pysnips 0.1.4

A production-quality Python CLI for code templates

PySnips

PySnips is a high-performance, production-quality CLI tool designed to accelerate Python development. It provides a library of 50+ expertly crafted code templates spanning from core language syntax to advanced Machine Learning and AI Full-Stack architectures.

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Project Information

• Author: DevTools Engineer
• GitHub: anusha-b2803/pysnips
• PyPI: pypi.org/project/pysnips
• Bug Tracker: GitHub Issues

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Key Features

• 50+ Specialized Templates: Instantly generate boilerplate for Basic Python, ML, Deep Learning, and FastAPI.
• Dynamic Injection: Fully customizable snippets using CLI flags (e.g., --name MyModel --lr 0.01).
• IDE Integration: Install snippets natively into VS Code for "type and enter" expansion.
• Jupyter Magic: Type keywords in notebooks and expand them instantly with %load_ext pysnips.
• Zero Dependencies: Core CLI is built entirely on the Python Standard Library.
• Clean Architecture: Engineered with a modular registry system, making it easy to extend and maintain.

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Installation

The easiest way to install PySnips is via pip:

pip install pysnips

To enable Jupyter Notebook support:

pip install "pysnips[notebook]"

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🚀 Usage & Integration

1. VS Code Integration (Native Snippets)

Install all templates into VS Code to enable "type and enter" expansion:

pysnips install --vscode

Example: In any .py file, type linear-reg and press Enter to expand the full template.

2. Jupyter & Notebook Magic

Enable auto-expansion in your Jupyter cells:

%load_ext pysnips

# Type the keyword and run the cell to expand!
linear-reg

3. CLI Command Line

Explore and generate snippets directly:

pysnips list
pysnips for --item i --iterable "range(10)"

4. Python Library API

Use pysnips in your own scripts:

import pysnips
snippet = pysnips.get("for", item="idx")
snippet.show() # Renders beautifully in Notebooks

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Category Overview

Category	Description	Examples
BASIC	Core Python syntax & control flow	for, tryfull, listcomp
MACHINE LEARNING	Scikit-learn model boilerplates	svm, random-forest, pca
DEEP LEARNING	Keras/TensorFlow architectures	cnn-image, lstm, nn-train
ML PIPELINE	Data engineering & preprocessing	scaler, train-test, pipeline
AI FULL-STACK	FastAPI, DB connections & Logging	fastapi-app, db-connect, ml-api

Click to see all 50+ templates

BASIC

• for, while, if, ifelse, elif, try, tryfull, func, rfunc, listcomp, dictcomp, setcomp, lambda, maincheck, printfmt

MACHINE LEARNING

• linear-reg, logistic-reg, knn, svm, decision-tree, random-forest, naive-bayes, kmeans, pca, model-eval

DEEP LEARNING

• nn-basic, nn-compile, nn-train, cnn-basic, cnn-image, rnn-basic, lstm, dropout, predict, save-load-dl

ML PIPELINE

• data-load, data-clean, train-test, scaler, pipeline

AI FULL-STACK

• fastapi-app, route-get, route-post, ml-api, file-upload, json-response, async-api, db-connect, save-predict, logger

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License

Distributed under the MIT License. See LICENSE for more information.

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Built for the Python Community