Python is a very popular programming language in the fields of data science, machine learning, and algorithmic trading. In particular, there are various libraries available to implement and test automated trading. Among them, Zipline<\/strong> is a popular backtesting framework for algorithmic trading. In this article, we will take a closer look at how to install and use Zipline.<\/p>\n Zipline is a Python-based open-source algorithmic trading backtesting library for financial markets developed by Quantopian. Zipline provides the following key features:<\/p>\n Before installing Zipline, a few preparations are needed. You can follow the steps below to proceed with the installation.<\/p>\n Zipline is recommended for installation on Linux and Mac OS. If you want to use it on Windows, it is recommended to use Windows Subsystem for Linux (WSL). Additionally, Python 3.5 or higher is required.<\/p>\n It is advisable to set up a virtual environment to install Zipline. This helps manage dependencies. Here is how to set up a virtual environment:<\/p>\n The next step is to install Zipline. Zipline can be installed via pip. The installation command is as follows:<\/p>\n Installing Zipline requires several essential packages, such as numpy and pandas. You can install them as follows:<\/p>\n There may be issues during installation. In this case, use the command below to install Zipline:<\/p>\n Once Zipline is installed, you can check whether the installation was successful by using the code below.<\/p>\n If you run the above code and no errors occur, then Zipline is installed successfully. If it runs normally, you will be able to check the version of Zipline.<\/p>\n Now that Zipline is installed, let\u2019s create a basic automated trading strategy.<\/p>\n The way to load data in Zipline is as follows:<\/p>\n The code above is an example of writing and executing a simple strategy that buys AAPL (Apple Inc.) stock. It is very useful for understanding the basic structure.<\/p>\n Zipline can visualize results using matplotlib. You can add the following code to visualize:<\/p>\n This code visualizes the portfolio value during January 2020. It allows you to see the performance of the algorithm strategy at a glance.<\/p>\n Zipline is a powerful tool for algorithmic trading using Python. Through the contents explained in this article, you learned how to install Zipline and implement a basic trading strategy. By taking this step, you can gain confidence in developing and backtesting more complex strategies.<\/p>\n Now that you have installed Zipline and learned the basics, consider the following topics for your next steps:<\/p>\n1. Introduction to Zipline<\/h2>\n
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2. Preparing to Install Zipline<\/h2>\n
2.1. System Requirements<\/h3>\n
2.2. Setting Up a Virtual Environment<\/h3>\n
python -m venv zipline-env\nsource zipline-env\/bin\/activate # Linux \/ Mac OS\nzipline-env\\Scripts\\activate # Windows<\/code><\/pre>\n3. Installing Zipline<\/h2>\n
pip install zipline<\/code><\/pre>\n3.1. Installing Required Packages<\/h3>\n
pip install numpy pandas matplotlib pytz<\/code><\/pre>\n3.2. In Case of Problems<\/h3>\n
pip install git+https:\/\/github.com\/quantopian\/zipline.zip<\/code><\/pre>\n4. Validating Zipline<\/h2>\n
import zipline\nprint(zipline.__version__)<\/code><\/pre>\n5. Trying Out Zipline<\/h2>\n
5.1. Loading Basic Data<\/h3>\n
from zipline.api import order, record, symbol\nfrom zipline import run_algorithm\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndef initialize(context):\n context.asset = symbol('AAPL')\n \ndef handle_data(context, data):\n order(context.asset, 1) # Buy AAPL stock\n record(AAPL=data.current(context.asset, 'price'))\n\nstart = pd.Timestamp('2020-01-01', tz='utc')\nend = pd.Timestamp('2020-01-31', tz='utc')\n\nrun_algorithm(start=start, end=end, initialize=initialize, handle_data=handle_data) # Run algorithm<\/code><\/pre>\n5.2. Visualizing Results<\/h3>\n
results = run_algorithm(start, end, initialize=initialize, handle_data=handle_data)\nresults.portfolio_value.plot()\nplt.show()<\/code><\/pre>\n6. Conclusion<\/h2>\n
7. Next Steps<\/h2>\n