Subgraphs: How to query Uniswap V2 subgraph
In this tutorial, we will explore how to query Uniswap V2, an already-deployed elastic subgraph on Chainstack. Elastic subgraphs are a powerful solution for indexing blockchain data. You can access major DeFi protocols such as Uniswap, Curve, and PancakeSwap through elastic subgraphs. No heavy deployment or programming needed.
Query DeFi subgraphs on Chainstack
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Introduction
Chainstack subgraphs simplify the extraction and processing of data from archive nodes, allowing for easy filtering and querying using GraphQL. Without subgraphs, Web3 developers and users would need to aggregate, process, and filter blockchain data themselves, which involves parsing vast amounts of raw transaction data.
We will discuss an elastic subgraph for Uniswap V2. For more information on setting up dedicated custom subgraphs, please refer to our detailed tutorial here.
Uniswap V2 subgraph
The Uniswap V2 subgraph is an already-deployed elastic subgraph that monitors and indexes data from Uniswap V2 smart contracts. You can explore the subgraph schema using the Explorer tool on the GraphiQL page of the subgraph, accessible via the GraphQL UI URL. Additionally, the GraphiQL page offers a convenient tool for testing different queries directly in the browser.
Automated liquidity protocol
💡 Uniswap V2 is an automated liquidity protocol powered by a constant product formula and implemented in a system of non-upgradeable smart contracts on the Ethereum blockchain.
Each Uniswap smart contract, or pair, manages a liquidity pool made up of reserves of two ERC-20 tokens.
Anyone can become a liquidity provider (LP) for a pool by depositing an equivalent value of each underlying token in return for pool tokens. These tokens track pro-rata LP shares of the total reserves, and can be redeemed for the underlying assets at any time.
According to the schema, we can interact with the following entities, among others:
- Liquidity positions;
- Pairs;
- Swaps;
- Tokens;
- Transactions.
Additionally, there are several historical data entities that might be useful:
- Liquidity positions snapshots;
- Hourly and daily pair data;
- Daily token data.
Each entity contains different sets of parameters, fields and nested entities.
Querying subgraph
There are multiple ways to query the subgraph. You can use GraphiQL, as mentioned earlier, or the command-line tool curl
, along with many other HTTP packages or GraphQL clients implemented in various programming languages. For the examples below, we will use the requests
package, a popular and user-friendly HTTP client library for Python.
We will write a Python function to query the subgraph. GraphQL queries are stored as separate files. You can find all the scripts and queries in the GitHub repository.
Lowercased addresses
Note that addresses used in the subgraph are lowercased. Using checksummed addresses or addresses with uppercase letters may result in empty or incorrect outputs.
Prerequisites
-
Log in to your Chainstack account and add an elastic Uniswap V2 subgraph in the Ethereum Mainnet.
-
Open your terminal (Command Prompt for Windows or Terminal for macOS/Linux) and run the following command to clone the GitHub repository to your current directory.
git clone https://github.com/chainstacklabs/uniswap-v2-subgraph-queries .
-
Set up your Python virtual environment.
python3 -m venv venv source venv/bin/activate
python -m venv venv venv\Scripts\activate
-
With the virtual environment activated, run the following command to install the required dependencies.
pip install -r requirements.txt
-
Create the environment variable file (.env) and paste your Chainstack endpoint URL there.
SUBGRAPH_URL=<uniswap_v2_subgraph_url>
Python main.py
Let’s first create a main function that will run all the queries in a loop. We'll start by loading the configuration file (.env
).
import os
import json
import time
import requests
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Constants
GRAPHQL_ENDPOINT = os.getenv("SUBGRAPH_URL")
QUERIES_DIR = 'Queries'
OUTPUTS_DIR = 'Outputs'
In our project, we store queries as separate .graphql
files in the Queries
folder. We will read each query file, execute it, and store its result in the Outputs
folder.
def main():
# Ensure the output directory exists
if not os.path.exists(OUTPUTS_DIR):
os.makedirs(OUTPUTS_DIR)
# List all GraphQL query files
query_files = [f for f in os.listdir(QUERIES_DIR) if f.endswith('.graphql')]
query_files.sort() # ascending order
# Process each query file
for query_file in query_files:
query_path = os.path.join(QUERIES_DIR, query_file)
output_path = os.path.join(OUTPUTS_DIR, query_file.replace('.graphql', '.json'))
try:
# Read query from a file
with open(query_path, 'r') as file:
query = file.read()
# Execute query
start_time = time.time()
query_result = requests.post(GRAPHQL_ENDPOINT, json={'query': query}, timeout=40)
elapsed_time = time.time() - start_time
# Save query result
with open(output_path, 'w') as file:
json.dump(query_result.json(), file, indent=4)
print(f"\nSaved results of {query_file} to {output_path}")
print(f'Elapsed time: {elapsed_time:.2f} seconds')
except Exception as e:
print(f"\nFailed to execute {query_file}: {e}")
if __name__ == "__main__":
main()
Meta queries
Get subgraph details. We can check the latest block synced to the subgraph by querying _meta
. Additionally, there is the deployment
field, which provides us with the unique identifier for the subgraph deployment. Append it to https://ipfsgw.com/ipfs/
to check the subgraph manifest content. hasIndexingErrors
indicates where there have been any indexing errors.
{
_meta {
block {
hash
number
parentHash
timestamp
}
deployment
hasIndexingErrors
}
}
Queries for traders
Swaps
Get latest swaps. Here, we query the swaps
entity with a few parameters: first
to limit the response size, orderBy
and orderDirection
to sort swaps by time in descending order.
{
swaps(first: 5, orderBy: timestamp, orderDirection: desc) {
id
transaction {
id
timestamp
}
pair {
token0 {
symbol
}
token1 {
symbol
}
}
amount0In
amount1In
amount0Out
amount1Out
amountUSD
}
}
Get latest swaps for pair of tokens. To obtain a pair address, you can call the getPair
function of the UniswapV2 Factory Contract (no gas is needed). You can also query the subgraph using specific conditions, such as traded pairs with USDC (this will be covered later in the tutorial). Use where
to filter the results.
{
swaps(
first: 5
orderBy: timestamp
orderDirection: desc
where: {
# WBTC/WETH pair
pair_: { id: "0xbb2b8038a1640196fbe3e38816f3e67cba72d940" }
}
) {
id
transaction {
id
timestamp
}
pair {
token0 {
symbol
}
token1 {
symbol
}
}
amount0In
amount1In
amount0Out
amount1Out
amountUSD
}
}
Get the latest swaps with threshold. In this case, we need to use the amountUSD
field. In the Explorer, we can see there is a special field for this called amountUSD_gte
. This field compares values to see if they are greater than or equal to a specified input.
{
swaps(
first: 5
orderBy: timestamp
orderDirection: desc
where: { amountUSD_gte: 100000 }
) {
id
transaction {
id
timestamp
}
pair {
token0 {
symbol
}
token1 {
symbol
}
}
amount0In
amount1In
amount0Out
amount1Out
amountUSD
}
}
Token prices
Get token price. To do this, we need to query the token
entity with the argument id
(token address). Since prices are in ETH, we should also include ethPrice
from the bundles
entity.
{
# WBTC token address
token(id: "0x2260fac5e5542a773aa44fbcfedf7c193bc2c599") {
id
symbol
name
derivedETH
}
bundles {
ethPrice
}
}
Get historical token prices. Here, we can use tokenDayDatas
, which stores historical data sets for all tokens. Prices are in USD.
{
tokenDayDatas(
first: 30
orderBy: date
orderDirection: desc
# WBTC token address
where: { token_: { id: "0x2260fac5e5542a773aa44fbcfedf7c193bc2c599" } }
) {
date
token {
symbol
}
priceUSD
}
}
Trading volume
Get hourly trading volume of pair. There is both daily and hourly data available. For our example, we will check the hourly data for the USDC/WETH pair (id
) since July 1, 2024 (hourStartUnix_gte
).
{
pairHourDatas(
# WBTC/WETH pair
where: {
pair_: { id: "0xbb2b8038a1640196fbe3e38816f3e67cba72d940" }
hourStartUnix_gte: 1719788422
}
orderBy: hourStartUnix
orderDirection: desc
) {
hourStartUnix
hourlyVolumeToken0
hourlyVolumeToken1
hourlyVolumeUSD
hourlyTxns
}
}
Get daily trading volume of a pair. The same approach for querying daily data. Here, we retreive data for the last 7 days.
{
pairDayDatas(
# WBTC/WETH pair
where: { pairAddress: "0xbb2b8038a1640196fbe3e38816f3e67cba72d940" }
orderBy: date
orderDirection: desc
first: 7
) {
date
dailyVolumeUSD
dailyTxns
dailyVolumeToken0
dailyVolumeToken1
}
}
Queries for liquidity providers
Pairs
Get largest pairs. The largest pairs have the largest reserves converted to USD. Sort by reserveUSD
in descending order.
{
pairs(orderBy: reserveUSD, orderDirection: desc, first: 10) {
id
createdAtTimestamp
createdAtBlockNumber
token0 {
symbol
id
}
token1 {
symbol
id
}
reserveUSD
reserveETH
}
}
Get recently created pools. The most recent pools have the highest block number. Sort by createdAtBlockNumber
in descending order.
{
pairs(orderBy: createdAtBlockNumber, orderDirection: desc, first: 10) {
id
createdAtTimestamp
createdAtBlockNumber
token0 {
symbol
id
}
token1 {
symbol
id
}
reserveUSD
reserveETH
}
}
Liquidity positions and DEX metrics
Get largest liquidity positions in pair. We can filter by the id
of the pair to get data for a specific pair. To find the largest positions, sort by liquidityTokenBalance
in descending order.
{
liquidityPositions(
orderBy: liquidityTokenBalance
orderDirection: desc
first: 10
# WBTC/WETH pair address
where: { pair_: { id: "0xbb2b8038a1640196fbe3e38816f3e67cba72d940" } }
) {
liquidityTokenBalance
id
pair {
token0 {
symbol
}
token1 {
symbol
}
id
}
user {
id
}
}
}
Get historical data on liquidity positions in pair. Snapshots store historical data for liquidity positions. Sort by block
in descending order, filtering for a specific pair.
{
liquidityPositionSnapshots(
orderBy: timestamp
orderDirection: desc
where: {
# WBTC/WETH pair address
pair_: { id: "0xbb2b8038a1640196fbe3e38816f3e67cba72d940" }
liquidityTokenBalance_gt: "0"
}
) {
block
liquidityTokenBalance
timestamp
id
user {
id
}
liquidityTokenTotalSupply
}
}
Get Uniswap performance. Uniswap data is accumulated and condensed into daily statistics in the uniswapDayDatas
entity.
{
uniswapDayDatas(first: 10, orderBy: date, orderDirection: desc) {
date
dailyVolumeETH
dailyVolumeUSD
totalLiquidityETH
totalLiquidityUSD
}
}
Conclusion
In this tutorial, we explored various entities such as swaps, tokens, and liquidity positions, and how to query them using GraphQL and Python. Additionally, we provided examples of querying historical data and filtering results based on specific conditions. By following this tutorial, you can effectively interact with and analyze data from Uniswap V2 using Chainstack subgraphs.
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Updated 4 months ago