* feat: analyze profits - closes #19 Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * feat: analyze profits - closes #19 Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * fix peotry lock Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * feat: add save to csv option Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * fix: update dockerfile to resolve deps automatically at build-time Signed-off-by: Luca Georges Francois <luca@quartz.technology> * feat: add porfit by day Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * feat: add failures saving Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * fix: launch script Signed-off-by: Arthurim <arthurbdauphine@gmail.com> * feat: get rpc url from env Signed-off-by: Arthurim <arthurbdauphine@gmail.com> Signed-off-by: Arthurim <arthurbdauphine@gmail.com> Signed-off-by: Luca Georges Francois <luca@quartz.technology> Co-authored-by: Luca Georges Francois <luca@quartz.technology>
This commit is contained in:
Eru Ilúvatar
GitHub
parent
880992362b
commit
bfbf1cc379
3
.gitignore
vendored
3
.gitignore
vendored
@ -25,3 +25,6 @@ cache
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# pycharm
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.idea
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# generated csvs
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*.csv
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@ -18,7 +18,7 @@ WORKDIR /app/
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USER flashbot
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RUN poetry config virtualenvs.create false \
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&& poetry install
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&& rm poetry.lock ; poetry lock && poetry install
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COPY --chown=flashbot . /app
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23
cli.py
23
cli.py
@ -6,6 +6,8 @@ from datetime import datetime
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import click
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import dramatiq
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from profit_analysis.analysis import analyze_profit, get_profit_by
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from profit_analysis.column_names import BLOCK_KEY
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from mev_inspect.concurrency import coro
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from mev_inspect.crud.prices import write_prices
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@ -47,6 +49,27 @@ async def inspect_block_command(block_number: int, rpc: str):
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)
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@cli.command()
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@click.argument("block_from", type=int)
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@click.argument("block_to", type=int)
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@click.argument("save_to_csv", type=bool)
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@coro
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async def analyze_profit_command(
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block_from: int, block_to: int, save_to_csv: bool = False
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):
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inspect_db_session = get_inspect_session()
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profit = analyze_profit(inspect_db_session, block_from, block_to, save_to_csv)
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print(" -------------------------------------------------------------------")
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print(" Profit By Block")
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print(get_profit_by(profit, BLOCK_KEY, save_to_csv))
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print(" -------------------------------------------------------------------")
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print(" Profit By Day")
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print(get_profit_by(profit, "date", save_to_csv))
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print(" -------------------------------------------------------------------")
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print(" Profit By Category")
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print(get_profit_by(profit, "category", save_to_csv))
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@cli.command()
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@click.argument("block_number", type=int)
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@click.option("--rpc", default=lambda: os.environ.get(RPC_URL_ENV, ""))
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20
launch_analysis.py
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20
launch_analysis.py
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@ -0,0 +1,20 @@
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import sys
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from profit_analysis.analysis import analyze_profit, get_profit_by
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from profit_analysis.column_names import BLOCK_KEY
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from mev_inspect.db import get_inspect_session
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block_from = int(sys.argv[1])
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block_to = int(sys.argv[2])
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inspect_db_session = get_inspect_session()
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profit = analyze_profit(inspect_db_session, block_from, block_to, True)
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print(" -------------------------------------------------------------------")
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print(" Profit By Block")
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print(get_profit_by(profit, BLOCK_KEY, True))
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print(" -------------------------------------------------------------------")
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print(" Profit By Day")
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print(get_profit_by(profit, "date", True))
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print(" -------------------------------------------------------------------")
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print(" Profit By Category")
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print(get_profit_by(profit, "category", True))
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10
mev
10
mev
@ -68,6 +68,14 @@ case "$1" in
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kubectl exec -ti deploy/mev-inspect -- \
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poetry run inspect-many-blocks $after_block_number $before_block_number
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;;
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analyze-profit)
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after_block_number=$2
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before_block_number=$3
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save_to_csv=$4
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echo "Analyzing profit from block $after_block_number to $before_block_number"
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kubectl exec -ti deploy/mev-inspect -- \
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poetry run analyze-profit $after_block_number $before_block_number $save_to_csv
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;;
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test)
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shift
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echo "Running tests"
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@ -122,7 +130,7 @@ case "$1" in
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kubectl exec -ti deploy/mev-inspect -- $@
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;;
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*)
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echo "Usage: "$1" {db|backfill|inspect|test}"
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echo "Usage: "$1" {db|backfill|inspect|test|analyze-profit}"
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exit 1
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esac
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29
mev_inspect/crud/read.py
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29
mev_inspect/crud/read.py
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import pandas as pd
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def read_from_db_all_into_dataframe(db_session, table, columns, where_clause):
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"""
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Reads all relevant rows from the DB as a df
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:param db_session:
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:param table:
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:param columns:
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:param where_clause:
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:return:
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"""
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query = "SELECT " + columns + " FROM " + table
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if where_clause != "":
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query += " WHERE " + where_clause
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result = db_session.execute(query)
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return result
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def read_profit_from_to(db_session, block_from, block_to):
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where_clause = (
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"block_number>=" + str(block_from) + " AND " + "block_number<=" + str(block_to)
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)
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profit = read_from_db_all_into_dataframe(
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db_session, "total_profit_by_block", "*", where_clause
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)
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profit = pd.DataFrame(profit.fetchall())
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profit = profit.drop(["id"], axis=1)
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return profit
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1694
poetry.lock
generated
1694
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
0
profit_analysis/__init__.py
Normal file
0
profit_analysis/__init__.py
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262
profit_analysis/analysis.py
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262
profit_analysis/analysis.py
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@ -0,0 +1,262 @@
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import datetime
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import os
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import pandas as pd
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import web3
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from profit_analysis.block_utils import add_block_timestamp
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from profit_analysis.coingecko import (
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add_cg_ids,
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get_address_to_coingecko_ids_mapping,
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get_coingecko_historical_prices,
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)
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from profit_analysis.column_names import (
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AMOUNT_DEBT_KEY,
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AMOUNT_RECEIVED_KEY,
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CG_ID_DEBT_KEY,
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CG_ID_RECEIVED_KEY,
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DECIMAL_DEBT_KEY,
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PRICE_DEBT_KEY,
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PRICE_KEY,
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PRICE_RECEIVED_KEY,
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TIMESTAMP_KEY,
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TOKEN_DEBT_KEY,
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TOKEN_RECEIVED_KEY,
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)
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from profit_analysis.constants import DATA_PATH
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from profit_analysis.token_utils import get_decimals
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from mev_inspect.crud.read import read_profit_from_to
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"""
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Steps:
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1. given blockfrom and block to, read the profit
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"""
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WETH_TOKEN_ADDRESS = "0x7ceB23fD6bC0adD59E62ac25578270cFf1b9f619"
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PD_DATETIME_FORMAT = "datetime64[ns]"
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def analyze_profit(inspect_db_session, block_from, block_to, save_to_csv=False):
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profit = read_profit_from_to(inspect_db_session, block_from, block_to)
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w3 = create_web3()
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profit = add_block_timestamp(w3, profit)
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profit = add_cg_ids(profit)
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profit = get_usd_profit(profit, save_to_csv)
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print(profit)
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return profit
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def get_usd_profit(profit, save_to_csv=False):
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"""
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For each token involved in mev transactions, will get its price at the time of the transaction and
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compute the profit of each mev transaction.
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:param profit: pd.DataFrame, with columns = ['block_number', 'timestamp', 'transaction_hash',
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'token_debt', 'amount_debt', 'cg_id_debt',
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'token_received', 'amount_received', 'cg_id_received']
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:param save_to_csv: bool, whether to save the analysed profits to csv or not
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:return: pd.DataFrame, with columns = ['block_number', 'timestamp', 'date', 'transaction_hash',
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'amount_received', 'token_received', 'price_received',
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'amount_debt', 'token_debt', 'price_debt',
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'profit_usd' ]
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"""
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tokens = profit[CG_ID_RECEIVED_KEY].unique()
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mapping = get_address_to_coingecko_ids_mapping()
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profit_with_price_tokens = pd.DataFrame()
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failures = {}
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for token in tokens:
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print("Processing", token)
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try:
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profit_by_received_token = pd.DataFrame(
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profit.loc[profit[CG_ID_RECEIVED_KEY] == token]
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)
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profit_by_received_token[TIMESTAMP_KEY] = pd.to_datetime(
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profit_by_received_token[TIMESTAMP_KEY], format="%Y-%m-%d %H:%M:%S"
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)
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dates = pd.to_datetime(profit_by_received_token[TIMESTAMP_KEY].unique())
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# @TODO: What is an optimal value here?
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# looks like sometimes there is no price for hours???
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offset_minutes = 30
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date_min = int(
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(dates.min() - datetime.timedelta(minutes=offset_minutes)).timestamp()
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)
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date_max = int(
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(dates.max() + datetime.timedelta(minutes=offset_minutes)).timestamp()
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)
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# get received token prices
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token_prices = get_coingecko_historical_prices(date_min, date_max, token)
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token_prices = token_prices.rename(columns={PRICE_KEY: PRICE_RECEIVED_KEY})
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token_prices[TOKEN_RECEIVED_KEY] = token
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# get received token decimals
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decimals = get_decimals(
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profit_by_received_token[TOKEN_RECEIVED_KEY].values[0]
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)
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# get debt tokens prices
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debt_tokens_prices = pd.DataFrame()
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for cg_id_debt in (
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profit_by_received_token[CG_ID_DEBT_KEY].astype(str).unique().tolist()
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):
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if cg_id_debt != "nan":
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debt_token_prices = get_coingecko_historical_prices(
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date_min, date_max, cg_id_debt
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)
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debt_token_prices[CG_ID_DEBT_KEY] = cg_id_debt
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debt_token = mapping.loc[
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mapping[CG_ID_DEBT_KEY] == cg_id_debt, TOKEN_DEBT_KEY
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].values[0]
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debt_token_prices[TOKEN_DEBT_KEY] = debt_token
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debt_tokens_prices = pd.concat(
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[debt_tokens_prices, debt_token_prices]
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)
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debt_tokens_prices = debt_tokens_prices.rename(
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columns={PRICE_KEY: PRICE_DEBT_KEY}
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)
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# get debt tokens decimals
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debt_tokens_decimals = pd.DataFrame(
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columns=[TOKEN_DEBT_KEY, DECIMAL_DEBT_KEY]
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)
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for debt_token in (
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profit_by_received_token[TOKEN_DEBT_KEY].astype(str).unique().tolist()
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):
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if debt_token != "":
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debt_token_decimals = get_decimals(debt_token)
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debt_tokens_decimals = pd.concat(
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[
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debt_tokens_decimals,
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pd.DataFrame(
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[[debt_token, debt_token_decimals]],
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columns=[TOKEN_DEBT_KEY, DECIMAL_DEBT_KEY],
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),
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]
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)
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profit_by_received_token = profit_by_received_token.merge(
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debt_tokens_decimals, on=TOKEN_DEBT_KEY, how="outer"
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)
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profit_by_received_token.loc[
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pd.isna(profit_by_received_token[AMOUNT_DEBT_KEY]), AMOUNT_DEBT_KEY
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] = 0
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# apply decimals
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profit_by_received_token[AMOUNT_RECEIVED_KEY] = pd.to_numeric(
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profit_by_received_token[AMOUNT_RECEIVED_KEY]
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).div(10**decimals)
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profit_by_received_token[AMOUNT_DEBT_KEY] = pd.to_numeric(
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profit_by_received_token[AMOUNT_DEBT_KEY]
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)
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# set up timestamps for merge
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token_prices[TIMESTAMP_KEY] = pd.to_datetime(token_prices[TIMESTAMP_KEY])
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# merge received token prices
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profit_with_price_token = pd.merge_asof(
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profit_by_received_token.astype({TIMESTAMP_KEY: PD_DATETIME_FORMAT})
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.sort_values(TIMESTAMP_KEY)
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.convert_dtypes(),
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token_prices[[TIMESTAMP_KEY, PRICE_RECEIVED_KEY]]
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.astype({TIMESTAMP_KEY: PD_DATETIME_FORMAT})
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.sort_values(TIMESTAMP_KEY)
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.convert_dtypes(),
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direction="nearest",
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on=TIMESTAMP_KEY,
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)
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if len(debt_tokens_prices) > 0:
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debt_tokens_prices[TIMESTAMP_KEY] = pd.to_datetime(
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debt_tokens_prices[TIMESTAMP_KEY]
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)
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# merge debt token prices
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profit_with_price_token = pd.merge_asof(
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profit_with_price_token.astype({TIMESTAMP_KEY: PD_DATETIME_FORMAT})
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.sort_values(TIMESTAMP_KEY)
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.convert_dtypes(),
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debt_tokens_prices[[TIMESTAMP_KEY, PRICE_DEBT_KEY]]
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.astype({TIMESTAMP_KEY: PD_DATETIME_FORMAT})
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.sort_values(TIMESTAMP_KEY)
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.convert_dtypes(),
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direction="nearest",
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on=TIMESTAMP_KEY,
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by=TOKEN_DEBT_KEY,
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)
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category = "liquidation"
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else:
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category = "arbitrage"
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profit_with_price_token[PRICE_DEBT_KEY] = 0
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profit_with_price_token["category"] = category
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profit_with_price_tokens = pd.concat(
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[profit_with_price_tokens, profit_with_price_token]
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)
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except Exception as e:
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# @TODO: save into list to add later
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print(" Failed for token=", token)
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print(e)
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failures[token] = e
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print("Finished processing all tokens")
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profit_with_price_tokens[PRICE_DEBT_KEY] = profit_with_price_tokens[
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PRICE_DEBT_KEY
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].fillna(value=0)
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profit_with_price_tokens[AMOUNT_DEBT_KEY] = profit_with_price_tokens[
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AMOUNT_DEBT_KEY
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].fillna(value=0)
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profit_with_price_tokens["profit_usd"] = (
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profit_with_price_tokens[AMOUNT_RECEIVED_KEY]
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* profit_with_price_tokens[PRICE_RECEIVED_KEY]
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- profit_with_price_tokens[AMOUNT_DEBT_KEY]
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* profit_with_price_tokens[PRICE_DEBT_KEY]
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)
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profit_with_price_tokens = profit_with_price_tokens.reset_index(drop=True)
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profit_with_price_tokens["date"] = profit_with_price_tokens[
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TIMESTAMP_KEY
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].dt.normalize()
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if save_to_csv:
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profit.to_csv(DATA_PATH + "usd_profit.csv", index=False)
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pd.DataFrame(failures.items(), columns=["token", "error"]).to_csv(
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DATA_PATH + "analyze_profit_failures.csv", index=False
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)
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return profit_with_price_tokens[
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[
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"block_number",
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"timestamp",
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"date",
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"transaction_hash",
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"amount_received",
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"token_received",
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"price_received",
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"amount_debt",
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"token_debt",
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"price_debt",
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"profit_usd",
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"category",
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]
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]
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def get_profit_by(profit_with_price_tokens, col, save_to_csv=False):
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profit_by_block = (
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profit_with_price_tokens.groupby([col])
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.agg({"profit_usd": ["sum", "mean", "median", "count"]})
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.reset_index()
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)
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profit_by_block.columns = profit_by_block.columns.droplevel(0)
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profit_by_block.rename(columns={"": col}, inplace=True)
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if save_to_csv:
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file_name = DATA_PATH + "profit_by_" + col + ".csv"
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print(file_name)
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profit_by_block.to_csv(file_name, index=False)
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return profit_by_block
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def create_web3():
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web3_rpc_url = os.environ.get("RPC_URL")
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w3_provider = web3.Web3(web3.Web3.HTTPProvider(web3_rpc_url))
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w3_provider.middleware_onion.inject(web3.middleware.geth_poa_middleware, layer=0)
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if w3_provider.isConnected():
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return w3_provider
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else:
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raise Exception("Failed to connect")
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21
profit_analysis/block_utils.py
Normal file
21
profit_analysis/block_utils.py
Normal file
@ -0,0 +1,21 @@
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import datetime
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|
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import pandas as pd
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from profit_analysis.column_names import BLOCK_KEY, TIMESTAMP_KEY
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def add_block_timestamp(w3, profit_by_block):
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block_timestamp = pd.DataFrame(
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profit_by_block[BLOCK_KEY].unique(), columns=[BLOCK_KEY]
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)
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block_timestamp[TIMESTAMP_KEY] = block_timestamp[BLOCK_KEY].apply(
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lambda x: get_block_timestamp(w3, x)
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)
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return profit_by_block.merge(block_timestamp, on=BLOCK_KEY)
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def get_block_timestamp(w3, block):
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block_info = w3.eth.get_block(int(block))
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ts = block_info[TIMESTAMP_KEY]
|
||||
dt = datetime.datetime.fromtimestamp(ts)
|
||||
return dt
|
||||
71
profit_analysis/coingecko.py
Normal file
71
profit_analysis/coingecko.py
Normal file
@ -0,0 +1,71 @@
|
||||
import pandas as pd
|
||||
import pycoingecko as pg
|
||||
from profit_analysis.column_names import (
|
||||
CG_ID_DEBT_KEY,
|
||||
CG_ID_KEY,
|
||||
CG_ID_RECEIVED_KEY,
|
||||
PRICE_KEY,
|
||||
TIMESTAMP_KEY,
|
||||
TOKEN_DEBT_KEY,
|
||||
TOKEN_KEY,
|
||||
TOKEN_RECEIVED_KEY,
|
||||
)
|
||||
from profit_analysis.constants import DATA_PATH
|
||||
|
||||
TRAILING_ZEROS = "000000000000000000000000"
|
||||
|
||||
|
||||
def get_address_to_coingecko_ids_mapping():
|
||||
token_cg_ids = pd.read_csv(DATA_PATH + "address_to_coingecko_ids.csv")
|
||||
token_cg_ids[TOKEN_DEBT_KEY] = token_cg_ids[TOKEN_KEY].astype(str)
|
||||
token_cg_ids[CG_ID_RECEIVED_KEY] = token_cg_ids[CG_ID_KEY]
|
||||
token_cg_ids[CG_ID_DEBT_KEY] = token_cg_ids[CG_ID_KEY]
|
||||
token_cg_ids[TOKEN_RECEIVED_KEY] = token_cg_ids[TOKEN_KEY].astype(str)
|
||||
return token_cg_ids
|
||||
|
||||
|
||||
def add_cg_ids(profit_by_block):
|
||||
token_cg_ids = get_address_to_coingecko_ids_mapping()
|
||||
token_cg_ids[TOKEN_DEBT_KEY] = token_cg_ids[TOKEN_DEBT_KEY].str.lower()
|
||||
token_cg_ids[TOKEN_RECEIVED_KEY] = token_cg_ids[TOKEN_RECEIVED_KEY].str.lower()
|
||||
profit_by_block[TOKEN_RECEIVED_KEY] = (
|
||||
profit_by_block[TOKEN_RECEIVED_KEY]
|
||||
.map(lambda x: x.replace(TRAILING_ZEROS, ""))
|
||||
.str.lower()
|
||||
)
|
||||
profit_by_block[TOKEN_DEBT_KEY] = (
|
||||
profit_by_block[TOKEN_DEBT_KEY]
|
||||
.map(lambda x: x.replace(TRAILING_ZEROS, ""))
|
||||
.str.lower()
|
||||
)
|
||||
profit_by_block = profit_by_block.merge(
|
||||
token_cg_ids[[TOKEN_DEBT_KEY, CG_ID_DEBT_KEY]], on=TOKEN_DEBT_KEY, how="left"
|
||||
)
|
||||
profit_by_block = profit_by_block.merge(
|
||||
token_cg_ids[[TOKEN_RECEIVED_KEY, CG_ID_RECEIVED_KEY]], how="left"
|
||||
)
|
||||
return profit_by_block[
|
||||
[
|
||||
"block_number",
|
||||
"timestamp",
|
||||
"transaction_hash",
|
||||
"token_debt",
|
||||
"amount_debt",
|
||||
"cg_id_debt",
|
||||
"token_received",
|
||||
"amount_received",
|
||||
"cg_id_received",
|
||||
]
|
||||
]
|
||||
|
||||
|
||||
def get_coingecko_historical_prices(start, end, token):
|
||||
cg = pg.CoinGeckoAPI()
|
||||
token_prices = cg.get_coin_market_chart_range_by_id(
|
||||
id=token, vs_currency="usd", from_timestamp=start, to_timestamp=end
|
||||
)["prices"]
|
||||
token_prices = pd.DataFrame(token_prices, columns=[TIMESTAMP_KEY, PRICE_KEY])
|
||||
token_prices[TIMESTAMP_KEY] = pd.to_datetime(
|
||||
pd.to_numeric(token_prices[TIMESTAMP_KEY]), unit="ms"
|
||||
)
|
||||
return token_prices[[TIMESTAMP_KEY, PRICE_KEY]]
|
||||
14
profit_analysis/column_names.py
Normal file
14
profit_analysis/column_names.py
Normal file
@ -0,0 +1,14 @@
|
||||
TOKEN_KEY = "token"
|
||||
TIMESTAMP_KEY = "timestamp"
|
||||
BLOCK_KEY = "block_number"
|
||||
TOKEN_RECEIVED_KEY = "token_received"
|
||||
TOKEN_DEBT_KEY = "token_debt"
|
||||
CG_ID_KEY = "cg_id"
|
||||
CG_ID_DEBT_KEY = "cg_id_debt"
|
||||
CG_ID_RECEIVED_KEY = "cg_id_received"
|
||||
AMOUNT_RECEIVED_KEY = "amount_received"
|
||||
AMOUNT_DEBT_KEY = "amount_debt"
|
||||
PRICE_DEBT_KEY = "price_debt"
|
||||
PRICE_RECEIVED_KEY = "price_received"
|
||||
PRICE_KEY = "price"
|
||||
DECIMAL_DEBT_KEY = "decimal_debt"
|
||||
1
profit_analysis/constants.py
Normal file
1
profit_analysis/constants.py
Normal file
@ -0,0 +1 @@
|
||||
DATA_PATH = "resources/"
|
||||
15
profit_analysis/token_utils.py
Normal file
15
profit_analysis/token_utils.py
Normal file
@ -0,0 +1,15 @@
|
||||
import pandas as pd
|
||||
from profit_analysis.column_names import TOKEN_KEY
|
||||
from profit_analysis.constants import DATA_PATH
|
||||
|
||||
|
||||
def get_decimals(token_address):
|
||||
decimals_mapping = pd.read_csv(DATA_PATH + "address_to_decimals.csv")
|
||||
decimals_mapping[TOKEN_KEY] = decimals_mapping[TOKEN_KEY].str.lower()
|
||||
decimals = decimals_mapping.loc[
|
||||
decimals_mapping[TOKEN_KEY] == token_address.lower(), "decimals"
|
||||
].values
|
||||
if len(decimals) > 0:
|
||||
return decimals[0]
|
||||
else:
|
||||
raise Exception("No Decimals for token=", token_address)
|
||||
@ -16,6 +16,7 @@ dramatiq = {extras = ["redis"], version = "^1.12.1"}
|
||||
pycoingecko = "^2.2.0"
|
||||
boto3 = "^1.20.48"
|
||||
aiohttp-retry = "^2.4.6"
|
||||
pandas = "^1.5.2"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
pre-commit = "^2.13.0"
|
||||
@ -46,6 +47,7 @@ fetch-range = 'cli:fetch_range'
|
||||
s3-export = 'cli:s3_export'
|
||||
enqueue-s3-export = 'cli:enqueue_s3_export'
|
||||
enqueue-many-s3-exports = 'cli:enqueue_many_s3_exports'
|
||||
analyze-profit = 'cli:analyze_profit_command'
|
||||
|
||||
[tool.black]
|
||||
exclude = '''
|
||||
|
||||
23
resources/address_to_coingecko_ids.csv
Normal file
23
resources/address_to_coingecko_ids.csv
Normal file
@ -0,0 +1,23 @@
|
||||
token,cg_id
|
||||
0x7ceB23fD6bC0adD59E62ac25578270cFf1b9f619,weth
|
||||
0xeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee,ethereum
|
||||
0x2260fac5e5542a773aa44fbcfedf7c193bc2c599,wrapped-bitcoin
|
||||
0x514910771af9ca656af840dff83e8264ecf986ca,chainlink
|
||||
0x0bc529c00c6401aef6d220be8c6ea1667f6ad93e,yearn-finance
|
||||
0xD6DF932A45C0f255f85145f286eA0b292B21C90B,aave
|
||||
0x1f9840a85d5af5bf1d1762f925bdaddc4201f984,uniswap
|
||||
0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174,usd-coin
|
||||
0x6b175474e89094c44da98b954eedeac495271d0f,dai
|
||||
0x408e41876cccdc0f92210600ef50372656052a38,republic-protocol
|
||||
0x39aa39c021dfbae8fac545936693ac917d5e7563,compound-usd-coin
|
||||
0x5d3a536e4d6dbd6114cc1ead35777bab948e3643,cdai
|
||||
0x4ddc2d193948926d02f9b1fe9e1daa0718270ed5,compound-ether
|
||||
0xc11b1268c1a384e55c48c2391d8d480264a3a7f4,compound-wrapped-btc
|
||||
0x0d500B1d8E8eF31E21C99d1Db9A6444d3ADf1270,matic-network
|
||||
0x430EF9263E76DAE63c84292C3409D61c598E9682,vulcan-forged
|
||||
0xc2132D05D31c914a87C6611C10748AEb04B58e8F,tether
|
||||
0x22a31bD4cB694433B6de19e0aCC2899E553e9481,mmfinance
|
||||
0xE6469Ba6D2fD6130788E0eA9C0a0515900563b59,terrausd-wormhole
|
||||
0x6f8a06447Ff6FcF75d803135a7de15CE88C1d4ec,shiba-inu
|
||||
0x831753DD7087CaC61aB5644b308642cc1c33Dc13,quick
|
||||
0x723b17718289a91af252d616de2c77944962d122,gaia-everworld
|
||||
|
18
resources/address_to_decimals.csv
Normal file
18
resources/address_to_decimals.csv
Normal file
@ -0,0 +1,18 @@
|
||||
token,decimals
|
||||
0x7ceB23fD6bC0adD59E62ac25578270cFf1b9f619,18
|
||||
0xeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee,18
|
||||
0x2260fac5e5542a773aa44fbcfedf7c193bc2c599,18
|
||||
0x514910771af9ca656af840dff83e8264ecf986ca,18
|
||||
0x0bc529c00c6401aef6d220be8c6ea1667f6ad93e,18
|
||||
0xD6DF932A45C0f255f85145f286eA0b292B21C90B,18
|
||||
0x1f9840a85d5af5bf1d1762f925bdaddc4201f984,18
|
||||
0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174,6
|
||||
0x39aa39c021dfbae8fac545936693ac917d5e7563,8
|
||||
0x0d500B1d8E8eF31E21C99d1Db9A6444d3ADf1270,18
|
||||
0x430EF9263E76DAE63c84292C3409D61c598E9682,18
|
||||
0xc2132D05D31c914a87C6611C10748AEb04B58e8F,6
|
||||
0x22a31bD4cB694433B6de19e0aCC2899E553e9481,18
|
||||
0xE6469Ba6D2fD6130788E0eA9C0a0515900563b59,6
|
||||
0x6f8a06447Ff6FcF75d803135a7de15CE88C1d4ec,18
|
||||
0x831753DD7087CaC61aB5644b308642cc1c33Dc13,18
|
||||
0x723b17718289a91af252d616de2c77944962d122,18
|
||||
|
27
scripts/launch_analysis.sh
Normal file
27
scripts/launch_analysis.sh
Normal file
@ -0,0 +1,27 @@
|
||||
#!/bin/bash
|
||||
# This is a script to analyze MEV profits
|
||||
# Input the pool Id of mev-inspect (can be found on your TILT interface)
|
||||
# TODO: How to extract the mev-inspect pool id to copy the csv files?
|
||||
mevInspectPoolId="mev-inspect-759f8dc6f7-2nnzl"
|
||||
# Input the starting and ending blocks you want to run the profit analysis for
|
||||
blockFrom=$((34500000))
|
||||
blockTo=$((34800000))
|
||||
window=$((100))
|
||||
reps=$(((${blockTo}-${blockFrom})/${window}))
|
||||
echo "${reps}"
|
||||
for i in $(seq 0 1 $reps)
|
||||
do
|
||||
from=$(($blockFrom + $i*$window))
|
||||
to=$(($blockFrom + ($i+1)*$window))
|
||||
echo "--"
|
||||
echo "rep= $i/$reps"
|
||||
echo "from= $from"
|
||||
echo "to= $to"
|
||||
./mev inspect-many $from $to
|
||||
done
|
||||
./mev analyze-profit $blockFrom $blockTo True
|
||||
declare -a file_names=("profit_by_date.csv" "profit_by_block_number.csv" "profit_by_category.csv")
|
||||
for fname in "${file_names[@]}"
|
||||
do
|
||||
kubectl cp $mevInspectPoolId:resources/$fname $fname;
|
||||
done
|
||||
Loading…
x
Reference in New Issue
Block a user