What You Will Build

By the end of Bundle 1, you will have built: ✅ A live Python connection to an Ethereum execution client via JSON-RPC ✅ A reusable Web3.py contract interaction framework ✅ A raw Swap log retrieval system using eth_getLogs ✅ An ABI-based event decoding pipeline ✅ A normalized swap-level pandas DataFrame ✅ A per-trade execution price calculation engine ✅ A block-timestamp mapping workflow ✅ A time-ordered on-chain price series derived from real swaps ✅ Derived trade metrics (volume, direction, estimated fees) ✅ A mini analytics dashboard built from execution-layer data ✅ Exportable CSV datasets ready for research or production workflows

Who This Is For

This program is designed for: ✅ Developers ✅ Quantitative analysts ✅ Data Scientists ✅ Academia Ideal for technically inclined learners who are: ✅ Comfortable with Python ✅ Want to build real on-chain analytics pipelines 

Part of the DeFiPy Analytics Track

This course is the first stage in a structured DeFi analytics pathway built around the DeFiPy ecosystem. DeFiPy is a Python-based analytics framework for: ✅ Reconstructing AMM state ✅ Modeling LP returns ✅ Simulating liquidity behavior ✅ Building production-grade analytics pipelines Bundle 1 focuses on the foundational layer: RPC, logs, Web3.py, and data normalization. Bundles 2 and 3 build directly into: ✅ AMM mathematics ✅ Simulation engines ✅ Off-chain state reconstruction ✅ Production pipeline architecture You are not just learning isolated scripts. You are entering a complete analytics framework.

Program Structure

🔴 4.5+ hours of structured instruction 🔴 8 lessons 🔴 71 total video sections 🔴 ncluding 18 hands-on coding sessions 🔴 4 Jupyter notebooks 🔴 ABIs and sample datasets included 🔴 End-to-end pipeline build + dashboard project

Program Instructor

Ian Moore, PhD Founding Core Developer of DeFiPy Author, DeFiPy: Python SDK for On-Chain Analytics Ian Moore is the founding core developer of DeFiPy and author of DeFiPy: Python SDK for On-Chain Analytics. His work focuses on execution-layer data engineering, automated market maker systems, and structured DeFi analytics pipelines. He has presented his research and engineering work at ETHDenver (2024), previously worked within blockchain infrastructure at Syscoin, and has served as an adjunct instructor at the University of Toronto. His teaching and development work bridges blockchain systems, quantitative modeling, and production analytics engineering. This program reflects the same systematic approach used in the development of DeFiPy, which is integrating execution-layer mechanics, formal AMM intuition, and production-grade Python workflows. 🔗 DAPX-Anchor: https://anchorregistry.ai/AR-2026-14KnMz5

Course Curriculum

9 Chapters · 71 Lessons

  1. 1

    Introduction

    1. Welcome Free preview
  2. 2

    What is On-Chain Analytics

    1. (Included in full purchase)

      Outline and Definitions

    2. (Included in full purchase)

      EVM Foundations

    3. (Included in full purchase)

      On-Chain Data Types

    4. (Included in full purchase)

      RPC Fundamentals

    5. (Included in full purchase)

      The On-Chain Analytics Workflow

  3. 3

    Ethereum Node Architecture & RPC Deep Dive

    1. (Included in full purchase)

      Outline and Why Node Architecture Matters

    2. (Included in full purchase)

      Execution vs. Consensus

    3. (Included in full purchase)

      Node Types and JSON RPC

    4. (Included in full purchase)

      JSON RPC and RPC Providers

    5. (Included in full purchase)

      Closing and Transition to Lesson 3

  4. 4

    Python Foundations for DeFi Web3.py Basics

    1. (Included in full purchase)

      Environment Setup

    2. (Included in full purchase)

      Introduction

    3. (Included in full purchase)

      Environment Setup and Web3.py Connection

    4. (Included in full purchase)

      Coding 1 – Connecting with Web3.py

    5. (Included in full purchase)

      Application Binary Interfaces (ABIs)

    6. (Included in full purchase)

      Coding 2 - Working with ABIs

    7. (Included in full purchase)

      Contract Objects

    8. (Included in full purchase)

      Coding 3 - Working with Contract Objects

    9. (Included in full purchase)

      Closing and Transition to Lesson 4

    10. (Included in full purchase)

      Lesson 3 Jupyter Notebook (code)

    11. (Included in full purchase)

      ABI - UniswapV3 (needed for Jupyter)

  5. 5

    Querying Logs, ABI Decoding & Events

    1. (Included in full purchase)

      Introduction

    2. (Included in full purchase)

      Logs & Events

    3. (Included in full purchase)

      Querying Logs with JSON-RPC

    4. (Included in full purchase)

      Coding 1 - Retrieving and Inspecting Logs

    5. (Included in full purchase)

      ABI Decoding

    6. (Included in full purchase)

      Coding 2 - Decoding Logs

    7. (Included in full purchase)

      Swap Event Decoding

    8. (Included in full purchase)

      Coding 3 - Decoding Swap Events into DataFrames

    9. (Included in full purchase)

      Closing and Optional Excercise

    10. (Included in full purchase)

      Lesson 4 Jupyter Notebook

    11. (Included in full purchase)

      ABI - UniswapV2 (needed for coding)

  6. 6

    AMM Concepts 1: Mental Models of Liquidity

    1. (Included in full purchase)

      Designing Your Analytics Pipeline

    2. (Included in full purchase)

      AMM Curve Intuition

    3. (Included in full purchase)

      Slippage & Trade Size

    4. (Included in full purchase)

      LP Mechanics

    5. (Included in full purchase)

      Closing and Transition into Lesson 6

  7. 7

    AMM Concepts II: Impermanent Loss & Ranges

    1. (Included in full purchase)

      Introduction

    2. (Included in full purchase)

      LP Payoff Geometry

    3. (Included in full purchase)

      Impermanent Loss

    4. (Included in full purchase)

      Oscillating vs Trending Markets

    5. (Included in full purchase)

      Concentrated Liquidity

    6. (Included in full purchase)

      Uniswap v2 to v3

  8. 8

    Building Your First On-Chain Pipeline

    1. (Included in full purchase)

      Introduction and Pipeline Overview

    2. (Included in full purchase)

      Pulling Raw Logs

    3. (Included in full purchase)

      Coding 1 - Fetching Raw Logs

    4. (Included in full purchase)

      Decoding Logs

    5. (Included in full purchase)

      Coding 2 - Decoding Swap Events

    6. (Included in full purchase)

      Normalizing Decoded Events

    7. (Included in full purchase)

      Coding 3 - Normalize Events to Dataframes

    8. (Included in full purchase)

      Computing Direction and Price

    9. (Included in full purchase)

      Coding 4 - Computing Execution Price

    10. (Included in full purchase)

      Attaching Block Timestamps

    11. (Included in full purchase)

      Coding 5 - Block Timestamps

    12. (Included in full purchase)

      Price Series

    13. (Included in full purchase)

      Coding 6 - Building a Price Series

    14. (Included in full purchase)

      Closing - Your First On-Chain Pipeline

    15. (Included in full purchase)

      Lesson 7 Jupyter Notebook

    16. (Included in full purchase)

      ABI - UniswapV2 (needed for coding)

  9. 9

    Mini Analytics Project: Simple Dashboard

    1. (Included in full purchase)

      Introduction and Data Preparation

    2. (Included in full purchase)

      Coding 1 - Load Data and Sanitize

    3. (Included in full purchase)

      Computing Derived Metrics

    4. (Included in full purchase)

      Coding 2 - Computing Price, Volume and Fees

    5. (Included in full purchase)

      Dashboard Construction

    6. (Included in full purchase)

      Coding 3 - Aggregate Metrics

    7. (Included in full purchase)

      Export Results

    8. (Included in full purchase)

      Coding 4 - CVSs for Future Development

    9. (Included in full purchase)

      Roadmap to Bundles 2 & 3 using DeFiPy

    10. (Included in full purchase)

      Lesson 8 Jupyter Notebook

    11. (Included in full purchase)

      usdc_weth_swaps_clean.csv

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