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gwfintechp1

https://docs.google.com/document/d/1klm7VtHYTkM3WEaCk-lgPEbygAx2n8mzEguT2XYj4C8/edit?usp=sharing

GW defi WhitePaper https://aave-api-v2.aave.com/data/markets-data/0xd05e3e715d945b59290df0ae8ef85c1bdb684744 https://docs.matic.network/docs/develop/tools/matic-gas-station/ https://blog.chain.link/develop-python-defi-project/ Dependencies

https://github.com/aave/protocol-v2/blob/master/markets/matic/rateStrategies.ts

Web3.py

https://web3py.readthedocs.io/en/stable/

GraphQL

https://thegraph.com/explorer/subgraph/aave/aave-v2-matic?selected=playground https://github.com/graphql/graphiql https://github.com/aave/protocol-v2-subgraph https://github.com/profusion/sgqlc

APIs

https://thegraph.com/explorer/subgraph/aave/aave-v2-matic?selected=playground https://aave-api-v2.aave.com/data/markets-data/0xd05e3e715d945b59290df0ae8ef85c1bdb684744

AAVE.js

https://github.com/aave/aave-js https://github.com/aave/protocol-v2/blob/master/markets/matic/rateStrategies.ts https://github.com/aave/protocol-v2

Pricing https://docs.1inch.io/api/ https://towardsdatascience.com/connecting-to-a-graphql-api-using-python-246dda927840

Development Calling Data Lending Data Borrowing Data Price Data Market Data Gas Data

Formatting Data Format data to help make decisions

Strategy Table We need a list of strategies and the math with them User input for stratgiers

Notification Suite Tell user, maybe show user the options

Execution Suite Actually execute it on chain Testing Historical - Go through compound, aave rates backtest strategies

May need SQL for this

Monte carlo testing on positions

import requests import json import pandas as pd query = """query {
reserves(first:10) { symbol name price { priceHistory (first: 10) { id asset { id } price timestamp } } stableBorrowRate variableBorrowRate } }""" url = 'https://api.thegraph.com/subgraphs/name/aave/aave-v2-matic' r = requests.post(url, json={'query': query}) print(r.status_code) print(r.text) json_data = json.loads(r.text) df_data = json_data['data']['reserves'] df = pd.DataFrame(df_data) df

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