How to Build Your First Project with Pymaxe
1. Project overview
- Goal: Create a small CLI tool that processes CSV data and outputs summary statistics (row count, column means, missing values).
- Assumption: Pymaxe is a Python framework installed via pip and provides project scaffolding, CLI helpers, and data utilities.
2. Prerequisites
- Python 3.10+ installed
- pip available
- Terminal/command line access
3. Setup (commands)
- Create project directory and virtual environment
bash
mkdir pymaxe-csv-tool cd pymaxe-csv-tool python -m venv venv source venv/bin/activate# use venv\Scripts\activate on Windows
- Install Pymaxe and dependencies
bash
pip install pymaxe pandas
- Initialize Pymaxe project scaffold
bash
pymaxe init –name pymaxe-csv-tool
4. Project structure (example)
- pymaxe-csv-tool/
- pymaxeconfig.yml
- src/
- main.py
- cli.py
- processor.py
- tests/
- README.md
5. Implement CLI (src/cli.py)
python
from pymaxe import CLI # assumed helper from .processor import summarize_csv cli = CLI(name=“pymaxe-csv-tool”) @cli.command() def summarize(path: str): ”““Summarize CSV file at path”“” summary = summarizecsv(path) for k, v in summary.items(): print(f”{k}: {v}“)
6. Implement processor (src/processor.py)
python
import pandas as pd def summarize_csv(path: str) -> dict: df = pd.read_csv(path) summary = { “rows”: len(df), “columns”: len(df.columns), “missing_values”: int(df.isna().sum().sum()) } # compute numeric column means numeric = df.select_dtypes(“number”) means = numeric.mean().todict() summary[“means”] = {k: float(v) for k, v in means.items()} return summary
7. Main entry (src/main.py)
python
from .cli import cli def main(): cli.run() if name == “main”: main()
8. Run & test
- Run the CLI:
bash
python -m src.main summarize data/sample.csv
- Add a quick test (tests/testprocessor.py) using pytest:
python
from src.processor import summarize_csv def test_summarize(tmp_path): p = tmp_path / “t.csv” p.write_text(“a,b\n1,2\n3,”) summary = summarizecsv(str(p)) assert summary[“rows”] == 2 assert “a” in summary[“means”]
Run:
bash
pip install pytest pytest
9. Packaging & distribution
- Add pymaxeconfig.yml and setup a console script entrypoint in setup.cfg or pyproject.toml to publish as a pip package.
- Example pyproject.toml entrypoint:
toml
[project.scripts] pymaxe-csv-tool = “src.main:main”
10. Next steps / improvements
- Add options for output format (JSON, CSV).
- Support large files with chunked processing.
- Add logging and configurable thresholds.
- Integrate Pymaxe testing/CI features (if available).
If you want, I can generate the full scaffold files for you.
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