sciences: {
type: "app",
app: "reward_sciences",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.rewardsciences.com/reward_categories`,
headers: {
Authorization: `Bearer ${this.reward_sciences.$auth.api_token}`,
"Accept": `application/vnd.rewardsciences.v1+json`,
"Content-Type": `application/json`,
},
})
},
})
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}}