FundSeeker

https://github.com/yuna78/fundseeker
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FundSeeker is a Python CLI tool for collecting and analyzing Chinese mutual fund data from Eastmoney...
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### Development Setup for Fundseeker

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Use these commands to set up the development environment. The script automatically creates a virtual environment, installs dependencies, and launches the interactive menu. Manual setup is also provided.

```bash
# macOS/Linux
./fundseeker.sh              # Auto-creates venv, installs deps, launches menu
```

```bash
# Windows
fundseeker.bat               # Same as above
```

```bash
# Manual setup (if needed)
python3 -m venv .venv
source .venv/bin/activate    # Windows: .venv\Scripts\activate
pip install -r requirements.txt
```

--------------------------------

### Manual Environment Setup

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Alternative method for setting up the Python virtual environment and installing dependencies manually. This is useful if the provided scripts fail.

```bash
python3 -m venv .venv && source .venv/bin/activate && pip install -r requirements.txt
```

--------------------------------

### Setup FundRecoFit Virtual Environment

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Steps to set up a Python virtual environment and install dependencies for the fund_reco_fit project.

```bash
# fund_reco_fit
cd fund_reco_fit
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```

--------------------------------

### Clone FundSeeker Repository

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Clone the project repository and navigate into the project directory to begin setup.

```bash
git clone https://github.com/yuna78/fundseeker.git
cd fundseeker
```

--------------------------------

### Run FundSeeker Development Setup

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Commands to set up and run the FundSeeker project locally on macOS/Linux and Windows.

```bash
cd fundseeker

# macOS/Linux
./fundseeker.sh

# Windows
fundseeker.bat
```

--------------------------------

### Report Issue Steps

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Example format for providing steps to reproduce an issue when reporting it via GitHub Issues.

```text
1. 运行命令 xxx
2. 输入参数 yyy
3. 看到错误 zzz
```

--------------------------------

### Launch FundSeeker CLI (Windows)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Launch the interactive menu for the FundSeeker CLI on Windows. This script sets up the environment and installs dependencies.

```bash
cd fundseeker
fundseeker.bat         # Launch interactive menu
```

--------------------------------

### Run FundSeeker CLI (macOS/Linux)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Execute the FundSeeker shell script to launch the interactive menu on macOS or Linux systems. This script handles environment setup and dependency installation.

```bash
cd fundseeker
./fundseeker.sh        # 启动交互式菜单
```

--------------------------------

### Launch FundSeeker CLI (macOS/Linux)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Launch the interactive menu for the FundSeeker CLI on macOS or Linux. This script sets up the environment and installs dependencies.

```bash
cd fundseeker
./fundseeker.sh        # Launch interactive menu
```

--------------------------------

### Advanced Model Configuration Example

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Configures a specific variant for the advanced recommendation model, including database paths, feature tables, model parameters, and top K selection.

```yaml
advanced_model:
  - label: 6m              # Variant identifier
    db_path: ../fund_reco_fit/data/fundseeker_nav.db
    feature_table: features_M_star
    weights_path: ../fund_reco_fit/models/model_params_6m.json
    top_k: 200
```

--------------------------------

### Python Function Example

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Example of a Python function with type hints and docstrings, adhering to PEP 8.

```python
from typing import List, Optional
from pathlib import Path

def fetch_fund_data(fund_code: str, start_date: Optional[str] = None) -> List[dict]:
    """
    获取基金数据

    Args:
        fund_code: 基金代码（6位）
        start_date: 开始日期，格式 YYYY-MM-DD

    Returns:
        基金数据列表
    """
    # 实现代码
    pass
```

--------------------------------

### Get Python Version

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Command to check the installed Python version, useful for environment information.

```bash
python --version
```

--------------------------------

### Install Dependencies (Windows)

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Run the 'repair' command in the Windows batch script to reinstall necessary dependencies if the script encounters module errors.

```bat
fundseeker.bat repair
```

--------------------------------

### Run FundSeeker Script

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Execute the main FundSeeker script. This is part of the testing and development setup.

```bash
# fundseeker
cd fundseeker
./fundseeker.sh
```

--------------------------------

### Run FundSeeker Script (macOS/Linux)

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Execute the main FundSeeker script to launch the interactive menu or run specific commands. The script handles virtual environment activation and dependency installation.

```bash
./fundseeker.sh
```

```bash
./fundseeker.sh rank
```

```bash
./fundseeker.sh details
```

```bash
./fundseeker.sh progress
```

```bash
./fundseeker.sh --help
```

```bash
./fundseeker.sh rank --start-date 2024-01-01 --end-date 2024-12-31 --limit 1000
```

```bash
./fundseeker.sh details --input 其他文件路径
```

```bash
./fundseeker.sh nav --start-date 2023-01-01 --end-date 2025-12-31
```

```bash
./fundseeker.sh nav 000001 --start-date 2023-01-01 --end-date 2025-12-31 --fmt csv
```

```bash
./fundseeker.sh recommend
```

```bash
./fundseeker.sh recommend --top-n 20
```

```bash
./fundseeker.sh recommend --mode advanced --top-n 200
```

```bash
./fundseeker.sh progress --date 2025-12-09
```

```bash
./fundseeker.sh menu
```

--------------------------------

### Import NAV Data to SQLite

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Import downloaded NAV data into an SQLite database. This involves setting up a Python virtual environment, installing dependencies, and running the NAV importer script.

```bash
cd ../fund_reco_fit
python3 -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

python3 -m src.nav_importer \
  --fundseeker-output ../fundseeker/output \
  --database data/fundseeker_nav.db
```

--------------------------------

### Get Latest Commit Hash

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Command to retrieve the hash of the latest commit, useful for project version information.

```bash
git log -1 --oneline
```

--------------------------------

### Configure Basic Recommendation Weights via Environment Variables

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Alternatively, set the weights for the basic recommendation model using environment variables. This allows for dynamic configuration without modifying the YAML file.

```bash
export FUNDSEEKER_RECENT_WEIGHT=0.4
export FUNDSEEKER_RATING_WEIGHT=0.25
```

--------------------------------

### Fetch Fund Details (Full Workflow)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Fetch detailed information for funds. This command assumes the fund list is available, typically generated or specified in previous steps.

```bash
./fundseeker.sh details
```

--------------------------------

### Fetch Fund Rankings and Ratings (Full Workflow)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Part of the full workflow, this command fetches a larger number of fund rankings and ratings. Ensure you are in the `fundseeker` directory.

```bash
cd fundseeker
./fundseeker.sh rank --limit 1000
```

--------------------------------

### Run Unit Tests

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Execute the Python unit tests for the FundSeeker project.

```bash
cd fundseeker
python -m unittest discover tests
```

--------------------------------

### Test Scripts After Restructuring

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/WORKFLOW_GUIDE.md

Verify that scripts can be executed with the --help flag after the project has been restructured. This confirms the scripts are accessible and executable.

```bash
# Test each script after restructuring
cd /path/to/fundseeker/fund_reco_fit
.venv/bin/python src/scripts/train.py --help
.venv/bin/python src/scripts/predict.py --help
```

--------------------------------

### Running Fundseeker Commands

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Execute various Fundseeker functionalities directly from the command line. The interactive menu is recommended for new users. Direct commands allow for specific operations like fetching rankings, details, NAV data, and generating recommendations.

```bash
# Interactive menu (recommended for first-time users)
./fundseeker.sh              # or fundseeker.bat on Windows
```

```bash
# Direct commands
./fundseeker.sh rank --limit 200                    # Fetch top 200 funds with ratings
```

```bash
./fundseeker.sh details --input data/fund_list.csv  # Fetch details for fund list
```

```bash
./fundseeker.sh nav                                 # Batch download NAV for all funds in list
```

```bash
./fundseeker.sh nav 000001 --start-date 2020-01-01  # Download NAV for specific fund
```

```bash
./fundseeker.sh recommend --top-n 200               # Generate basic recommendations
```

```bash
./fundseeker.sh recommend --mode advanced --adv-variant 6m  # Use ML model
```

```bash
./fundseeker.sh progress                            # Check task progress
```

--------------------------------

### Generate Basic Recommendations

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Generate fund recommendations using the 8-factor scoring model. The `--top-n` parameter specifies the number of top recommendations to generate.

```bash
./fundseeker.sh recommend --top-n 200
```

--------------------------------

### Rollback Method 1: Restore from Backup

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/WORKFLOW_GUIDE.md

Restore the project to a previous state by extracting a tarball backup. Ensure the backup file name includes the correct date and time.

```bash
# Method 1: Restore from backup
cd /path/to/fundseeker
tar -xzf fundseeker_backup_YYYYMMDD_HHMMSS.tar.gz
```

--------------------------------

### Activate FundRecoFit Virtual Environment

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Commands to activate the Python virtual environment for the fund_reco_fit project on different operating systems.

```bash
# 激活虚拟环境
source .venv/bin/activate  # macOS/Linux
# 或
.venv\Scripts\activate     # Windows
```

--------------------------------

### Run FundSeeker Script (Windows)

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Execute the FundSeeker batch script for Windows users. This script initiates the CLI, offering an interactive menu or direct command execution.

```bat
fundseeker.bat
```

```bat
fundseeker.bat rank
```

```bat
fundseeker.bat details
```

```bat
fundseeker.bat repair
```

--------------------------------

### Fetch Fund Rankings

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Use the CLI to fetch fund rankings, including multi-institution ratings. The `--limit` parameter controls the number of funds to retrieve.

```bash
./fundseeker.sh rank --limit 200
```

--------------------------------

### Clone FundSeeker Repository

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Clone your forked repository to your local machine and navigate into the project directory.

```bash
git clone https://github.com/your-username/fundseeker.git
cd fundseeker
```

--------------------------------

### Navigate to Project Directory

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Change the current directory to the FundSeeker project location. This is a prerequisite for running most CLI commands.

```bash
cd /Users/haitongsun/Documents/04.wocheng/999.fundseeker
```

--------------------------------

### FundSeeker Project Structure

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Overview of the directory structure for the FundSeeker Python CLI tool. Shows the organization of entry points, services, data fetchers, utilities, and output directories.

```tree
fundseeker/
├── .main.py              # Typer CLI entry point
├── fundseeker.sh/.bat    # Shell wrappers for venv management
├── config.yaml           # Configuration (weights, paths, model configs)
├── src/
│   ├── cli/              # Interactive menu system
│   ├── services/         # Business logic layer
│   │   ├── rank_service.py           # Ranking + rating fetcher
│   │   ├── detail_service.py         # Fund details with resume
│   │   ├── nav_service.py            # NAV time series downloader
│   │   ├── recommend_service.py      # Basic 8-factor scoring
│   │   └── advanced_recommend_service.py  # ML-based recommendations
│   ├── data/             # Low-level data fetchers (HTTP/parsing)
│   └── utils/            # Config, logging, I/O helpers
├── data/                 # User-editable fund lists
├── templates/            # CSV templates for fund lists
├── output/               # All generated Excel/CSV files (timestamped)
├── .fs/                  # Hidden progress tracking and logs
└── doc/                  # Requirements, design docs, user manual
```

--------------------------------

### Standard Fund Data Update Workflow

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

This sequence outlines the recommended standard process for updating fund data, involving checking status, generating an update plan, downloading data, importing it, and recalculating features.

```bash
cd /path/to/fundseeker/fund_reco_fit

# 步骤1: 检查数据状态
.venv/bin/python src/scripts/update/check_dates.py

# 步骤2: 生成更新计划
.venv/bin/python src/scripts/update/smart_update.py

# 步骤3: 按照smart_update.py的输出，逐个批次下载数据
cd ../fundseeker
cp ../fund_reco_fit/batch_update_YYYYMMDD.csv data/fund_list.csv
./fundseeker.sh nav --start-date YYYY-MM-DD

# 步骤4: 导入数据
cd ../fund_reco_fit
.venv/bin/python src/scripts/import_data.py

# 步骤5: 重新计算特征
.venv/bin/python src/feature_builder.py --freq M --table-name features_M_star
```

--------------------------------

### Basic Recommendation Weights Configuration

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Defines the weights for different factors used in basic mode recommendations. These can be overridden by environment variables.

```yaml
recommendation_weights:
  recent: 0.35      # Recent momentum
  mid: 0.20         # Mid-term trend
  long: 0.15        # Long-term stability
  risk_penalty: 0.10  # Volatility penalty
  manager: 0.10     # Manager performance
  scale: 0.05       # Fund size
  rating: 0.30      # Agency ratings
  age: 0.02         # Fund age
```

--------------------------------

### Incremental Fund Data Update with Python

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

This script attempts to automatically call the fundseeker's NavService for data download. It requires correct path configurations and is less frequently used manually due to its complexity compared to `smart_update.py`.

```bash
.venv/bin/python src/scripts/update/incremental_update.py
```

--------------------------------

### Running Fundseeker with Python Directly

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Execute Fundseeker commands using the Python interpreter after activating the virtual environment. This allows for more direct control and integration with Python scripts. Options include specifying date ranges and controlling resume capabilities.

```python
python .main.py rank --start-date 2024-01-01 --end-date 2024-12-31
```

```python
python .main.py details --no-resume                 # Disable resume capability
```

```python
python .main.py recommend --mode advanced --snapshot-date 2024-12-31
```

--------------------------------

### Running Fundseeker Tests

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

Execute the test suite for the Fundseeker project. You can run all tests or target specific test modules for focused testing.

```bash
python -m unittest discover tests    # Run all tests
```

```bash
python -m unittest tests.test_config # Run specific test module
```

--------------------------------

### Push to Your Fork

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Push your local feature branch to your forked repository on GitHub.

```bash
git push origin feature/your-feature-name
```

--------------------------------

### Configure Basic Recommendation Weights

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Customize the weights for the 8 factors used in the basic recommendation model by editing `fundseeker/config.yaml`.

```yaml
recommendation_weights:
  recent: 0.35        # 近期动量
  mid: 0.20           # 中期趋势
  long: 0.15          # 长期稳定性
  risk_penalty: 0.10  # 波动惩罚
  manager: 0.10       # 基金经理表现
  scale: 0.05         # 基金规模
  rating: 0.30        # 机构评级
  age: 0.02           # 基金年龄
```

--------------------------------

### Run Full Update Process with Shell

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

This shell script automates the execution of the complete update process. It is suitable for automated tasks requiring a one-click execution of the entire update flow.

```bash
bash src/scripts/update/run_update.sh
```

--------------------------------

### Configure Recommendation Weights in YAML

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Set recommendation weights by editing the `fundseeker/config.yaml` file. This method allows for fine-grained control over various factors influencing fund recommendations.

```yaml
recommendation_weights:
  recent: 0.35        # Recent momentum
  mid: 0.20           # Mid-term trend
  long: 0.15          # Long-term stability
  risk_penalty: 0.10  # Volatility penalty
  manager: 0.10       # Manager performance
  scale: 0.05         # Fund size
  rating: 0.30        # Agency ratings
  age: 0.02           # Fund age
```

--------------------------------

### Commit Changes

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Stage all changes and commit them with a descriptive message following the specified convention.

```bash
git add .
git commit -m "feat: add new feature description"
```

--------------------------------

### Generate Advanced Recommendations

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Generate recommendations using the configured advanced model. Specify the mode as 'advanced' and the variant label defined in the configuration.

```bash
cd ../fundseeker
./fundseeker.sh recommend --mode advanced --adv-variant 6m
```

--------------------------------

### Download Historical NAV Data

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Download historical Net Asset Value (NAV) time series data for funds listed in `data/fund_list.csv`. This is a crucial step for feature engineering.

```bash
./fundseeker.sh nav
```

--------------------------------

### Fetch Fund Details

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Retrieve detailed information for a list of funds specified in an input CSV file. This command requires the `--input` argument to point to the fund list.

```bash
./fundseeker.sh details --input data/fund_list.csv
```

--------------------------------

### Check Fund Data Status with Python

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

Use this script to check the latest NAV data date for each fund before initiating an update. It helps in understanding the current data status and identifying which funds require updates.

```bash
.venv/bin/python src/scripts/update/check_dates.py
```

--------------------------------

### Rollback Method 2: Manually Move Files Back

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/WORKFLOW_GUIDE.md

Manually move script files back to their original locations within the fund_reco_fit directory. This is an alternative to restoring from a backup.

```bash
# Method 2: Manually move back to original location
cd fund_reco_fit
mv src/scripts/train.py auto_tune_top200.py
mv src/scripts/predict.py predict_2026.py
# ... other files ...
```

--------------------------------

### Configure Advanced Model in FundSeeker

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Configure the FundSeeker CLI to use the advanced machine learning model. This involves editing the `config.yaml` file to specify the model's database, feature table, and weights path.

```yaml
advanced_model:
  - label: 6m
    db_path: ../fund_reco_fit/data/fundseeker_nav.db
    feature_table: features_M_star
    weights_path: ../fund_reco_fit/models/model_params_6m.json
    top_k: 200
```

--------------------------------

### Build Features for Model Training

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Construct features from the NAV data stored in the SQLite database. This command calculates rolling indicators over a specified frequency (`--freq`).

```python
python3 -m src.feature_builder \
  --database data/fundseeker_nav.db \
  --freq M \
  --table-name features_M_star
```

--------------------------------

### Smart Incremental Fund Data Update with Python

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

This is the recommended core tool for generating grouped batch update files. It automatically detects the latest data date for each fund, groups them by date, and creates CSV files for batch updates, simplifying the update process.

```bash
.venv/bin/python src/scripts/update/smart_update.py
```

--------------------------------

### Simplified Fund Data Update with Shell

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

A simplified update script for quickly updating a small number of funds or testing the update process. It is less comprehensive than the standard update flow.

```bash
bash src/scripts/update/simple_update.sh
```

--------------------------------

### Quick Data Validation with Shell

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

This script performs a quick validation of data integrity after an update. It is useful for a rapid check to ensure data is normal and the database connection is sound.

```bash
bash src/scripts/update/quick_validate.sh
```

--------------------------------

### Create Feature Branch

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Always create a new branch for your feature or bug fix. Do not work directly on the main branch.

```bash
# 创建并切换到新分支
git checkout -b feature/your-feature-name

# 或者修复 bug
git checkout -b fix/bug-description
```

--------------------------------

### Check Data Update Progress with Shell

Source: https://github.com/yuna78/fundseeker/blob/main/doc/fund_reco_fit/UPDATE_SCRIPTS_GUIDE.md

Use this shell script to monitor the progress of long-running data download or processing tasks. It is useful for checking the status of background jobs.

```bash
bash src/scripts/update/check_progress.sh
```

--------------------------------

### Train Factor Model

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Train a factor model using the constructed features. This involves specifying the database, feature table, date ranges for snapshots, future horizon, and output format.

```python
python3 -m src.optimizer \
  --database data/fundseeker_nav.db \
  --feature-table features_M_star \
  --snapshot-start 2020-01-01 \
  --snapshot-end 2024-12-31 \
  --future-horizon 6 \
  --top-k 200 \
  --output-json models/model_params_6m.json
```

--------------------------------

### Check Code Style with Flake8

Source: https://github.com/yuna78/fundseeker/blob/main/CONTRIBUTING.md

Use flake8 to check Python code style compliance in the src directory.

```bash
# 如果安装了 flake8
flake8 src/
```

--------------------------------

### Progress Tracking JSON Structure

Source: https://github.com/yuna78/fundseeker/blob/main/CLAUDE.md

This JSON structure is used to save and load progress for long-running tasks. Services check for existing progress files and resume from 'last_index + 1' unless '--no-resume' is passed.

```json
{
  "total": 10000,
  "processed": 2500,
  "last_index": 2499,
  "start_time": "2024-12-14T10:30:00",
  "last_update": "2024-12-14T11:45:00"
}
```

--------------------------------

### Validate Model (Optional)

Source: https://github.com/yuna78/fundseeker/blob/main/README.md

Perform model validation to check for overfitting. This can be done using rolling window validation or by testing against future real data.

```bash
./quick_validate.sh
```

--------------------------------

### Deactivate Virtual Environment

Source: https://github.com/yuna78/fundseeker/blob/main/fundseeker/user_manual.md

Command to exit the Python virtual environment after completing FundSeeker operations.

```bash
deactivate
```
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