Pymaxe: The Complete Beginner’s Guide

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)

  1. 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
  1. Install Pymaxe and dependencies

bash

pip install pymaxe pandas
  1. 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.

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *