Building a DeFi Lending Application with Python (Part 2)

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In the traditional fintech world, developers have long relied on sophisticated tools to build algorithmic trading systems and financial applications. Today, decentralized finance (DeFi) offers similar — if not greater — flexibility, transparency, and composability, enabling developers to create innovative financial products that were previously impossible. One of the core functionalities in DeFi is non-custodial lending and borrowing of digital assets. This article dives into how you can leverage Python to interact with DeFi protocols like Aave and automate deposit, borrowing, and repayment processes on the blockchain.

If you haven’t already, we recommend reviewing Part 1 of this series before continuing.

Depositing Collateral

To begin, we’ll run a script named aave_borrow.py, which performs four key operations:

Let’s start by examining the beginning of the main function:

def main():
    account = get_account()
    erc20_address = config["networks"][network.show_active()]["weth_token"]

    if network.show_active() in ["mainnet-fork"]:
        get_weth(account=account)

    lending_pool = get_lending_pool()

First, we retrieve our wallet address using the get_account() function. If we're working on a test network like a local fork of Ethereum mainnet, this function pulls the account from Hardhat or Ganache. We also fetch the WETH token address from the configuration file. On testnets, we ensure our wallet holds WETH by calling get_weth(), which mints WETH in exchange for ETH.

The most important component here is the lending_pool — a smart contract that manages all lending and borrowing logic on Aave. This contract provides essential functions such as:

Smart contracts in DeFi function similarly to classes in traditional software development — each comes with predefined methods. You can verify this by printing type(lending_pool); it will return a contract object, just like the WETH token interface.

👉 Discover how blockchain automation can simplify DeFi interactions.

How to Get the Lending Pool Contract

To interact with any smart contract, we need two things: its ABI (Application Binary Interface) and its on-chain address. In our case, we use an interface defined in the interfaces folder, following the common naming convention of prefixing interfaces with "I", such as ILendingPool.

However, Aave doesn’t expose the lending pool address directly. Instead, we must query the LendingPoolAddressesProvider contract, which acts as a registry for all protocol addresses. This design ensures resilience — even if the lending pool upgrades, the provider remains constant.

Here’s how we retrieve it:

def get_lending_pool():
    lending_pool_addresses_provider = interface.ILendingPoolAddressesProvider(
        config["networks"][network.show_active()]["lending_pool_addresses_provider"]
    )
    lending_pool_address = lending_pool_addresses_provider.getLendingPool()
    lending_pool = interface.ILendingPool(lending_pool_address)
    return lending_pool

This method guarantees we always connect to the correct and up-to-date lending pool.

Approving and Depositing Tokens

Before depositing collateral, we must approve the lending pool to spend our tokens. This is a standard security feature of ERC-20 tokens: no contract can transfer your funds without explicit permission.

We use the following function:

approve_erc20(amount, lending_pool.address, erc20_address, account)

And here's what happens inside:

def approve_erc20(amount, lending_pool_address, erc20_address, account):
    print("Approving ERC20...")
    erc20 = interface.IERC20(erc20_address)
    tx_hash = erc20.approve(lending_pool_address, amount, {"from": account})
    tx_hash.wait(1)
    print("Approved!")
    return True

Key parameters:

After approval, we proceed to deposit:

print("Depositing...")
lending_pool.deposit(erc20_address, amount, account.address, 0, {"from": account})
print("Deposited!")

This triggers three on-chain events visible via Etherscan:

  1. Minting of aTokens (e.g., aWETH)
  2. Transfer of WETH to the lending pool
  3. Receipt of aTokens by your wallet

Understanding aTokens

aTokens represent your share in the liquidity pool. They accrue interest in real time — their balance increases automatically as borrowers pay interest. When you withdraw, your aTokens are burned, and you receive the underlying asset plus accumulated yield.

You can even track your aWETH balance in MetaMask by adding the token contract manually (on Kovan: 0x87b1f4cf9bd63f7bbd3ee1ad04e8f52540349347).

Borrowing Assets Against Collateral

With collateral deposited, you’re now eligible to borrow — but only up to a certain limit determined by your health factor and loan-to-value (LTV) ratio.

Why borrow?

For example, if you deposit 1 ETH and borrow 0.5 ETH worth of DAI, your health factor remains strong. But if debt exceeds safe thresholds, your position becomes vulnerable to liquidation.

Aave uses a liquidation mechanism: when health factor drops below 1, third parties can repay part of your debt and claim collateral at a discount — incentivizing protocol safety.

To determine borrowing capacity, we call:

borrowable_eth, total_debt_eth = get_borrowable_data(lending_pool, account)

Which uses:

def get_borrowable_data(lending_pool, account):
    (
        total_collateral_eth,
        total_debt_eth,
        available_borrow_eth,
        current_liquidation_threshold,
        tlv,
        health_factor,
    ) = lending_pool.getUserAccountData(account.address)

    available_borrow_eth = Web3.fromWei(available_borrow_eth, "ether")
    total_collateral_eth = Web3.fromWei(total_collateral_eth, "ether")
    total_debt_eth = Web3.fromWei(total_debt_eth, "ether")

    print(f"You have {total_collateral_eth} worth of ETH deposited.")
    print(f"You have {total_debt_eth} worth of ETH borrowed.")
    print(f"You can borrow {available_borrow_eth} worth of ETH.")

    return float(available_borrow_eth), float(total_debt_eth)

This returns critical metrics including:

Note: Some functions like getUserAccountData are view functions — they read blockchain state without requiring gas. Only state-changing actions (like deposits or borrows) require transactions.

Executing the Borrow Operation

Once we know how much we can borrow, we calculate the equivalent amount in the target asset (e.g., DAI):

borrowable_eth, total_debt_eth = get_borrowable_data(lending_pool, account)
print("LET'S BORROW IT ALL!")

erc20_eth_price = get_asset_price()
amount_erc20_to_borrow = (1 / erc20_eth_price) * (borrowable_eth * 0.95)

print(f"We are going to borrow {amount_erc20_to_borrow} DAI")
borrow_erc20(lending_pool, amount_erc20_to_borrow, account)

We apply a 95% buffer to avoid hitting liquidation limits due to price fluctuations.

👉 Learn how automated scripts can optimize DeFi yield strategies.

Frequently Asked Questions

Q: What is a health factor in DeFi lending?
A: The health factor measures how close your position is to liquidation. A value above 1 means your loan is safely collateralized; below 1 triggers potential liquidation.

Q: Why do I need to approve tokens before depositing?
A: ERC-20 tokens require explicit approval for security reasons. Without it, smart contracts cannot move your funds.

Q: What are aTokens and how do they earn interest?
A: aTokens are interest-bearing tokens minted upon deposit. Their balance grows over time as borrowers pay interest into the pool.

Q: Can I lose money using DeFi lending protocols?
A: Yes — through liquidations if your health factor drops too low, or via smart contract risks. Always monitor positions and use safety margins.

Q: Is this system non-custodial?
A: Yes. You retain full control of your assets. The protocol uses smart contracts instead of intermediaries.

Q: Can I automate repayments using Python?
A: Absolutely. With proper monitoring and scheduling tools, you can fully automate deposits, borrows, and repayments.

👉 Start building automated DeFi strategies today.

By combining Python scripting with DeFi protocols like Aave, developers gain powerful tools to create custom financial applications — from algorithmic hedging to automated yield optimization. As blockchain ecosystems evolve, these skills will become increasingly vital for fintech innovation.

This concludes Part 2 of our series on building DeFi applications with Python. Stay tuned for Part 3, where we’ll cover loan repayment automation and real-time health monitoring.