Python File Handling for Algorithmic & Crypto Trading 15/100 Days

Quantitative Analysis is growing rapidly in developed markets like Singapore. With Python:

• Analyze historical data
• Customize technical indicators
• Backtest and automate strategies

Freqtrade Strategies: Learn and apply
With Freqtrade you can easily:

• Train your trading bots with historical data
• Store data in JSON or CSV

Use indicators like RSI, MACD, and Bollinger Bands

Python File Handling in Algorithmic Trading

Why is File Handling important?
In Algo Trading, we deal with many types of files — such as:

.csv (trade data)

.json (config)

.log (trading logs)

Binary files (special data formats)

It is important to have knowledge of Python File Handling so that you can store, process and record data properly.

Use Cases of File Handling in Algo Trading
1. Historical Data Management

• Downloading data from the market and storing it in .csv or .json format
• Later using it for analysis, backtesting and machine learning
• with open(“price_data.csv”, “r”) as file:
• data = file.readlines()

2. Loading Data for Analysis

• Reading data from files and using it in libraries like Pandas
• This data helps in model training and strategy testing
• import pandas as pd
  df = pd.read_csv(“trade_data.csv”)

3. Trade Logging & Record Keeping

• Logging every trade information: Symbol, Price, Quantity
• Keeping error logs so that debugging is easy
• with open(“trade_log.txt”, “a”) as log:
• log.write(“Buy BTC at $42000\n”)

4. Configuration Storage (JSON/YAML)

Storing API Keys, Strategy Parameters and Settings in .json or .yaml files

This is useful in Automation

{
“api_key”: “ABC123”,

“max_trade”: 5,

“strategy”: “RSI”

}