A repository for managing and automating tasks related to the Symbiant project, including code, scripts, and The Symbiant-Automation repository is a comprehensive collection of scripts and tools designed to automate various tasks related to the Symbiant project. It includes modules for data processing, report generation, API interactions, and task scheduling. The repository aims to streamline workflows and improve efficiency by automating repetitive tasks.documentation.

The Symbiant-Automation repository is designed to streamline and automate various tasks related to the Symbiant project. It includes a collection of scripts, modules, and tools that facilitate automation, data processing, and report generation.

To get started with this repository, follow these steps:

1. Clone the repository:

   git clone https://github.com/SymbiantZyB/symbiant-automation.git

2. Navigate to the repository directory:

   cd symbiant-automation

3. Install the required dependencies:

   pip install -r requirements.txt

The repository includes a command-line interface (CLI) for running automation tasks. Here are some examples of how to use the CLI:

To display the version of the CLI tool, run:

python cli.py --version

The api_client.py module provides a simple interface for making API requests. Here's an example of how to use it:

from api_client import APIClient

# Initialize the API client with the base URL and API key
client = APIClient(base_url="https://api.example.com", api_key="your_api_key")

# Make a GET request to the "status" endpoint
response = client.get("status")

# Print the response
print(response)

The data_processor.py module provides functionality for data cleaning and transformation. Here's an example of how to use it:

import pandas as pd
from data_processor import DataProcessor

# Create a sample DataFrame
sample_data = pd.DataFrame({'col1': [1, 2, None, 4], 'col2': ['A', 'B', 'B', None]})

# Initialize the DataProcessor
processor = DataProcessor()

# Clean the data
cleaned_data = processor.clean_data(sample_data)

# Print the cleaned data
print(cleaned_data)

The report_generator.py module allows for generating structured reports. Here's an example of how to use it:

from report_generator import ReportGenerator

# Initialize the ReportGenerator with a title
report = ReportGenerator(title="Automation Report")

# Add a section to the report
report.add_section(heading="Introduction", content="This is a sample report section.")

# Save the report to a PDF file
report.save_report(filename="example_report.pdf")

To run a specific task, use the -t or --task option:

python cli.py -t example

Replace example with the name of the task you want to run.