Calculating DEX Liquidity Pool Fees and Volumes

Decentralized exchanges are playing an increasingly important role in supporting cryptoasset trading, particularly when it comes to tokens using the ERC-20 standard. Coin Metrics has been actively working on collecting data from major DeFi protocols. For our first release, we have added support for all major liquidity pools on Uniswap v2, Uniswap v3, and Sushiswap v1.

Resources

This notebook demonstrates basic functionality offered by the Coin Metrics Python API Client and DEX Market Data.

Coin Metrics offers a vast assortment of data for hundreds of cryptoassets. The Python API Client allows for easy access to this data using Python without needing to create your own wrappers using requests and other such libraries.

To understand the data that Coin Metrics offers, feel free to peruse the resources below.

• The Coin Metrics API v4 website contains the full set of endpoints and data offered by Coin Metrics.
• The Coin Metrics Product Documentation gives detailed, conceptual explanations of the data that Coin Metrics offers.
• The API Spec contains a full list of functions.

File Download

Download the entire notebook as either a jupyter notebook to run yourself or as a pdf from the two links below

725KB

DEFI - Dex Data (1).ipynb

1MB

DEFI_dex_data (2).pdf

pdf

Setup

from os import environ
import sys
import pandas as pd
import numpy as np
import seaborn as sns
import logging
from datetime import date, datetime, timedelta
from coinmetrics.api_client import CoinMetricsClient
import json
import logging
from pytz import timezone as timezone_conv
from datetime import timezone as timezone_info
import matplotlib.dates as mdates
from IPython.display import Markdown as md
import matplotlib.pyplot as plt
import plotly.express as px 
%matplotlib inline

sns.set_theme()
sns.set_style('whitegrid')
sns.set(rc={'figure.figsize':(16,8)})
sns.set_context("notebook", font_scale=1.2, rc={"font.family": "Lato"});

logging.basicConfig(
    format='%(asctime)s %(levelname)-8s %(message)s',
    level=logging.INFO,
    datefmt='%Y-%m-%d %H:%M:%S'
)

# We recommend privately storing your API key in your local environment.
try:
    api_key = environ["CM_API_KEY"]
    logging.info("Using API key found in environment")
except KeyError:
    api_key = ""
    logging.info("API key not found. Using community client")
    
client = CoinMetricsClient(api_key)

2024-10-09 11:26:54 INFO     Using API key found in environment

DEX Market Catalog

The catalog/markets endpoint returns a list of available markets along with time ranges of available data. Users can pass in a list of markets, exchanges, or market types (spot, futures, options).

We can retrieve our DEX markets by fetching a list of all 'spot' markets, then filtering for the markets where the 'experimental' parameter equals true.

spot_markets = pd.concat([client.reference_data_markets(
    type = 'spot',
    page_size = 10000,
    exchange = "uniswap_v3_eth",
).to_dataframe(), client.reference_data_markets(
    type = 'spot',
    page_size = 10000,
    exchange = "uniswap_v2_eth",
).to_dataframe(), client.reference_data_markets(
    type = 'spot',
    page_size = 10000,
    exchange = "sushiswap_v1_eth",
).to_dataframe()])

exp_markets = spot_markets.loc[spot_markets['experimental']==True] 

exp_markets

	market	exchange	base	quote	pair	symbol	type	size_asset	margin_asset	strike	...	order_price_increment	order_price_min	order_price_max	order_size_min	order_taker_fee	order_maker_fee	margin_trading_enabled	experimental	base_native	quote_native
0	uniswap_v3_eth-1-1inch-dai-spot	uniswap_v3_eth	1inch	dai	1inch-dai	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
1	uniswap_v3_eth-1-1inch-usdc-spot	uniswap_v3_eth	1inch	usdc	1inch-usdc	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
2	uniswap_v3_eth-1-1inch-weth-spot	uniswap_v3_eth	1inch	weth	1inch-weth	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
3	uniswap_v3_eth-1-ageur_eth-eurcv_eth-spot	uniswap_v3_eth	ageur_eth	eurcv_eth	ageur_eth-eurcv_eth	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
4	uniswap_v3_eth-1-ageur_eth-usdc-spot	uniswap_v3_eth	ageur_eth	usdc	ageur_eth-usdc	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
220	sushiswap_v1_eth-yfi-sushi-spot	sushiswap_v1_eth	yfi	sushi	yfi-sushi	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
221	sushiswap_v1_eth-yfi-usdc-spot	sushiswap_v1_eth	yfi	usdc	yfi-usdc	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
222	sushiswap_v1_eth-yfi-usdt_eth-spot	sushiswap_v1_eth	yfi	usdt_eth	yfi-usdt_eth	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
223	sushiswap_v1_eth-yfi-wbtc-spot	sushiswap_v1_eth	yfi	wbtc	yfi-wbtc	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>
224	sushiswap_v1_eth-yfi-weth-spot	sushiswap_v1_eth	yfi	weth	yfi-weth	<NA>	spot	<NA>	<NA>	<NA>	...	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	True	<NA>	<NA>

2544 rows × 39 columns

# Calculate number of markets (pools) per DEX
mkt_counts = pd.DataFrame(exp_markets['exchange'].value_counts()).reset_index()

print (mkt_counts)

           exchange  count
0    uniswap_v3_eth   1643
1    uniswap_v2_eth    676
2  sushiswap_v1_eth    225

# Plot number of markets (pools) per DEX
ax1 = plt.subplot()
# mkt_counts['exchange'].plot(kind='bar', width=0.8, color=sns.color_palette('tab10'))
ax1.bar(x = mkt_counts['exchange'], height = mkt_counts['count'], color=sns.color_palette('tab10'))
plt.setp(ax1.get_xticklabels(), rotation=0)
ax1.set_facecolor("white")
plt.grid(color='black', linestyle='--', linewidth=0.2)
plt.title('\nCount of Markets \nby Decentralized Exchange\n', fontdict={'fontsize': 24, 'font': 'arial'})
# for i, v in enumerate(mkt_counts['exchange']):
ax1.set_xticks(range(len(mkt_counts['exchange'])))
ax1.set_xticklabels([label.get_text().upper() for label in ax1.get_xticklabels()], rotation=0, ha='center', va='top', fontsize=17)
plt.xticks(fontweight='bold')
plt.show()

# Show fields
pd.DataFrame(exp_markets.loc[exp_markets['exchange'] == 'uniswap_v3_eth'].iloc[0]).dropna()

	0
market	uniswap_v3_eth-1-1inch-dai-spot
exchange	uniswap_v3_eth
base	1inch
quote	dai
pair	1inch-dai
type	spot
pool_config_id	1
contract_address	063332bbf9f8385e4106919b5c6ae2e6a4f72228
fee	0.01
price_includes_fee	False
variable_fee	False
base_address	111111111117dc0aa78b770fa6a738034120c302
quote_address	6b175474e89094c44da98b954eedeac495271d0f
experimental	True

DEX markets include metadata for 3 different smart contracts:

• contract_address: The address of the liquidity pool contract. Each liquidity pool is a unique instance of a smart contract, deployed at a dedicated address. The pool contract holds both the base and the quote asset.

• base_address: The address of the ERC-20 token contract associated with the base asset.

• quote_address: The address of the ERC-20 token contract associated with the quote asset.

# DEX fields
exp_markets[['pool_config_id','contract_address','base_address','quote_address','fee']]

	pool_config_id	contract_address	base_address	quote_address	fee
0	1	063332bbf9f8385e4106919b5c6ae2e6a4f72228	111111111117dc0aa78b770fa6a738034120c302	6b175474e89094c44da98b954eedeac495271d0f	0.01
1	1	2ee7e6e459fffbbc655f09f2e1b3131abf98c397	111111111117dc0aa78b770fa6a738034120c302	a0b86991c6218b36c1d19d4a2e9eb0ce3606eb48	0.01
2	1	1d1284e43da1de5ee8dd6acbb03f3624cfbd872c	111111111117dc0aa78b770fa6a738034120c302	c02aaa39b223fe8d0a0e5c4f27ead9083c756cc2	0.01
3	1	f339217aa24e70eddf900f3b1a78eb9efcdea115	1a7e4e63778b4f12a199c062f3efdd288afcbce8	5f7827fdeb7c20b443265fc2f40845b715385ff2	0.01
4	1	735a26a57a0a0069dfabd41595a970faf5e1ee8b	1a7e4e63778b4f12a199c062f3efdd288afcbce8	a0b86991c6218b36c1d19d4a2e9eb0ce3606eb48	0.01
...	...	...	...	...	...
220	<NA>	f173a7a055340c91dbdf3083ce3babaa7535a03c	0bc529c00c6401aef6d220be8c6ea1667f6ad93e	6b3595068778dd592e39a122f4f5a5cf09c90fe2	0.3
221	<NA>	3a5747cf4e21861e2d0d3d51a0e8737ab4dfadc8	0bc529c00c6401aef6d220be8c6ea1667f6ad93e	a0b86991c6218b36c1d19d4a2e9eb0ce3606eb48	0.3
222	<NA>	f5fbc6ca5c677f1c977ed3a064b9dda14c5e241b	0bc529c00c6401aef6d220be8c6ea1667f6ad93e	dac17f958d2ee523a2206206994597c13d831ec7	0.3
223	<NA>	1d108372a83fbc3a0bfb7ca4d0e427449e7a5ca2	0bc529c00c6401aef6d220be8c6ea1667f6ad93e	2260fac5e5542a773aa44fbcfedf7c193bc2c599	0.3
224	<NA>	088ee5007c98a9677165d78dd2109ae4a3d04d0c	0bc529c00c6401aef6d220be8c6ea1667f6ad93e	c02aaa39b223fe8d0a0e5c4f27ead9083c756cc2	0.3

2544 rows × 5 columns

Each liquidity pool is also associated with a corresponding fee percentage. With each trade, fees are distributed pro-rata to the pool's liquidity providers.

# Range of pool fees
pool_fees = pd.DataFrame(exp_markets.fee.unique().dropna())
pool_fees

	0
0	0.01
1	0.05
2	0.3
3	1.0

Due to the permissionless nature of provisioning a liquidity pool, users can easily add arbitrary ERC-20 tokens to the decentralized exchange. There are over 50,000 trading pairs available on Uniswap today. To prioritize only the most relevant and liquid markets, we cover the subset of markets where both tokens are part of Coin Metrics reference rate coverage.

# Assets covered
asset_coverage = np.unique(exp_markets[['base', 'quote']].values)
print(asset_coverage)
print('\nTotal number of assets: \033[1m' + str(len(asset_coverage)) + '\033[0m\n')

['1inch' 'aave' 'ageur_eth' 'alcx' 'alpha' 'alusd' 'ampl_eth' 'ant' 'ape'
 'api3' 'audio' 'ausd_eth' 'axs_1_eth' 'axs_2_eth' 'badger' 'bal'
 'band_eth' 'bat' 'bit' 'bnb_eth' 'bnt' 'boost_eth' 'btm_eth' 'busd'
 'cbat' 'cbeth' 'ccomp' 'cdai' 'cel' 'cennz' 'ceth' 'chz_eth' 'comp' 'cro'
 'crv' 'crvusd_eth' 'cuni' 'cusdc' 'cusdcv3' 'cusdt' 'cvc' 'cvx' 'cwbtc'
 'czrx' 'dai' 'dar' 'degen_eth' 'deusd_eth' 'dgx' 'dorkl_eth' 'dpi' 'drgn'
 'eeth_eth' 'elf' 'eng' 'enj' 'ens' 'esd' 'ethos' 'ethx_eth' 'eul'
 'eurc_eth' 'eurcv_eth' 'eure_eth' 'eurs_eth' 'eurt_eth' 'fdusd_eth'
 'fei_eth' 'flx' 'fox_eth' 'frax_eth' 'frxeth_eth' 'ftm_eth' 'ftt' 'fun'
 'fwb' 'fxc_eth' 'fxs' 'gala' 'gbpt_eth' 'gho_eth' 'glm' 'gno' 'grt'
 'gt_eth' 'gusd' 'gyen_eth' 'hbot' 'hbtc' 'hedg' 'hex_eth' 'hpos10i_eth'
 'hpos1m_eth' 'ht' 'husd' 'idrt_eth' 'imx' 'inst' 'kin1' 'knc' 'ldo'
 'lend' 'leo_eth' 'link' 'linq_eth' 'looks' 'loom' 'lpt' 'ltx_eth'
 'lusd_eth' 'mana' 'matic_eth' 'mco' 'meth_eth' 'mim_eth' 'mkr_2_eth'
 'mnt' 'mpl' 'mtl_metal' 'myc' 'myth' 'nexo' 'nftx' 'nmr' 'ogn'
 'ohm_2_eth' 'okb' 'omg' 'ousd_eth' 'paid' 'parrot_eth' 'pax' 'paxg' 'pay'
 'pdt' 'pepe_eth' 'perp' 'pndc_eth' 'pog_eth' 'pol_eth' 'poly' 'pow_eth'
 'powr' 'ppt' 'pufeth_eth' 'pvpbot_eth' 'pxeth_eth' 'pyusd_eth' 'qash'
 'qnt' 'rad' 'radar' 'rai_eth' 'ren' 'renbtc' 'renfil_eth' 'rep_3_eth'
 'reth_eth' 'rev_eth' 'rez_eth' 'rlb_eth' 'rook' 'rseth_eth' 'rsr'
 'rsweth_eth' 'safe_eth' 'sai' 'salt' 'sand' 'sbtc_eth' 'sdai_eth'
 'seth_synthseth_eth' 'shepe_eth' 'shia_eth' 'shib' 'skl' 'slp_1_eth'
 'slp_2_eth' 'snt' 'snx_3_eth' 'socks' 'spell' 'srm' 'srn' 'steth_lido'
 'stg_eth' 'stkaave' 'stmx' 'stone_eth' 'storj' 'susd_eth' 'susde_eth'
 'sushi' 'sweth_eth' 'swise' 'swrv' 't_eth' 'taud_eth' 'tbtc_eth'
 'tcad_eth' 'tgbp_eth' 'thkd_eth' 'toke' 'trx_eth' 'tusd_2_eth' 'ubt'
 'uma' 'uni' 'univ2aaveweth_eth' 'univ2crvweth_eth' 'univ2daiweth_eth'
 'univ2snxweth_eth' 'univ2uniweth_eth' 'univ2wbtcweth_eth'
 'univ2yfiweth_eth' 'uqc_1_eth' 'uqc_2_eth' 'usd0_eth' 'usda_eth' 'usdc'
 'usdd_eth' 'usde_eth' 'usdk' 'usdn_eth' 'usdt_eth' 'usdv_eth' 'usdy_eth'
 'ustc.t_eth_wh' 'veri' 'wbtc' 'wcelo' 'wcusd' 'weeth_eth' 'weth' 'wluna'
 'wnxm' 'wsteth' 'wust' 'wzec' 'xai_silofinance_eth' 'xaut_1_eth'
 'xaut_2_eth' 'xchf' 'xidr_eth' 'xsgd_eth' 'xsushi' 'yama_eth' 'yfi' 'zrx']

Total number of assets: 249

The majority of DEX assets trade against Wrapped Ether (WETH). Note that Ethereum's native asset ETH is not supported in Uniswap V2/V3, as the asset was created prior to the ERC-20 standard. From the Uniswap documentation:

"Unlike Uniswap V1 pools, V2 pairs do not support ETH directly, so ETH⇄ERC-20 pairs must be emulated with WETH. The motivation behind this choice was to remove ETH-specific code in the core, resulting in a leaner codebase. End users can be kept fully ignorant of this implementation detail, however, by simply wrapping/unwrapping ETH in the periphery." docs.uniswap.org

# Enter an asset ticker to see available 'base' and 'quote' markets
asset = 'weth'

selected_markets = exp_markets.loc[(exp_markets['base']==asset) | (exp_markets['quote']==asset)]
print('\nTotal number of ' + '\033[1m' + asset + '\033[0m' + ' markets: \n\033[1m' 
      + str(len(selected_markets)) + '\n')

Total number of weth markets: 
847

Using the min_time parameter, we can filter for the newest DEX liquidity pool deployed in our coverage

defi_market_catalogs = pd.concat([client.catalog_market_trades_v2(
    market_type = 'spot',
    page_size = 10000,
    exchange = "uniswap_v3_eth",
).to_dataframe(), client.catalog_market_trades_v2(
    market_type = 'spot',
    page_size = 10000,
    exchange = "uniswap_v2_eth",
).to_dataframe(), client.catalog_market_trades_v2(
    market_type = 'spot',
    page_size = 10000,
    exchange = "sushiswap_v1_eth",
).to_dataframe()]).sort_values('min_time').reset_index()

print (defi_market_catalogs)

      index                                      market  \
0       560               uniswap_v2_eth-usdc-weth-spot   
1       154                uniswap_v2_eth-dai-weth-spot   
2       152                uniswap_v2_eth-dai-usdc-spot   
3       387                uniswap_v2_eth-ren-usdc-spot   
4        85               uniswap_v2_eth-cdai-weth-spot   
...     ...                                         ...   
2012    207         uniswap_v3_eth-2-paxg-usdt_eth-spot   
2013    208       uniswap_v3_eth-2-paxg-xaut_2_eth-spot   
2014    302  uniswap_v3_eth-2-weeth_eth-pufeth_eth-spot   
2015     24    uniswap_v3_eth-1-deusd_eth-usdt_eth-spot   
2016    656   uniswap_v3_eth-3-usdt_eth-crvusd_eth-spot   

                      min_time                  max_time  
0    2020-05-05 21:09:32+00:00 2024-10-03 19:44:11+00:00  
1    2020-05-14 00:01:38+00:00 2024-10-03 19:22:47+00:00  
2    2020-05-15 02:18:16+00:00 2024-10-03 12:06:35+00:00  
3    2020-05-17 21:32:57+00:00 2024-09-03 22:31:59+00:00  
4    2020-05-18 17:18:03+00:00 2024-10-01 22:43:11+00:00  
...                        ...                       ...  
2012 2024-09-16 01:14:11+00:00 2024-09-17 01:00:23+00:00  
2013 2024-09-17 01:56:23+00:00 2024-09-28 12:37:23+00:00  
2014 2024-09-26 04:21:35+00:00 2024-10-03 09:49:59+00:00  
2015 2024-09-27 23:06:35+00:00 2024-10-03 10:26:47+00:00  
2016 2024-09-28 07:12:59+00:00 2024-10-03 18:50:35+00:00  

[2017 rows x 4 columns]

# Check for the newest market
newest = defi_market_catalogs.loc[defi_market_catalogs['min_time'].idxmax()].dropna()
pd.DataFrame(newest)

	2016
index	656
market	uniswap_v3_eth-3-usdt_eth-crvusd_eth-spot
min_time	2024-09-28 07:12:59+00:00
max_time	2024-10-03 18:50:35+00:00

DEX Swaps Data

Swaps data is served through our existing /timeseries/market-trades endpoint because swaps are conceptually identical to a trade. Users can see all the standard trade fields for a swap such as time, price, and volume but can also see defi-specific fields such as the block height, block hash, transaction id, addresses involved in the swap, and more.

defi_market = 'uniswap_v3_eth-2-weth-usdt_eth-spot'
start = datetime.now() - timedelta(days=3)
end = datetime.now() - timedelta(hours=1)

defi_trades = client.get_market_trades(
    markets=defi_market,
    start_time=start,
    end_time = end
).to_dataframe()

defi_trades['amount'] = defi_trades['amount'].astype(float)
defi_trades.head()

	market	time	coin_metrics_id	amount	price	database_time	side	block_hash	block_height	txid	initiator	sender	beneficiary
0	uniswap_v3_eth-2-weth-usdt_eth-spot	2024-09-30 15:53:23+00:00	04V5RQT2E04FT3C4GH7U1MGVR9VR7AUFALO31HO6QSOKR9...	0.128299	2607.212871	2024-09-30 15:53:34.441041+00:00	sell	a27008fe8d84844fe0da1fda7fb3abcf557030c706d731...	20864491	ae1fd1a682a4acfaddd474f06d9cbc7fe903435b465b65...	8249187b3b1f22da84b1c82eb876a2004d60e5a7	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad
1	uniswap_v3_eth-2-weth-usdt_eth-spot	2024-09-30 15:55:11+00:00	04V5RT664167K4H7OBE0IQ00JBU0GG2K0O9O102M1TS37N...	8.010022	2605.89657	2024-09-30 15:55:23.154367+00:00	sell	c6204c7a1227c2dc0968009afc08405406138080560f78...	20864500	a585c10e6fa329213cfc758189b3dee4fbdd11f84b0090...	a172577031eafd8b03dce022533863fe988159cd	51c72848c68a965f66fa7a88855f9f7784502a7f	51c72848c68a965f66fa7a88855f9f7784502a7f
2	uniswap_v3_eth-2-weth-usdt_eth-spot	2024-09-30 15:55:35+00:00	04V5RTJ008QUN6D495DB7M93HLAHH6RUCO7GALPGLR6JRU...	3.275656	2605.139188	2024-09-30 15:55:48.193560+00:00	buy	600235eb99a4495ab3d9238d55189b7e660f055730aecd...	20864502	983dd154bcd17d715def39a8a46e36d5b8f765f73bde82...	8ae57a027c63fca8070d1bf38622321de8004c67	ef1c6e67703c7bd7107eed8303fbe6ec2554bf6b	ef1c6e67703c7bd7107eed8303fbe6ec2554bf6b
3	uniswap_v3_eth-2-weth-usdt_eth-spot	2024-09-30 15:55:59+00:00	04V5RU5PJI877ESIO9ET0AAEOBK5UBINH6ER8NCIB3U2KG...	6.002656	2604.703261	2024-09-30 15:56:09.664424+00:00	sell	b99c9073bb92c25dd0294ec2e85f2e57899db45d9258fc...	20864504	cb9eda573eef860fe7019837c23a66b881e5e4b28549e7...	d1fa51f2db23a9fa9d7bb8437b89fb2e70c60cb7	d4bc53434c5e12cb41381a556c3c47e1a86e80e3	d4bc53434c5e12cb41381a556c3c47e1a86e80e3
4	uniswap_v3_eth-2-weth-usdt_eth-spot	2024-09-30 15:56:11+00:00	04V5RUDJMTR74RDCP4JUIDIL6UN9UTSE7MEBP0BR3USP60...	0.399800	2603.679987	2024-09-30 15:56:23.744604+00:00	sell	b3b776726dacc927e9365537ae9f778e3d9cbc817b1fb9...	20864505	0083045534c1203964355113751c48cb79f262f70edcf7...	81fe73a6fb28c49c14c82fcae2a4fe19f57d150c	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad

color_map = {'buy': 'green', 'sell': 'red'}
defi_price = plt.scatter(x=defi_trades['time'], y=defi_trades['price'], s=defi_trades['amount'], c=defi_trades['side'].map(color_map))

plt.xlabel("", fontsize=15)
plt.ylabel("Price (USDT)\n", font='arial',fontsize=15)

market_string = defi_market.split("uniswap_v3_eth-", 1)[-1].split("-spot")[0].upper()
plt.title('\nUniswap V3\n Pool ' + market_string + '\nTrades\n', font='arial', size=20)

legend_labels = ['BUY', 'SELL']
legend_handles = [plt.Line2D([0], [0], marker='o', color='w', markerfacecolor=color_map['buy'], markersize=12),
                  plt.Line2D([0], [0], marker='o', color='w', markerfacecolor=color_map['sell'], markersize=12)]
legend = plt.legend(legend_handles, legend_labels, loc='lower right', fontsize=16, framealpha=0, bbox_to_anchor=(0.99, 1.02))

plt.gca().set_facecolor('white')
plt.grid(color='black', linestyle='dotted')
plt.show()

pd.DataFrame(defi_trades.iloc[0])

	0
market	uniswap_v3_eth-2-weth-usdt_eth-spot
time	2024-09-30 15:53:23+00:00
coin_metrics_id	04V5RQT2E04FT3C4GH7U1MGVR9VR7AUFALO31HO6QSOKR9...
amount	0.128299
price	2607.212871
database_time	2024-09-30 15:53:34.441041+00:00
side	sell
block_hash	a27008fe8d84844fe0da1fda7fb3abcf557030c706d731...
block_height	20864491
txid	ae1fd1a682a4acfaddd474f06d9cbc7fe903435b465b65...
initiator	8249187b3b1f22da84b1c82eb876a2004d60e5a7
sender	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad
beneficiary	3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad

Unlike centralized exchanges, where there is an unknown buyer and a seller, each swap is associated with 3 different Ethereum addresses:

• Initiator is the ethereum address which submitted the transaction as a result of which the swap/liquidity action occurred

• Sender is the ethereum address that invoked the uniswap pool smart contract's function for swapping or adding/removing liquidity

• Beneficiary is the ethereum address that got credited with the output tokens (in case of a swap or liquidity removal) or with liquidity (in case of liquidity addition)

print('\nTotal number of ' + '\033[1m' + defi_market + '\033[0m' + ' trades (' + str(start.date()) + ' to ' + str(end.date()) + '): \n\033[1m' 
      + str(len(defi_trades)) + '\033[0m\n')

print('\nTotal number of ' + '\033[1m' + defi_market + '\033[0m' + ' buys (' + str(start.date()) + ' to ' + str(end.date())+ '): \n\033[1m' 
      + str(len(defi_trades.loc[(defi_trades['side']=='buy')])) + '\033[0m\n')

print('\nTotal number of ' + '\033[1m' + defi_market + '\033[0m' + ' unique buyers (' + str(start.date()) + ' to ' + str(end.date()) + '): \n\033[1m' 
      + str(len((defi_trades.loc[(defi_trades['side']=='buy')]).beneficiary.unique())) + '\n')

Total number of uniswap_v3_eth-2-weth-usdt_eth-spot trades (2024-10-06 to 2024-10-09): 
5874


Total number of uniswap_v3_eth-2-weth-usdt_eth-spot buys (2024-10-06 to 2024-10-09): 
3003


Total number of uniswap_v3_eth-2-weth-usdt_eth-spot unique buyers (2024-10-06 to 2024-10-09): 
351

defi_buyers = pd.DataFrame(defi_trades)
defi_buyers['time'] = pd.to_datetime(defi_buyers['time'])
defi_buyers.set_index('time', inplace=True)

hourly_unique_buyers = defi_buyers['beneficiary'].resample('h').nunique()
sns.set_style('whitegrid')
fig, ax = plt.subplots()
sns.lineplot(data=hourly_unique_buyers, ax=ax)
ax.set_xlabel('')
ax.set_ylabel('Unique Buyers per Hour')
ax.set_title('\nPool ' + str(market_string) + '\nUnique Buyers per Hour\n', font='arial', size=20)
plt.grid(color='black', linestyle='dotted')
plt.show()

# Unique buyer addresses
((defi_trades.loc[(defi_trades['side']=='buy')]).beneficiary.unique())

<StringArray>
['1111111254eeb25477b68fb85ed929f73a960582',
 '5ced44f03ff443bbe14d8ea23bc24425fb89e3ed',
 '2bbf5243e49e8f0025988754dac6620ab0d3e162',
 '308c6fbd6a14881af333649f17f2fde9cd75e2a6',
 'def1c0ded9bec7f1a1670819833240f027b25eff',
 '313d26bf14c4362883cc798d4aa50352fc55c954',
 '3fc91a3afd70395cd496c647d5a6cc9d4b2b7fad',
 '111111125421ca6dc452d289314280a0f8842a65',
 '2580916979353d3a40c71be00b0e197a98694cdf',
 'e37e799d5077682fa0a244d46e5649f71457bd09',
 ...
 '898fcb7b4e3bee37ebb0ca3a3fbd08cefdc8c995',
 '8ef79d6c328c25da633559c20c75f638a4863462',
 '309eac50cedc3909ce0f03c9725bb7a684b75829',
 '98c640aac6b88f5e1ab14073dd2d5baf71461e9c',
 '0f388ecdbc128083bfe317b00de2c25fbe9f24d5',
 '8583c58e3b0e02d2cdf45b06e437674f2fb47eb6',
 '6905fef2f9a7825f94018f4f989dc82f88be9181',
 '0b2b99d9fa762060fdbf1657984f7ece56ca5e5c',
 'f2b6525a3d7f28113cc57cb9b73dde9230073059',
 '051ef36e55875c08e4efaea6072c6d0f66fb0b9f']
Length: 351, dtype: string

# Calculate approximate USD volume (NOTE: quote asset must be a stablecoin)
defi_trades['DEX Volume (USD)'] = (defi_trades['amount'])*(defi_trades['price'])

# Use only the amount field if base asset is a stablecoin
#defi_trades['DeFi Volume (USD)'] = (defi_trades['amount'])

# Largest trade
largest = defi_trades.loc[defi_trades['amount'].idxmax()]
trade_size_usd = '${:,.2f}'.format(largest['DEX Volume (USD)'])
pd.DataFrame(largest)

	2628
market	uniswap_v3_eth-2-weth-usdt_eth-spot
time	2024-10-07 18:39:35+00:00
coin_metrics_id	04VIAJ3J2LDTBQKN8T3DB7MJM1EP7SID408V74DL4USTFL...
amount	1192.565431
price	2274.221925
database_time	2024-10-07 18:39:54.427105+00:00
side	buy
block_hash	73155bd5ea974746d59ed3b05d93f24d2011f391b527b9...
block_height	20915532
txid	cb93842f093812b85469b576914d02907345d2624e1eee...
initiator	b5eaac5a8649142dcdd13f981767913bcdf7ee42
sender	ddc25c965443834179438c2eb30e70f34b854a04
beneficiary	ddc25c965443834179438c2eb30e70f34b854a04
DEX Volume (USD)	2712158.449637
Datetime	2024-10-07 18:00:00

print('\nLARGEST TRADE: \n\n' + trade_size_usd + ' by address 0x' + largest['beneficiary'] + '\n')

LARGEST TRADE: 

$2,712,158.45 by address 0xddc25c965443834179438c2eb30e70f34b854a04

# ATLAS links for blockchain metadata
md('<br>**ATLAS** by Coin Metrics <br> **Blockchain Search Engine** <br><br>**BUYER ADDRESS:** https://atlas.coinmetrics.io/address-details?asset=weth&address=' + str(largest['beneficiary']) + '<br><br>**TRANSACTION INFO:** https://atlas.coinmetrics.io/transaction-details?asset=weth&tx_hash=' + str(largest['txid']) + '<br><br>**BlOCK INFO:** https://atlas.coinmetrics.io/block-details?asset=weth&block_hash=' + str(largest['block_hash']) + '<br><br>For more info on **ATLAS** visit: https://coinmetrics.io/atlas/')

ATLAS by Coin Metrics Blockchain Search Engine BUYER ADDRESS: https://atlas.coinmetrics.io/address-details?asset=weth&address=ddc25c965443834179438c2eb30e70f34b854a04 TRANSACTION INFO: https://atlas.coinmetrics.io/transaction-details?asset=weth&tx_hash=cb93842f093812b85469b576914d02907345d2624e1eee463999bade940a8851 BlOCK INFO: https://atlas.coinmetrics.io/block-details?asset=weth&block_hash=73155bd5ea974746d59ed3b05d93f24d2011f391b527b9d7d5c42e59752c6d41 For more info on ATLAS visit: https://coinmetrics.io/atlas/

defi_trades['Datetime'] = pd.to_datetime(defi_trades.time.dt.strftime('%m/%d/%y %H:00'))
defi_vol = defi_trades.groupby('Datetime')['DEX Volume (USD)'].sum()

pd.DataFrame(defi_vol)

	DEX Volume (USD)
Datetime
2024-10-06 11:00:00	217166.26046
2024-10-06 12:00:00	438390.416765
2024-10-06 13:00:00	533070.744054
2024-10-06 14:00:00	1163987.797628
2024-10-06 15:00:00	705547.880282
...	...
2024-10-09 06:00:00	625096.999423
2024-10-09 07:00:00	485056.495087
2024-10-09 08:00:00	553334.67282
2024-10-09 09:00:00	462252.636566
2024-10-09 10:00:00	102118.526838

72 rows × 1 columns

Retrieving volume for a centralized exchange via the market-candles endpoint

cex_market = 'coinbase-eth-usd-spot'

cex_vol = client.get_market_candles(
    markets=cex_market,
    frequency='1h',
    start_time=start,
    end_time=end- timedelta(hours=1)
).to_dataframe()

cex_vol = cex_vol.rename(columns={"candle_usd_volume": "CEX Volume (USD)"})
cex_vol['Datetime'] = pd.to_datetime(cex_vol.time.dt.strftime('%m/%d/%y %H:00'))
cex_vol = cex_vol.groupby('Datetime')['CEX Volume (USD)'].sum()

vol_comp = pd.merge(defi_vol, cex_vol,on="Datetime", how="left").dropna()
vol_comp["DEX Volume (USD)"] = vol_comp['DEX Volume (USD)'].astype(int)
vol_comp["CEX Volume (USD)"] = vol_comp['CEX Volume (USD)'].astype(int)

vol_comp

	DEX Volume (USD)	CEX Volume (USD)
Datetime
2024-10-06 12:00:00	438390	946175
2024-10-06 13:00:00	533070	1258087
2024-10-06 14:00:00	1163987	3316466
2024-10-06 15:00:00	705547	2654936
2024-10-06 16:00:00	551985	1881551
...	...	...
2024-10-09 05:00:00	550504	1912136
2024-10-09 06:00:00	625096	2814167
2024-10-09 07:00:00	485056	4493300
2024-10-09 08:00:00	553334	2393424
2024-10-09 09:00:00	462252	2559575

70 rows × 2 columns

sns.set_style('whitegrid')
vc = sns.lineplot(data=vol_comp)
vc.yaxis.set_major_formatter('${x:,.0f}')
vc.set_title(str('\n' + defi_market.upper() + '\n vs. \n' + cex_market.upper() + '\n Hourly Volume \n'),font='arial',fontsize=17.5)
vc.set_ylabel("Volume (USD) \n", font='arial',fontsize = 14)
plt.grid(color='black', linestyle='dotted')
legend = vc.legend(fontsize=15, framealpha=0, bbox_to_anchor=(1.0, 1.2))
vc.set_xlabel("");