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Environment Setup Guide

Before starting quantitative trading, you need a clean, stable, and isolated Python environment. This guide provides two mainstream solutions: Miniconda (Classic & Stable) and uv (Fast & Modern).

Option A: Miniconda (Classic)

Miniconda is a minimal installer for conda. It is the industry standard for data science, making it easy to manage Python versions and dependencies.

1. Install Miniconda

Tip: Users in China can download from Tsinghua Mirror for faster speeds.

  1. Visit Miniconda Website (or Tsinghua Mirror).
  2. Download the Windows 64-bit installer (.exe).
  3. Run the installer. It is recommended to check "Add Miniconda3 to my PATH environment variable" (convenient for beginners).
  4. After installation, open Command Prompt (CMD) or PowerShell.

Method A: Via Homebrew (Recommended) Open Terminal and run: 

brew install --cask miniconda
init conda

Method B: Via Installer Script 1. Download script for Apple Silicon or Intel. 2. Run in terminal: bash Miniconda3-latest-MacOSX-arm64.sh.

Open terminal and run: 

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh
~/miniconda3/bin/conda init bash

1.5 Configure Mirrors (For Users in China)

If you are located in China, download speeds might be slow. It is recommended to use the Tsinghua University mirror.

# Configure Conda Mirror
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --set show_channel_urls yes

# Configure Pip Mirror
pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

2. Create Virtual Environment

Do not install libraries directly into your system Python! We need a dedicated "sandbox".

Open your terminal (or CMD/Anaconda Prompt on Windows) and type:

# Create an environment named 'akquant' with Python 3.10
conda create -n akquant python=3.10 -y

# Activate the environment
conda activate akquant

Once activated, your command prompt prefix will change to (akquant), indicating you are inside the sandbox.

Option B: uv (Fast & Modern)

If you want extreme speed and lightweight management, uv is the fastest package manager in the Python ecosystem (written in Rust). It replaces pip and virtualenv.

1. Install uv

Run in PowerShell: 

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Run in Terminal: 

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Create & Manage Environment

uv does not require pre-installed Python; it manages Python versions for you.

# 1. Create a project directory
mkdir my_strategy
cd my_strategy

# 2. Initialize virtual env (Specify Python 3.10)
# uv will automatically download Python 3.10 and create .venv folder
uv venv --python 3.10

# 3. Activate environment
# Windows:
.venv\Scripts\activate
# macOS / Linux:
source .venv/bin/activate

3. Install AKQuant & Verify

Whether you used Miniconda or uv, you should now be in an activated virtual environment.

Install

If using Miniconda: 

pip install akquant

# Users in China can use the Tsinghua mirror for speed:
# pip install akquant -i https://pypi.tuna.tsinghua.edu.cn/simple

If using uv: 

uv pip install akquant

# Users in China:
# uv pip install akquant --index-url https://pypi.tuna.tsinghua.edu.cn/simple

Verify

Create a test script verify.py:

import akquant
import pandas as pd

print(f"AKQuant Version: {akquant.__version__}")
print(f"Pandas Version: {pd.__version__}")
print("Environment setup successful! Ready to trade.")

Run it:

python verify.py

If you see the success message, your arsenal is ready! Next, go to Python for Finance to learn syntax, or jump to Quant Guide to start coding strategies.