examples/code-doc
Public

Prompt: System Instructions

Fork the Pipe — to testit in the playground here

About

This pipe expertly creates comprehensive and professional code documentation, offering detailed descriptions for functions, classes, methods, and variables. It provides a high-level overview and clear usage examples, ensuring that your code is well-documented and easy to understand. Ideal for maintaining clarity and consistency in complex codebases.

Variables

import numpy as np
import pandas as pd

class TimeSeriesAnalyzer:
    def __init__(self, data: pd.DataFrame):
        self.data = data
        self.validate_data()

def validate_data(self):
        if 'timestamp' not in self.data.columns or 'value' not in self.data.columns:
            raise ValueError("DataFrame must contain 'timestamp' and 'value' columns.")
        self.data['timestamp'] = pd.to_datetime(self.data['timestamp'])
        self.data.sort_values('timestamp', inplace=True)

def moving_average(self, window: int) -> pd.Series:
        return self.data['value'].rolling(window=window).mean()

def seasonal_decompose(self, period: int):
        from statsmodels.tsa.seasonal import seasonal_decompose
        ts = self.data.set_index('timestamp')
        decomposition = seasonal_decompose(ts['value'], period=period)
        return decomposition

def forecast(self, periods: int) -> pd.Series:
        from statsmodels.tsa.holtwinters import ExponentialSmoothing
        model = ExponentialSmoothing(self.data['value'], seasonal='add', seasonal_periods=periods)
        fit = model.fit()
        forecast = fit.forecast(periods)
        return forecast

def plot(self):
        import matplotlib.pyplot as plt
        plt.figure(figsize=(10, 6))
        plt.plot(self.data['timestamp'], self.data['value'], label='Original')
        plt.title('Time Series Data')
        plt.xlabel('Timestamp')
        plt.ylabel('Value')
        plt.legend()
        plt.show()

# Example usage
if __name__ == "__main__":
    # Simulated data
    dates = pd.date_range(start='2023-01-01', periods=100, freq='D')
    values = np.random.randn(100).cumsum()
    df = pd.DataFrame({'timestamp': dates, 'value': values})

analyzer = TimeSeriesAnalyzer(df)
    print(analyzer.moving_average(window=7))
    print(analyzer.seasonal_decompose(period=12).seasonal)
    print(analyzer.forecast(periods=10))
    analyzer.plot()

Tools

No tools added to the Pipe.

Safety

Readme

CodeDoc — ⌘ Langbase

The CodeDoc is a robust pipe designed to create comprehensive and well-structured documentation for your code. By analyzing your code, it produces detailed descriptions for functions, classes, methods, and variables, ensuring clarity and consistency. This tool is essential for maintaining high-quality documentation in complex codebases, making it easier for developers to understand and maintain the code.

Features

Detailed Descriptions: Provides in-depth explanations for each component of the code, including functions, classes, methods, and variables.
High-Level Overview: Summarizes the overall functionality and purpose of the code.
Usage Examples: Includes clear examples of how to use each component.
Consistent Formatting: Adheres to industry best practices for documentation, ensuring clarity and readability.
Input/Output Details: Documents input parameters, return values, exceptions, and dependencies.

How It Works

Enter Input: Submit the code snippet or the complete codebase that you need documented. The tool will analyze the code to identify key components and their roles.
Generate Output: The pipe will produce a detailed and professionally formatted documentation output. This includes an overview of the code, descriptions for each function, class, method, and variable, usage examples, and other relevant details. The output is ready for integration into your project documentation.

Learn more

Check the CodeDoc Pipe on ⌘ Langbase
Go through Documentation: Pipe Quick Start
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Langbase

examples/code-doc
Public

Prompt: System Instructions

About

Meta

Type

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

Tools

Safety

Readme

CodeDoc — ⌘ Langbase

Features

How It Works

Learn more

⌘Langbase

Prompt: System Instructions

About

Meta

Type

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

Tools

Safety

Readme

CodeDoc — ⌘ Langbase

Features

How It Works

Learn more

Langbase