Overledger
Overledger Platform. The enterprise standard for building on blockchain.
Integrate the Overledger API with the Python API
Setup the Overledger API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Overledger and Python remarkably fast. Free for developers.
Popular Overledger and Python Actions#
Executes a signed transaction by sending it to a blockchain node via Overledger. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Prepares a smart contract transaction for signing on the Overledger platform. See the documentation
Overview of Overledger#
The Overledger API by Quant Network allows developers to interact with multiple blockchain networks. It facilitates the creation, reading, and execution of smart contracts and transactions across different blockchains. This API simplifies the complex nature of blockchain interoperability, enabling multi-chain applications (MApps) through a single gateway.
Connect Overledger#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
overledger: {
type: "app",
app: "overledger",
}
},
async run({steps, $}) {
const data = {
"location": {
"technology": "Ethereum",
"network": "Ethereum Sepolia Testnet"
}
}
return await axios($, {
method: "post",
url: `https://api.sandbox.overledger.io/v2/autoexecution/search/block/latest`,
headers: {
Authorization: `Bearer ${this.overledger.$auth.oauth_access_token}`,
"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}}