Update installation instructions with video link

README.md

@@ -2,7 +2,7 @@
 <img align="center" width="30%" alt="image" src="https://github.com/AI4Finance-Foundation/FinGPT/assets/31713746/e0371951-1ce1-488e-aa25-0992dafcc139">
 </div>
 
-# FinRL: Financial Reinforcement Learning → FinRL-X 
+# FinRL: Financial Reinforcement Learning → FinRL-X
 
 <div align="center">
 <img align="center" src=figs/logo_transparent_background.png width="55%"/>
@@ -24,7 +24,7 @@
 
 > [!IMPORTANT]
 > **FinRL-X** is the next-generation evolution of FinRL, designed for AI-native, modular, and production-oriented quantitative trading.
-> 
+>
 > - **This repository (`FinRL`)** preserves the original end-to-end educational and research framework.
 > - **For the latest architecture, live trading deployment, and production-focused development, please use [`FinRL-X / FinRL-Trading`](https://github.com/AI4Finance-Foundation/FinRL-Trading).**
 
@@ -87,7 +87,7 @@ Key contributors include:
 
 - [**Hongyang (Bruce) Yang**](https://www.linkedin.com/in/brucehy/) – research and development on financial reinforcement learning frameworks, market environments, and quantitative trading applications
 - [other contributors…]
-  
+
 ## Overview
 
 FinRL is the original open-source framework for financial reinforcement learning, organized around three core layers:

docs/source/start/installation.rst

@@ -188,7 +188,7 @@ Windows 10 (wsl install)
 
 Step 1: Install Ubuntu on Windows 10
 --------------------------------------
-Please check this video for detailed steps:
+Please check this video for detailed steps: https://youtu.be/QM3mzEJCzjY?si=UxTlRGeMOG-daROy
 
 .. raw:: html
 

examples/FinRL_StockTrading_2026_1_data.py

@@ -6,14 +6,21 @@
 Introduce how to use FinRL to fetch and process data that we need for ML/RL trading.
 """
 
+from __future__ import annotations
+
 import itertools
 
 import pandas as pd
 import yfinance as yf
 
 from finrl import config_tickers
-from finrl.config import INDICATORS, TRAIN_START_DATE, TRAIN_END_DATE, TRADE_START_DATE, TRADE_END_DATE
-from finrl.meta.preprocessor.preprocessors import FeatureEngineer, data_split
+from finrl.config import INDICATORS
+from finrl.config import TRADE_END_DATE
+from finrl.config import TRADE_START_DATE
+from finrl.config import TRAIN_END_DATE
+from finrl.config import TRAIN_START_DATE
+from finrl.meta.preprocessor.preprocessors import data_split
+from finrl.meta.preprocessor.preprocessors import FeatureEngineer
 from finrl.meta.preprocessor.yahoodownloader import YahooDownloader
 
 # %% Part 1. Fetch data - Single ticker

examples/FinRL_StockTrading_2026_2_train.py

@@ -7,11 +7,15 @@
 Introduce how to use FinRL to make data into the gym form environment, and train DRL agents on it.
 """
 
+from __future__ import annotations
+
 import pandas as pd
 from stable_baselines3.common.logger import configure
 
 from finrl.agents.stablebaselines3.models import DRLAgent
-from finrl.config import INDICATORS, TRAINED_MODEL_DIR, RESULTS_DIR
+from finrl.config import INDICATORS
+from finrl.config import RESULTS_DIR
+from finrl.config import TRAINED_MODEL_DIR
 from finrl.main import check_and_make_directories
 from finrl.meta.env_stock_trading.env_stocktrading import StockTradingEnv
 

examples/FinRL_StockTrading_2026_3_Backtest.py

@@ -8,7 +8,10 @@
 Mean Variance Optimization and DJIA index.
 """
 
+from __future__ import annotations
+
 import matplotlib
+
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np

finrl/config_tickers.py

@@ -140,7 +140,7 @@
     "TRI",
     "WBD",
     "WMT",
-    "ZS"
+    "ZS",
 ]
 
 # SP 500 constituents at 2019