Pynions is a lean Python framework for building AI-powered automation flows that run on your machine.
git clone https://github.com/craftled/pynions.gitPynions is a lean Python framework for building AI-powered automation flows that run on your machine.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/craftled/pynionsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a Pynions automation flow for [COMPANY] in the [INDUSTRY] sector. The flow should process [DATA] and perform the following tasks: [TASK1], [TASK2], and [TASK3]. Include error handling and logging for each step. Provide the complete Python code for the flow.
# Pynions Automation Flow for GreenTech Solutions
## Overview
This automation flow processes customer data for GreenTech Solutions, a renewable energy company. The flow performs the following tasks:
- Data validation
- Customer segmentation
- Email campaign preparation
## Code
```python
import pynions as pn
# Initialize the flow
flow = pn.Flow(name='GreenTech_Customer_Automation')
# Step 1: Data Validation
validate_data = pn.Task(
name='Validate_Customer_Data',
function=validate_customer_data,
inputs={'data': 'customer_data.csv'},
error_handler=handle_validation_error,
logger=pn.Logger(level='INFO')
)
flow.add_task(validate_data)
# Step 2: Customer Segmentation
segment_customers = pn.Task(
name='Segment_Customers',
function=segment_customers_by_usage,
inputs={'validated_data': validate_data.outputs['validated_data']},
error_handler=handle_segmentation_error,
logger=pn.Logger(level='INFO')
)
flow.add_task(segment_customers)
# Step 3: Email Campaign Preparation
prepare_emails = pn.Task(
name='Prepare_Email_Campaign',
function=prepare_segmented_email_campaign,
inputs={'segmented_data': segment_customers.outputs['segmented_data']},
error_handler=handle_email_preparation_error,
logger=pn.Logger(level='INFO')
)
flow.add_task(prepare_emails)
# Run the flow
flow.run()
```
## Error Handling
- Validation errors are logged and the flow stops if critical data is missing.
- Segmentation errors are logged and the flow continues with partial data.
- Email preparation errors are logged and the flow completes without sending emails.
## Logging
- All steps log their start and completion times.
- Errors are logged with timestamps and descriptions.Take a free 3-minute scan and get personalized AI skill recommendations.
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