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PythonForForexPythonForForex
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‎.gitignore‎

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/

‎balances.py‎

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import os
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from binance.client import Client
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# init
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api_key = os.environ.get('binance_api')
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api_secret = os.environ.get('binance_secret')
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client = Client(api_key, api_secret)
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## main
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# get balances for all assets & some account information
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print(client.get_account())
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# get balance for a specific asset only (BTC)
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print(client.get_asset_balance(asset='BTC'))
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# get balances for futures account
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print(client.futures_account_balance())
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# get balances for margin account
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# will raise an exception if margin account is not activated
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#print(client.get_margin_account())

‎btc_bars3.csv‎

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‎btc_historical_csv.py‎

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import csv
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import json
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import os
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import pandas as pd
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from binance.client import Client
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# init
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api_key = os.environ.get('binance_api')
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api_secret = os.environ.get('binance_secret')
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client = Client(api_key, api_secret)
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## main
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# valid intervals - 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1M
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# get timestamp of earliest date data is available
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timestamp = client._get_earliest_valid_timestamp('BTCUSDT', '1d')
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print(timestamp)
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# request historical candle (or klines) data
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bars = client.get_historical_klines('BTCUSDT', '1d', timestamp, limit=1000)
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# print(bars)
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# option 1 - save to file using json method - this will retain Python format (list of lists)
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with open('btc_bars.json', 'w') as e:
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json.dump(bars, e)
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# option 2 - save as CSV file using the csv writer library
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with open('btc_bars.csv', 'w', newline='') as f:
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wr = csv.writer(f)
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for line in bars:
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wr.writerow(line)
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# option 3 - save as CSV file without using a library. Shorten to just date, open, high, low, close
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with open('btc_bars2.csv', 'w') as d:
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for line in bars:
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d.write(f'{line[0]}, {line[1]}, {line[2]}, {line[3]}, {line[4]}\n')
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# delete unwanted data - just keep date, open, high, low, close
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for line in bars:
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del line[5:]
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# option 4 - create a Pandas DataFrame and export to CSV
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btc_df = pd.DataFrame(bars, columns=['date', 'open', 'high', 'low', 'close'])
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btc_df.set_index('date', inplace=True)
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print(btc_df.head())
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# export DataFrame to csv
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btc_df.to_csv('btc_bars3.csv')

‎buy_bnb.py‎

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import os
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from binance.client import Client
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# init
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api_key = os.environ.get('binance_api')
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api_secret = os.environ.get('binance_secret')
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client = Client(api_key, api_secret)
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# functions
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def topup_bnb(min_balance: float, topup: float):
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''' Top up BNB balance if it drops below minimum specified balance '''
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bnb_balance = client.get_asset_balance(asset='BNB')
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bnb_balance = float(bnb_balance['free'])
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if bnb_balance < min_balance:
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qty = round(topup - bnb_balance, 5)
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print(qty)
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order = client.order_market_buy(symbol='BNBUSDT', quantity=qty)
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return order
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return False
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# example
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min_balance = 1.0
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topup = 2.5
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order = topup_bnb(min_balance, topup)

‎create_order.py‎

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import os
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from binance.client import Client
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from binance.enums import *
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from binance.exceptions import BinanceAPIException, BinanceOrderException
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# init
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api_key = os.environ.get('binance_api')
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api_secret = os.environ.get('binance_secret')
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client = Client(api_key, api_secret)
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## main
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# create order
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# make a test order first. This will raise an exception if the order is incorrect.
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buy_order_limit = client.create_test_order(
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symbol='ETHUSDT',
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side='BUY',
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type='LIMIT',
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timeInForce='GTC',
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quantity=100,
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price=200)
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buy_order = client.create_test_order(symbol='ETHUSDT', side='BUY', type='MARKET', quantity=100)
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# create a real order if the test orders did not raise an exception
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try:
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buy_limit = client.create_order(
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symbol='ETHUSDT',
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side='BUY',
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type='LIMIT',
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timeInForce='GTC',
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quantity=100,
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price=200)
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# same order but with helper function
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buy_limit = client.order_limit_buy(symbol='ETHUSDT', quantity=100, price=200)
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# market order using a helper function
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market_order = client.order_market_sell(symbol='ETHUSDT', quantity=100)
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# cancel previous orders
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cancel = client.cancel_order(symbol='ETHUSDT', orderId=buy_limit['orderId'])
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except BinanceAPIException as e:
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# error handling goes here
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print(e)
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except BinanceOrderException as e:
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# error handling goes here
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print(e)
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# using binance constants - the library has hard coded commonly used strings
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# https://python-binance.readthedocs.io/en/latest/constants.html#
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# this order uses required strings such as 'BUY' and 'MARKET' which are prone to spelling errors
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buy_order = client.create_test_order(symbol='ETHUSDT', side='BUY', type='MARKET', quantity=100)
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# binance constants can be used instead
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buy_order = client.create_test_order(symbol='ETHUSDT', side=SIDE_BUY, type=ORDER_TYPE_MARKET, quantity=100)

‎indicators.py‎

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import btalib
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import pandas as pd
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# load DataFrame
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btc_df = pd.read_csv('btc_bars3.csv', index_col=0)
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# btc_df.set_index('date', inplace=True)
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btc_df.index = pd.to_datetime(btc_df.index, unit='ms')
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# calculate 20 moving average using Pandas
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btc_df['20sma'] = btc_df.close.rolling(20).mean()
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print(btc_df.tail(5))
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# calculate just the last value for the 20 moving average
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mean = btc_df.close.tail(20).mean()
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# get the highest closing price in 2020
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max_val = btc_df.close['2020'].max()
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print(mean)
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print(max_val)
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# technical indicators using bta-lib
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# sma
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sma = btalib.sma(btc_df.close)
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print(sma.df)
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# create sma and attach as column to original df
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btc_df['sma'] = btalib.sma(btc_df.close, period=20).df
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print(btc_df.tail())
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# calculate rsi and macd
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rsi = btalib.rsi(btc_df, period=14)
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macd = btalib.macd(btc_df, pfast=20, pslow=50, psignal=13)
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print(rsi.df)
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print(macd.df)
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# access last rsi value
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print(rsi.df.rsi[-1])
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# join the rsi and macd calculations as columns in original df
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btc_df = btc_df.join([rsi.df, macd.df])
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print(btc_df.tail())

‎latest_btc_price.py‎

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import os
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from binance.client import Client
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# init
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api_key = os.environ.get('binance_api')
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api_secret = os.environ.get('binance_secret')
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client = Client(api_key, api_secret)
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## main
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# get latest price from Binance API
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btc_price = client.get_symbol_ticker(symbol='BTCUSDT')
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# print full output (dictionary)
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print(btc_price)
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# print just the price
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print(btc_price['price'])

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