checkemotion 0.2.2

Assign emotional personalities to Python functions via AST + runtime analysis

emotion

Give your Python functions feelings.
A Python decorator that assigns emotional personalities to functions based on code structure and runtime behaviour.

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What It Does

Feature	Description
🎭 Emotion assignment	Each function gets an emotion based on its code structure: complexity, keywords, recursion, async, error-handling, etc.
🌈 Rich colorful CLI	Every call prints ANSI 256-color output: emotion chip, intensity bar, valence badge, wall time, CPU time, memory, error count
💬 Inter-function conversation	When two conversation=True functions run concurrently, they talk to each other in the terminal
🔄 Emotion drift	Emotions evolve every 10 calls based on error rate, latency, and frequency
🤝 Social relationships	Functions develop feelings toward each other: friendship, jealousy, respect, anger, pity…
🔬 Deep profiling	Wall time, CPU time, heap delta, heap peak via tracemalloc — O(1) overhead per call
🕸️ Call graph	Static AST scan builds a project-wide call graph; see who calls whom

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Quick Demo

from checkemotion import emotion

@emotion
def calculate_total(numbers: list) -> float:
    return sum(n for n in numbers if n > 0)

@emotion(conversation=True)
def validate_user(user_id: int, role: str) -> bool:
    try:
        assert user_id > 0
        assert role.strip()
        return True
    except AssertionError:
        return False

calculate_total([1, 2, 3, 4, 5])
validate_user(42, "admin")

Terminal output:

  😊  calculate_total  ▸  glad  [joy]  ░····  ▲ +
    ▸ awakened  Sums positive numbers and returns the total.

  │ ✓ done  😊 calculate_total  #1  ⏱ 0.1ms  cpu 0.01ms  mem +0.0KB  cc=2  err=0

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Installation

pip install checkemotion

Or clone and run directly:

git clone https://github.com/itsmohitrohilla/emotion.git
cd emotion
python examples/quickstart.py

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The @emotion Decorator

# Bare — simplest form
@emotion
def my_function(x):
    return x * 2

# With options
@emotion(enabled=True, conversation=True, verbose=True)
def my_function(x):
    return x * 2

Option	Default	Description
enabled	True	False → zero overhead, function unchanged
conversation	False	Functions talk to each other when running concurrently
verbose	True	False → silent mode, metrics still collected

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Public API

from checkemotion import (
    emotion,              # decorator
    build_report,         # build_report(name) → FunctionReport
    all_reports,          # all_reports(sort_by="call_count") → list
    describe,             # describe(func) → one-line string
    callers_of,           # callers_of(name) → list of caller names
    callees_of,           # callees_of(name) → list of callee names
    scan_directory,       # scan_directory(path) → build call graph
    get_all_names,        # list of all registered function names
    get_data,             # get_data(name) → raw registry dict
)

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Requirements

• Python 3.11+
• Zero external dependencies — pure stdlib
• Optional: Ollama with phi3.5:mini for AI-generated descriptions