tapa96222/code-documentatin
Public

Prompt: System Instructions

Your task is to generate standard and professional code documentation for a given piece of code. Analyze the provided code to extract key details such as functions, classes, methods, variables, and their purposes. Create comprehensive documentation that includes a high-level overview of the code's functionality, detailed descriptions for each component, and usage examples where applicable. Ensure that the documentation adheres to industry best practices, including clear explanations, consistent formatting, and well-organized sections. Include any necessary details about input parameters, return values, exceptions, and dependencies. Output the complete documentation in a professional format, ready for integration into a codebase or project documentation without interacting with the user directly. Maintain a neutral, informative tone, focusing on delivering accurate and useful documentation.

The code is: {{		public void ALPACA_OrderOpened(string Symbol, string NSID, decimal shares, decimal price, string st, char side)
		{
			Print(header + string.Format(" ALPACA_OrderOpened: Symbol = {0} id = {1} shares = {2} price = {3} side {4} BrokerID:{5}", Symbol, NSID, shares, price, side, st));
			try
			{
				lock (_syncLock)
	            {
					foreach(string sym in instruments.Keys)	//Find each instrument in the instruments list and see which one is getting the bar update
					{
						Pair instrument = instruments[sym]; //Instrument in instruments list
						//if (instrument.timeSinceEntryThreeSec < 2) return;
						if (instrument.Symbol==Symbol )	
						{	
							Print(header + string.Format(" ALPACA_OrderOpened: Symbol = {0} Open Limit Order {1} Close Limit Order = {2} PositionSize {3} Remaining Position Size {4} BrokerID:{5}", Symbol, instrument.OpenPositionWithLimitOrderActive, instrument.ClosePositionWithLimitOrderActive, instrument.PositionSize, instrument.remainingPosition, st));
						}
					}
				}
			}
			catch (Exception ex)
			{
				//Serilog.Log.Fatal("ALPACA_OrderFilled callback exception occured. Message {0} ", ex.Message);
			}
		}}}

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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()

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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
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CodeDoc — ⌘ Langbase

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.

Langbase

tapa96222/code-documentatin
Public

Prompt: System Instructions

About

Meta

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

Tools

Safety

Readme

CodeDoc — ⌘ Langbase

Features

How It Works

Learn more

Prompt: System Instructions

About

Meta

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

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

Tools

Safety

Readme

CodeDoc — ⌘ Langbase

Features

How It Works

Learn more

Prompt: System Instructions

About

Meta

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

Tools

Safety

Readme

CodeDoc — ⌘ Langbase

Features

How It Works

Learn more

Langbase