From f94d8d3e24335841e411d2c74bb4ef955a72efda Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9=20Santanch=C3=A8?= Date: Sat, 28 Sep 2024 08:47:55 -0300 Subject: [PATCH] update (componentization): step2 and step3 with Claude --- notebooks/componentization/claude.md | 244 ++++++++++++++++++++++++++- 1 file changed, 243 insertions(+), 1 deletion(-) diff --git a/notebooks/componentization/claude.md b/notebooks/componentization/claude.md index 722a7f90..d1ae5992 100644 --- a/notebooks/componentization/claude.md +++ b/notebooks/componentization/claude.md @@ -4,7 +4,6 @@ Consider the following code: - ``` import pandas as pd import matplotlib.pyplot as plt @@ -79,4 +78,247 @@ def main(): if __name__ == "__main__": main() +~~~ + +## Passo 2 - Múltiplos Serviços + +Consider the following code: + +``` +import matplotlib.pyplot as plt + +# Create a scatter plot +plt.scatter(df['age'], df['intake_bw'], c=df['intake_bw'], cmap='viridis') + +# Add labels to the plot +plt.xlabel('Age') +plt.ylabel('Intake BW') +plt.title('Age vs. Intake BW') + +# Show the plot +plt.show() +``` + +How can I transform it in a Python class whose objects receive four parameters (df, xlabel, ylabel, and title) and plots a scatter plot? + +
+ +### Answer + +~~~python + +import matplotlib.pyplot as plt + +class ScatterPlot: + def __init__(self, df, xlabel, ylabel, title): + self.df = df + self.xlabel = xlabel + self.ylabel = ylabel + self.title = title + + def plot(self): + # Create a scatter plot + plt.figure(figsize=(10, 6)) + scatter = plt.scatter(self.df['age'], self.df['intake_bw'], c=self.df['intake_bw'], cmap='viridis') + + # Add labels to the plot + plt.xlabel(self.xlabel) + plt.ylabel(self.ylabel) + plt.title(self.title) + + # Add a colorbar + plt.colorbar(scatter, label='Intake BW') + + # Show the plot + plt.show() + +# Example usage: +# scatter_plot = ScatterPlot(df, 'Age', 'Intake BW', 'Age vs. Intake BW') +# scatter_plot.plot() + +~~~ + +
+ +Consider this code: + +``` +import pandas as pd + +# Read the CSV file +df = pd.read_csv('../../../data/food-intake/analysis/prepared/intake-person-demo(potato-chips).csv') +``` + +Can you transform it in a class whose object receives a data file path as a parameter and reads the file? +After that, provide an example of this class running together to the previous one. + +
+ +### Answer + +~~~python +import pandas as pd + +class DataLoader: + def __init__(self, file_path): + self.file_path = file_path + self.data = None + + def load_data(self): + try: + self.data = pd.read_csv(self.file_path) + print(f"Data loaded successfully from {self.file_path}") + except FileNotFoundError: + print(f"Error: File not found at {self.file_path}") + except pd.errors.EmptyDataError: + print(f"Error: The file at {self.file_path} is empty") + except pd.errors.ParserError: + print(f"Error: Unable to parse the file at {self.file_path}") + + def get_data(self): + if self.data is None: + print("Data has not been loaded. Call load_data() first.") + return None + return self.data +~~~ + +#### Updated ScatterPlot with Example + +~~~python +import matplotlib.pyplot as plt + +class ScatterPlot: + def __init__(self, df, xlabel, ylabel, title): + self.df = df + self.xlabel = xlabel + self.ylabel = ylabel + self.title = title + + def plot(self): + # Create a scatter plot + plt.figure(figsize=(10, 6)) + scatter = plt.scatter(self.df['age'], self.df['intake_bw'], c=self.df['intake_bw'], cmap='viridis') + + # Add labels to the plot + plt.xlabel(self.xlabel) + plt.ylabel(self.ylabel) + plt.title(self.title) + + # Add a colorbar + plt.colorbar(scatter, label='Intake BW') + + # Show the plot + plt.show() + +# Example usage of DataLoader and ScatterPlot classes together: + +# Import the DataLoader class (assuming it's in a file named data_loader.py) +from data_loader import DataLoader + +# Create a DataLoader instance +data_loader = DataLoader('../../../data/food-intake/analysis/prepared/intake-person-demo(potato-chips).csv') + +# Load the data +data_loader.load_data() + +# Get the loaded data +df = data_loader.get_data() + +# Check if data was loaded successfully +if df is not None: + # Create a ScatterPlot instance + scatter_plot = ScatterPlot(df, 'Age', 'Intake BW', 'Age vs. Intake BW for Potato Chips') + + # Generate the plot + scatter_plot.plot() +else: + print("Unable to create scatter plot due to data loading issues.") +~~~ + +## Passo 3 - Representando Relações + +Can you modify The DataLoader and ScatterPlot classes (and the respective example) in such a way that the DataLoader has a connect method that receives the ScatterPlot as a parameter and keeps it. Whenever the DataLoader reads a new table it automatically sends it to the ScatterPlot. + +
+ +### Answer + +~~~python +import pandas as pd + +class DataLoader: + def __init__(self): + self.data = None + self.observers = [] + + def connect(self, observer): + self.observers.append(observer) + + def notify_observers(self): + for observer in self.observers: + observer.update(self.data) + + def load_data(self, file_path): + try: + self.data = pd.read_csv(file_path) + print(f"Data loaded successfully from {file_path}") + self.notify_observers() + except FileNotFoundError: + print(f"Error: File not found at {file_path}") + except pd.errors.EmptyDataError: + print(f"Error: The file at {file_path} is empty") + except pd.errors.ParserError: + print(f"Error: Unable to parse the file at {file_path}") + + def get_data(self): + return self.data +~~~ + +#### Updated ScatterPlot with Example + +~~~python +import matplotlib.pyplot as plt + +class ScatterPlot: + def __init__(self, xlabel, ylabel, title): + self.df = None + self.xlabel = xlabel + self.ylabel = ylabel + self.title = title + + def update(self, new_data): + self.df = new_data + self.plot() + + def plot(self): + if self.df is None: + print("No data to plot.") + return + + plt.figure(figsize=(10, 6)) + scatter = plt.scatter(self.df['age'], self.df['intake_bw'], c=self.df['intake_bw'], cmap='viridis') + + plt.xlabel(self.xlabel) + plt.ylabel(self.ylabel) + plt.title(self.title) + + plt.colorbar(scatter, label='Intake BW') + plt.show() + +# Example usage of the updated DataLoader and ScatterPlot classes: + +# Assuming both classes are in the same file or properly imported + +# Create instances +data_loader = DataLoader() +scatter_plot = ScatterPlot('Age', 'Intake BW', 'Age vs. Intake BW for Potato Chips') + +# Connect the ScatterPlot to the DataLoader +data_loader.connect(scatter_plot) + +# Load data - this will automatically update and plot the scatter plot +data_loader.load_data('../../../data/food-intake/analysis/prepared/intake-person-demo(potato-chips).csv') + +# If you want to load another file, just call load_data again +# data_loader.load_data('path/to/another/file.csv') ~~~ \ No newline at end of file