Table of Contents

On March 22, it was announced that the Cosmos ecological smart contract platform Injective Test Network integrated with the Python Network, allowing developers to build DApps to access high-fidelity and high-frequency market data for various assets. This is the first time Python data supports the Cosmos ecosystem. Python Network introduces an innovative on-demand pull model oracle that allows users to push available prices onto the chain when needed, and enables everyone in the blockchain environment to access the data point. Python runs on Injective and is implemented by Wormhole. Publishers can send data directly to Python in the form of transactions, and then place these data assets on the chain. When a target chain (such as Injective) requests data, Python can send data through Wormhole.

The Injective Test Network integrates with the Python Network, allowing developers to build DApps to access agency data

1. Introduction
2. The Integration of Injective Test Network and Python Network
3. The Advantages of Using Python Network for the Cosmos Ecosystem
4. The Innovative On-Demand Pull Model Oracle
5. How Python Network Enables Access to High-Fidelity and High-Frequency Market Data
6. Python’s Implementation on Injective and Wormhole
7. Publishers’ Direct Data Sending
8. Conclusion
9. FAQs
# Injective Test Network Integrates with Python Network: Empowering DApp Developers with High-Fidelity Market Data

Introduction

On March 22, the Cosmos ecological smart contract platform Injective Test Network announced its integration with the Python Network. This integration enables DApp developers to access high-fidelity and high-frequency market data for various assets for the first time in the Cosmos ecosystem. Python Network offers an innovative on-demand pull model oracle that allows users to push available prices onto the chain when needed, enabling everyone in the blockchain environment to access the data points.

The Integration of Injective Test Network and Python Network

Injective Test Network has been established to provide decentralized trading services to users globally. The platform is supported by the Cosmos ecosystem, and the integration with Python Network marks the first time that Python data supports this ecosystem. Through this integration, developers can build DApps that can access high-fidelity and high-frequency market data, enabling them to make more informed decisions.

The Advantages of Using Python Network for the Cosmos Ecosystem

Python Network enables the injection of any and all data oracles onto the blockchain, allowing developers to get the data they need in real-time. This feature is particularly advantageous when it comes to accessing market data, where timely access to accurate data points is essential for making informed decisions. Python Network also facilitates better scalability, as developers can build on it without worrying about the network’s congestion.

The Innovative On-Demand Pull Model Oracle

Python Network’s on-demand pull model oracle enables users to push prices onto the chain when required. This on-demand model ensures that no unnecessary data is added to the blockchain, making sure that the chain remains lean and concise. The pull model oracle also ensures that no data is left out, as developers can get any data they need, on-demand.

How Python Network Enables Access to High-Fidelity and High-Frequency Market Data

Python Network allows publishers to send data directly to Python in the form of transactions that can be placed on the chain. When a target chain, such as Injective, requests data, Python can provide the data through Wormhole. This feature enables DApp developers to access high-fidelity and high-frequency market data quickly and efficiently, providing them with a competitive edge in a volatile market.

Python’s Implementation on Injective and Wormhole

Python Network’s implementation on Injective is supported by Wormhole. This implementation ensures that the data is transmitted securely across the blockchain. Wormhole is a decentralized infrastructure that enables cross-chain communication, providing a secure and efficient means of data transfer between different chains.

Publishers’ Direct Data Sending

Publishers can send their data directly to Python in the form of transactions, ensuring that the data is added to the chain accurately and securely. This feature enables publishers to ensure that their data is used correctly and provides them with a competitive edge in the market.

Conclusion

The integration of Injective Test Network with Python Network marks a significant milestone in the Cosmos ecosystem, allowing DApp developers to access high-fidelity and high-frequency market data quickly and efficiently. Python Network’s innovative on-demand pull model oracle ensures that the chain is lean, and only necessary data is added. This integration is a significant advancement in the blockchain market, providing DApp developers with a competitive edge.

FAQs

1. What is Injective Test Network?
Injective Test Network is a decentralized trading platform that provides global users with decentralized trading services.
2. What is Python Network?
Python Network is a data oracle network that allows developers to access high-fidelity and high-frequency market data for various assets in the blockchain.
3. What advantages does Python Network offer to DApp developers?
Python Network provides DApp developers with real-time access to market data, offering them a competitive edge in the market. Python Network also allows publishers to send their data directly to the chain, ensuring that their data is used correctly.