Extracting Ethereum Historical Data from Binance API

As an Ethereum developer, you are probably familiar with the importance of historical data for analysis and trading strategies. However, extracting accurate historical data from external APIs like Binance can be challenging due to various limitations.

Problem: Limited time range

You have encountered an issue where your code is only receiving 3 entries despite expecting around 700 entries between [current_time – 2 years] and [current_time]. This discrepancy stems from the fact that historical data on Binance usually has a much longer time range than what you are looking for.

Why this happens

There are several reasons why this can happen:

• API Limitations: Binance APIs have rate limits, which can prevent excessive requests to avoid overloading their servers.

• Data caching: External APIs often cache historical data for performance and reliability reasons, which can lead to older records being returned before the requested time range.

• Data format inconsistencies

  

  : Historical data may be stored in different formats or structures, making it difficult to extract specific records.

Solutions

To overcome these challenges, consider the following solutions:

1. Check API rate limits

Make sure you are not exceeding Binance’s API rate limits. You can do this by checking their documentation and monitoring the number of requests using a tool like [Rate Limit Checker](

import requests
max_requests = 1000
current_time = datetime.now()
while true:
try:
response = requests.get(' params={'symbol': 'ETH', 'interval': '1D', 'start': int(current_time.timestamp()) - 86400, 'count': 70})
if response.status_code == 200:
abort
except exception like e:
print(f"Error: {e}")

2. Use Binance’s Historical Data Feature

Binance offers a historical data feature that allows you to retrieve data for any time period, including long-term ranges such as [current_time – 2 years]. However, this feature may not be available or may require additional authentication.

requests to import





Set your API credentials and other parameters
api_key = 'YOUR_API_KEY'
api_secret = 'YOUR_API_SECRET'
symbol = 'ETH'
interval = '1D'
start_date = (datetime.now() - datetime.timedelta(days=730)).strftime('%Y-%m-%d')
end_date = (datetime.now() - datetime.timedelta(days=365)).strftime('%Y-%m-%d')
response = requests.get(f' interval, start, end)', 
auth=(api_key, api_secret), headers={'limit': 100})
if response.status_code == 200:
    print(response.json())

3. Use a library or framework

Consider using libraries such as [pandas-datareader]( (for Python 3.x) or [yfinance]( (for Python 2.x), which provide more comprehensive and flexible data extraction capabilities.

import pandas as pd
pd.set_option('display.max_columns', None)
symbol = 'ETH'
start_date = datetime.now() - timedelta(days=730).strftime('%Y-%m-%d')
end_date = (datetime.now() - datetime.timedelta(days=365)).strftime('%Y-%m-%d')
df = pd.read_csv(f'
print(df.head(70)) 
Print the first 70 records

By implementing these solutions, you should be able to extract historical data from Binance that meets your requirements.