AdrianClv / Tokens-Analysis

Tokens analysis

Simple example of how to use Python to get data from the Ethereum blockchain.

Files

• tokens.ipynb: Jupyter notebook with the code used (Python)
• tokens.csv (input file): List of tokens to analyze
• ./datasets/balances.csv (output file): Matrix with the balance of tokens of different addresses
• ./datasets/{TOKEN_NAME}.csv (output file): Raw data of user transactions with the token

Code

from urllib2 import Request, urlopen, URLError
import pandas as pd
import numpy as np
import json

Get data from Etherscan

# Write your Etherscan API key here
APIKEY = ""

# Make sure you have this file in the same directory
tokens = pd.read_csv('tokens.csv', index_col=False, header=0)

tokenTxs = {}

def getTxs(token):
    try:
        # Will look only for normal txs
        request = Request("http://api.etherscan.io/api?module=account&action=txlist&address={}&apikey={}".format(token["Address"], APIKEY))
        response = urlopen(request)
        txs = response.read()
        tokenTxs[token["Project"]] = pd.read_json(json.dumps(json.loads(txs)["result"]), orient='records')
    except URLError, e:
        print 'API error. Got an error code:', e

tokens.apply(getTxs, axis=1)

# Sample data
tokenTxs["Acade City"].head()

	blockHash	blockNumber	confirmations	contractAddress	cumulativeGasUsed	from	gas	gasPrice	gasUsed	hash	input	isError	nonce	timeStamp	to	transactionIndex	value
0	0x5fd4ccfbc4fd08790bec564d3941bdd39a59fc242fc7...	2541610	798691		419262	0x5f23acdd1e87112b5fe143509d74ded22b6e59b3	400000	21800903077	87290	0x92089c7ccbcb0e190e4d87e3158c0572e066f22ab53a...	0x7d124a0200000000000000000000000008e50ae3e83f...	0	15	2016-10-31 14:38:13	0xac709fcb44a43c35f0da4e3163b117a17f3770f5	1	0.000000e+00
1	0xacf96f6ef0fcd8878ed90705f3b35a01d36f41a73ffb...	2541693	798608		205240	0xb6f2af0b3551161fe95f18219a8d402fc4e0233b	100000	21000000000	100000	0xf64a321a017ddf84a0daa9aecdf3353c0a5b1369822f...	0x	1	27	2016-10-31 14:58:24	0xac709fcb44a43c35f0da4e3163b117a17f3770f5	5	1.000000e+17
2	0x12aa0744a148380816466e7a8b7f7302bcd3971a998c...	2541866	798435		105000	0x5d61433e4dbd2e6a44c62846a7ef3a1d4cd256b3	21000	21000000000	21000	0xdcdbed18849b1b7603c0fa5075a037cf48971ac9ce1c...	0x	1	0	2016-10-31 15:43:16	0xac709fcb44a43c35f0da4e3163b117a17f3770f5	4	1.000000e+12
3	0x9ea42e81a52662618b847314d253bbb3fc7bef219f0d...	2542668	797633		121000	0xcecafbdbbb5d5baf57844a6611e36fc781aad017	100000	21000000000	100000	0x934743bcc99b9e211ff607407740e5eebd3255283a33...	0x	1	0	2016-10-31 18:52:16	0xac709fcb44a43c35f0da4e3163b117a17f3770f5	1	6.000000e+18
4	0x6d29e46ae11e4c5cef7f0ea2580993fd6451ce5a5ec7...	2543686	796615		358785	0x6cfabd40891abe610efd0cc0cfb8a2f2209ea68d	100000	26000000000	100000	0xb369fac72065e37a74712f8c4375f5d1deea9b735c01...	0x	1	0	2016-10-31 22:58:32	0xac709fcb44a43c35f0da4e3163b117a17f3770f5	10	4.000000e+18

# Remove duplicates
uniqueAddresses = np.array([])

for txs in tokenTxs.itervalues():
    uniqueAddresses = np.concatenate([uniqueAddresses, np.unique(txs["from"])])

print "Number of user accounts (with duplicates): {}".format(len(uniqueAddresses))
uniqueAddresses = np.unique(uniqueAddresses)
print "Number of user accounts (after removing duplicates): {}".format(len(uniqueAddresses))

Number of user accounts (with duplicates): 17362
Number of user accounts (after removing duplicates): 15286

Get data from local node

# Uncomment to install web3
#!pip install web3

from web3 import Web3, KeepAliveRPCProvider, IPCProvider

# Note that you should create only one RPCProvider per
# process, as it recycles underlying TCP/IP network connections between
# your process and Ethereum node
#web3 = Web3(KeepAliveRPCProvider(host='localhost', port='8545'))

# or for an IPC based connection
web3 = Web3(IPCProvider())

# ERC20 standar
abi = json.loads('[{"constant":false,"inputs":[{"name":"_spender","type":"address"},{"name":"_value","type":"uint256"}],"name":"approve","outputs":[{"name":"success","type":"bool"}],"payable":false,"type":"function"},{"constant":true,"inputs":[],"name":"totalSupply","outputs":[{"name":"","type":"uint256"}],"payable":false,"type":"function"},{"constant":false,"inputs":[{"name":"_from","type":"address"},{"name":"_to","type":"address"},{"name":"_value","type":"uint256"}],"name":"transferFrom","outputs":[{"name":"success","type":"bool"}],"payable":false,"type":"function"},{"constant":true,"inputs":[{"name":"_owner","type":"address"}],"name":"balanceOf","outputs":[{"name":"balance","type":"uint256"}],"payable":false,"type":"function"},{"constant":false,"inputs":[{"name":"_to","type":"address"},{"name":"_value","type":"uint256"}],"name":"transfer","outputs":[{"name":"success","type":"bool"}],"payable":false,"type":"function"},{"constant":true,"inputs":[{"name":"_owner","type":"address"},{"name":"_spender","type":"address"}],"name":"allowance","outputs":[{"name":"remaining","type":"uint256"}],"payable":false,"type":"function"},{"anonymous":false,"inputs":[{"indexed":true,"name":"_from","type":"address"},{"indexed":true,"name":"_to","type":"address"},{"indexed":false,"name":"_value","type":"uint256"}],"name":"Transfer","type":"event"},{"anonymous":false,"inputs":[{"indexed":true,"name":"_owner","type":"address"},{"indexed":true,"name":"_spender","type":"address"},{"indexed":false,"name":"_value","type":"uint256"}],"name":"Approval","type":"event"}]')

balances = pd.DataFrame("", index=uniqueAddresses, columns=tokens["Project"].values)

def setBalances(token):
    tokenContract = web3.eth.contract(
        abi = abi,
        address = token["Address"]
    )

    for address in uniqueAddresses:
        try:
            balances.set_value(address, token["Project"], tokenContract.call().balanceOf(address))
        except URLError, e:
            print 'Web3 error. Got an error code:', e

tokens.apply(setBalances, axis=1)

# Sample data
balances.head()

	Augur	ICONOMI	Golem	Digix	Pluton (Plutus)	SingularDTV	First Blood	VSice (VDlice)	Hacker Gold (Ether.camp)	Maker DAO	Chrono Bank	Unicorns (Ethereum Fundation)	Xaurum	Acade City	Swarm City	Bitpark Coin	Round
0x00004aba4ac63de11447e4e17aca83f0abb1fc33	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
0x000118f3bd5a727f663c85c671370760c7730927	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
0x0001aebe0b48bbf1cee8df2c0dfd7c2031543859	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
0x0001fe7648a2c144becdf9f17f0055315a519f86	0	0	0	0	0	0	0	0	0	0	134349877	0	0	0	0	0	0
0x000313efbb302549f83e35e50bf0a4e3f0a639af	0	0	2262127659574400000	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Export

# You need to have a ./dataset directory
# Raw data
for project, txs in tokenTxs.items():
    url = "./datasets/{}.csv".format(project)
    txs.to_csv(url, sep=',')

# Balances
balances.to_csv("./datasets/balances.csv", sep=',')