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""" | |
File Name: bot_sap_to_duckdb.py | |
Author: | |
Date: 17-FEB-2025 | |
Description: This script fetches SAP Partner Finder data via API, | |
processes it, and loads it into a database using the DLT pipeline. | |
Python Environment Setup: | |
1. Create a virtual environment: | |
- For Unix/Linux/Mac: `python3 -m venv env` |
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generator client { | |
provider = "prisma-client-js" | |
} | |
datasource db { | |
provider = "postgresql" | |
url = env("DATABASE_URL") | |
} | |
enum UserType { |
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title: PII Processing and Anonymization Workflow | |
description: A pipeline for detecting, anonymizing, enriching, and de-anonymizing sensitive PII text | |
nodes: | |
- id: input01 | |
name: Input | |
description: Text containing sensitive PII | |
icon: mdi:file-document | |
color: bg-pink-400 | |
show_annotation: false | |
- id: pii_detection |
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title: Notification Workflow Pipeline | |
description: ETL pipeline for processing and routing notifications through EventBridge and AWS Lambda | |
nodes: | |
- id: app-db | |
name: App DB | |
description: Smart Data Partner and source for events | |
icon: mdi:database-cog | |
color: bg-blue-500 | |
show_annotation: false | |
- id: eventbridge01 |
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<div tw="flex flex-col justify-between w-full h-full bg-cover bg-center p-10 box-border font-sans text-white bg-indigo-600"> | |
<div tw="flex flex-row items-start justify-start"> | |
<img src="https://res.cloudinary.com/nathansweb/image/upload/v1727025413/senthilsweb.com/avatars/senthil-face-photo-sep-2024.png" alt="Profile" tw="w-[150px] h-[150px] mr-5 mt-8 rounded-2xl" /> | |
<div tw="flex flex-col items-start"> | |
<h1 tw="text-4xl mb-2">Senthilnathan Karuppaiah</h1> | |
<p tw="text-xl my-1">Software Engineer</p> | |
<p tw="text-xl my-1 flex items-center">123-456-7890</p> | |
<p tw="text-xl my-1 flex items-center">sk@example.com</p> | |
<p tw="text-xl my-1 flex items-center">www.senthilsweb.com</p> | |
</div> |
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{ | |
"contentType": "application/vnd.gorules.decision", | |
"edges": [ | |
{ | |
"id": "1dfbc57d-ad1f-4cf8-978a-e43241856fc8", | |
"type": "edge", | |
"sourceId": "be0a5c2d-538d-4e50-9843-91b274e1b9d8", | |
"targetId": "7c07550a-07bc-4ee4-80d6-9ad900e3d6c9" | |
}, | |
{ |
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""" | |
File Name: bot_jira_to_duckdb.py | |
Author: Senthilnathan Karuppaiah | |
Date: 22-FEB-2024 | |
Description: This script fetches JIRA issue data in CSV format based on a specified JQL query, | |
parses it, and loads it into a database using the DLT pipeline. | |
Python Environment Setup (replace `env` with your desired environment name): | |
1. Create a virtual environment: | |
- For Unix/Linux/Mac: `python3 -m venv env` |
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<div class="absolute inset-0 -z-10 mx-0 max-w-none overflow-hidden"> | |
<div class="absolute left-1/2 top-0 ml-[-38rem] h-[25rem] w-[81.25rem] dark:[mask-image:linear-gradient(white,transparent)]"> | |
<div class="absolute inset-0 bg-gradient-to-r from-[#ec4899] to-[#fbcfe8] opacity-40 [mask-image:radial-gradient(farthest-side_at_top,white,transparent)] dark:from-[#ec4899]/30 dark:to-[#fbcfe8]/30 dark:opacity-100"> | |
<svg aria-hidden="true" class="dark:fill-white/2.5 absolute inset-x-0 inset-y-[-50%] h-[200%] w-full skew-y-[-18deg] fill-black/40 stroke-black/50 mix-blend-overlay dark:stroke-white/5"> | |
<defs> | |
<pattern id=":S1:" width="72" height="56" patternUnits="userSpaceOnUse" x="-12" y="4"><path d="M.5 56V.5H72" fill="none"></path></pattern> | |
</defs> | |
<rect width="100%" height="100%" stroke-width="0" fill="url(#:S1:)"></rect> | |
<svg x="-12" y="4" class="overflow-visible"> | |
<rect stroke-width="0" width="73" height="57" x="288" y="168"></rect> |
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