Binance Futures Trading with Python | Build a Martingale Bot

Install Python and PyCharm, add Python to the path, and set up a new project to begin learning Python basics for building a Binance futures trading bot.

Demonstrates printing in Python by printing literals, variables, and concatenated statements. Shows using the format method and f-strings to embed variables in strings.

Master using variables to store values in Python with valid names and assignments. Learn four datatypes: string, integer, float, boolean and how to convert between them and assign multiple values.

Explore Python operators: arithmetic (+, -, *, /, //, %, **), comparison (==, !=, >, <, >=, <=), boolean (and, or, not), and assignment (=, +=, -=, *=, /=) examples.

Learn how Python functions, defined with def, organize code into reusable blocks, handle arguments, and use return to store outputs.

Learn how Python distinguishes local and global variables. Declare x inside and outside functions, and use the global keyword to access and modify variables from within.

Master Python lists by learning syntax with square brackets, positive and negative indexing, slicing, and methods like append, insert, remove, pop, and extend to manage and combine data.

Explore how dictionaries store data as key-value pairs and maintain order in Python. Create and manipulate dictionaries with keys, values, adding pairs, retrieving values, and removing entries with pop.

Explore if statements in Python to run code blocks when conditions are true, with indentation. See how else statements handle false conditions with simple examples.

Explore Python while loops, their syntax and condition-driven execution, and learn how break and continue control flow alter iterations with practical examples.

Learn to use Python for loops to run code blocks a number of times, iterating over lists, ranges, and dictionaries with examples that print items and access keys and values.

Explains how to define classes and create objects in Python, including properties, methods, and constructors, and demonstrates instantiating objects and invoking methods.

Learn to create a pandas series, a 1d data structure with indexes and values, by importing pandas, building from a list, printing it, and using custom indexes.

Explore pandas dataframes as two-dimensional tables with rows, columns, and an index. Learn to create a dataframe from a dictionary, import pandas, and select data by column and row.

Explore how to select a specific column in a pandas data frame using dot notation, single brackets, and double brackets, and how to fetch the last three rows with loc.

Learn how to select rows by column values using df.loc with a condition, such as age greater than 20 or marks greater than 85, and print the names.

Iterate columns in a data frame with a for loop, accessing each column by df['column_name'] (as with the name and age columns) and printing its values.

Apply the martingale strategy to futures, using staged Bitcoin bets for long and short positions, and calculate percentage profit as total profit divided by initial value times 100.

Apply the martingale strategy to trending markets, using long or short positions with safety orders and a volume multiplier, and place gaps at -1%, -3%, -7%, -15%.

Create a Binance futures testnet account, verify the email with a temporary email from temp mail.org in an incognito window, then log in for $15,000.

Install the python-binance library and pandas to connect to the Binance futures testnet. Import the client from the python-binance library and import pandas for data analysis.

Connect to the Binance API using API key and API secret on the testnet, create a client, fetch account balance, convert assets to a data frame, and print the balance.

Place market orders in python using the futures client to create orders with symbol btc usd, side buy or sell, and quantity, then test and print output.

Implement a live streaming function to fetch the current market price for a futures symbol on testnet. Then switch to a real futures account function to provide continuous price updates.

Create a function to compute price deviation from the initial price using current price, initial price, and direction, returning (current - initial)/initial * 100, negated for short.

Stream live real futures prices by calling the real market price function with a symbol, retrieve the ticker price, convert it to float, and continuously print updates.

Place limit orders in Python for Bitcoin USD futures by specifying symbol, side, quantity, and a price below market price; define functions to place buy and sell limit orders.

Place take profit orders for long and short futures using sell and buy limit orders, and calculate the take profit price from margin, position amount, leverage.

Compute the take profit price by pulling futures position data, filtering nulls, and calculating total margin, profit, and take profit percentage with leverage, then round to the correct decimals.

Implement a take profit order function for Binance futures trading with Python, handling long and short directions, using a try-except block and recursion to retry on runtime errors.

Develop Python functions to close buy and sell limit orders on Binance futures, cancel orders, and place new limit orders above or below market price.

Define initial trading parameters for a Binance futures martingale bot by setting Bitcoin USD, volume above $10, decimals, cycles, initial deviation, step, safety orders, volume multiplier, and direction.

Assemble the bot with a for loop and a while loop to place market orders with symbol, direction, and volume, capture initial price, then compute margin to detect open positions.

Place safety orders by evaluating the current price deviation against the next price level, then adjust the value multiplier and deviation to add more safety orders.

Assemble the bot step 4 by exiting the while true loops when no open positions exist, set margin to zero, and disable the loops to safeguard the trading bot.

Compute take-profit levels at 3% for futures. Update price and amount on each change, delete old TP orders, and verify open orders before re-placing a try-except block.

Adjust the bot's settings by increasing volume above $10, using one decimal place, 10-cycle plan, and a 0.05 deviation with a 2x multiplier, then verify take profit order and balance.

Create a Python class with a constructor that initializes properties like symbol, volume, decimals, cycles, initial deviation, safety orders, volume multiplier, direction, and take profit, using self to assign them.

Convert functions into class methods by using the self keyword and calling methods with self. Create a method run diff and place the for loop inside it to finish class.

Create bot objects from a class, configure bitcoin and ethereum trading parameters (volume, cycles, deviation, safety orders, take profit), and run them in multiprocessing via threading.

Discover instructions for building a martingale bot for Binance futures trading with Python. Follow guidance to implement automated, Python-driven trading workflows.

Identify trending currency pairs using the Ichimoku cloud indicator, learning the Tenkan Sen, Kijun Sen, Senkou Span A and B, the kumo cloud, and the lagging span.

Identify trending currency pairs using the Ichimoku cloud indicator, analyzing bullish uptrends and bearish downtrends with the thick green Kumo, bullish Kijun and Tenkan, and the lagging span position.

identify ichimoku trending currency pairs across larger and medium timeframes, then enter on five-minute confirmations—macd cross, stochastic cross, and candlestick patterns with bollinger band breakout—set stoploss at recent higher low.

Identify ichimoku trading currency pairs across forex and crypto on a four-hour chart, using the kumo cloud, senkou spans, tenkan, kijun, and lagging span to spot trending versus non-trending pairs.