88 lines
3.4 KiB
Python
88 lines
3.4 KiB
Python
import urllib.parse
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import hashlib
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import hmac
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import base64
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import requests
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import time
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import xlwings,pandas # for excel sheets. pandas reads it, xlwings writes it; not sure if xlwings is needed anymore but pandas requires a few modules to be installed -pip install pandas[excel]
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import io
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from dotenv import load_dotenv
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import os
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load_dotenv()
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# binance.us api url
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api_url = "https://api.binance.us"
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# get binanceus signature
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def get_binanceus_signature(data, secret):
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postdata = urllib.parse.urlencode(data)
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message = postdata.encode()
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byte_key = bytes(secret, 'UTF-8')
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mac = hmac.new(byte_key, message, hashlib.sha256).hexdigest()
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return mac
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# Attaches auth headers and returns results of a POST request
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def binanceus_request_key(uri_path, data, api_key, api_sec):
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headers = {}
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headers['X-MBX-APIKEY'] = api_key
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signature = get_binanceus_signature(data, api_sec)
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params={
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**data,
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"signature": signature,
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}
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req = requests.get((api_url + uri_path), params=params, headers=headers)
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return req.text
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def binanceus_request(uri_path):
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req = requests.get((api_url + uri_path))
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return req.text
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# create a file named '.env' with the below keys like so: BINANCE_API_KEY="mysuperlongbinancekey"
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api_key = os.environ.get("BINANCE_API_KEY")
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secret_key = os.environ.get("BINANCE_SECRET_KEY")
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# uri_path = "/api/v3/ticker/price" # URI NO KEY initial api link doesn't require auth, 2 columns simple data
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# uri_path = "/api/v3/openOrders" # get all open orders
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uri_path = "/sapi/v1/capital/config/getall" # asset fees and wallet status get all
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data_time_stamp = {
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"timestamp": int(round(time.time() * 1000))
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}
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# here we pull the data
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# result = binanceus_request(uri_path) # URI NO KEY
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result = binanceus_request_key(uri_path, data_time_stamp, api_key, secret_key)
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print("Reading JSON data into DataFrame...")
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df_nested = pandas.read_json(io.StringIO(result)) # this works, don't use wrong uri_path
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# df_nested = pandas.DataFrame.from_dict(result, orient='columns') # dictionary example doesn't work with json data
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print("DataFrame created successfully.")
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# print (df_nested) # to prove it works (176 rows x 14 columns)
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# Check the shape of the DataFrame
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print("DataFrame shape:", df_nested.shape) # will show if it's a dataframe or not i reckon
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# print(df_nested.dtypes)
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# print(df_nested)
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out_path = "S:\\Documents\\prodigy\\Coding-Programming\\Repos\\python-scripts\\Scripts\\api-testing\\" # windows needs double \\ escape the escape
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try:
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# wb = xlwings.Book('binance.xlsx').sheets('BinanceWallet') # Method 1; file name and sheet page
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# wb.range('a1').options(pandas.DataFrame, index=False).value = pandas.DataFrame(df_nested) # works using URI NO KEY dataset, have to have file open
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# df_nested.to_excel(out_path + 'binance.xlsx', sheet_name='BinanceWallet', index=False) # Method 2; creates new file with sheet name, will delete current document and replace be careful
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with pandas.ExcelWriter(out_path + 'binance.xlsx', mode="a", engine="openpyxl", if_sheet_exists="replace") as writer: # Method 3(best); mode="a" means append
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df_nested.to_excel(writer, sheet_name="BinanceWallet") # has more options that actually work, still need to pip install openpyxl though
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print(out_path + 'binance.xlsx')
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print("Excel Sheet written successfully")
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except Exception as e:
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print(f"Error: {e}")
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