🤖 Job_Bot

An end-to-end RPA bot that scrapes, structures, filters & emails job-market data — fully hands-free

Driving Chrome across five major job portals to turn hours of manual research into a one-click, automated report.

🎯 The Problem It Solves

Searching job portals by hand is slow, repetitive, and error-prone — open a site, run a search, click each listing, copy the salary, benefits, and requirements, paste them into a spreadsheet, repeat. Job_Bot does all of it automatically.

It drives a real Chrome browser through five popular job sites — LinkedIn, Indeed, Glassdoor, Monster, and SimplyHired — reads each posting, extracts the details that matter, lets you filter the results by keyword, exports everything to Excel, and emails you the finished report. No manual copy-pasting, no missed listings.

🌟 Highlights

🔎 5 job portals automated	LinkedIn · Indeed · Glassdoor · Monster · SimplyHired
🧩 Structured extraction	Parses raw postings into 7 clean fields (compensation, benefits, experience, responsibilities, qualifications, schedule, requirements)
🎛️ Interactive filtering	Filter results by any column + keyword at runtime — no code edits
📊 Excel reporting	Auto-writes results and filtered copies to spreadsheets
📧 Automated email delivery	Sends the final report over SMTP to any recipient
♻️ Modular & reusable	Shared sub-workflows for extraction & filtering, reused across every scraper
🛡️ Resilient	Try/Catch + app-state checks survive slow loads, pop-ups & layout quirks

✨ Features & Functionalities

• Multi-portal job scraping — Dedicated workflows scrape listings from LinkedIn, Indeed, Glassdoor, Monster, and SimplyHired.
• Structured data extraction — A reusable Data_Extraction workflow parses each raw job-detail blob into clean fields: compensation, benefits, experience, responsibilities, qualifications, schedule, and requirements.
• Personal & organization data collection — Personal.xaml and Organization.xaml gather employee-level and company-level records (name, address, job title, industry, company name, employment status, and more).
• Excel export — Collected data is written to workbooks (Employee_Data.xlsx, Employment.xlsx) via Write Range.
• Interactive keyword filtering — Data_Filtering prompts the user to choose a filter column and enter a keyword, then removes non-matching rows and saves a filtered copy (Filtered_Employee_Data.xlsx, Filtered_Employment.xlsx).
• Automated email delivery — Results are emailed to a user-supplied address via SMTP.
• Resilient navigation — Try/Catch blocks and Check App State / Target appears checks handle pages that load slowly or differ between listings.

🛠️ Tech Stack

Area	Technology
Automation platform	UiPath Studio 21.10 (Workflow / .xaml)
Runtime	.NET Framework (Legacy profile)
Expression language	VB.NET
Web / UI automation	UiPath.UIAutomation.Activities — Chrome automation, selectors, Extract Table Data, Check App State
Spreadsheets	UiPath.Excel.Activities — Read/Write Range
Email	UiPath.Mail.Activities — Send SMTP Mail Message
Core logic	UiPath.System.Activities — control flow, assigns, input dialogs
Version control	Git / GitHub

🏗️ How It's Built

Main.xaml                      # Entry point (workflow shell)
│
├── Personal.xaml              # Orchestrates job scraping + employee data + filtering + email
│   ├── Extract_Data_Linkedin.xaml      ┐
│   ├── Extract_Data_Indeed.xaml        │
│   ├── Extract_Data_Glassdoor.xaml     ├─ Site scrapers → each invokes Data_Extraction
│   ├── Extract_Data_Monster.xaml       │
│   └── Extract_Data_SimplyHired.xaml   ┘
│
├── Organization.xaml          # Collects organization/company data + filtering + email
│
├── Data_Extraction.xaml       # ♻️ Reusable: parses raw job text → structured fields
└── Data_Filtering.xaml        # ♻️ Reusable: keyword-based row filtering + Excel write

Design principle: common logic lives in shared, argument-driven sub-workflows (Data_Extraction, Data_Filtering) instead of being copy-pasted into every scraper — keeping the project DRY and easy to extend with new job sites

🚀 Getting Started

Prerequisites

• Windows OS
• UiPath Studio 21.10.x (Community Edition is free)
• Google Chrome with the UiPath Browser Extension enabled (Studio → Tools → UiPath Extensions → Chrome)
• A reachable SMTP server / email account for the email step

Run It

1. Clone the repository

   git clone https://github.com/HarshTanwar1/Job_Bot.git

2. Open in UiPath Studio

   • Launch Studio → Open a Local Project → select project.json.
   • Studio restores dependencies automatically (Excel, Mail, System, UIAutomation). If not, restore them via Manage Packages.

3. Verify the Chrome extension is installed and enabled (the bot uses Use Browser Chrome).

4. Configure email — Open Personal.xaml / Organization.xaml and set your SMTP server, port, and credentials in the Send SMTP Mail Message activity.

5. Run a workflow

   • Employee + job data: open and Run Personal.xaml
   • Organization data: open and Run Organization.xaml
   • Follow the on-screen dialogs to enter your email, choose whether to filter, pick a column, and enter a keyword.

6. Check the output — Results land in the .xlsx files (Employee_Data.xlsx, Employment.xlsx, and the Filtered_*.xlsx copies) and in your inbox.

⚠️ Note: Scrapers depend on each site's current page layout. If a site changed its markup since this project was built, some selectors may need to be re-indicated in UiPath Studio

📚 What I Learned

• Building modular, reusable UiPath workflows by extracting shared logic into separate argument-driven .xaml files instead of duplicating it across every scraper.
• Designing robust web selectors and handling the reality that every job portal — and even individual listings on the same site — renders its pages differently.
• Using Check App State / Target appears and Try/Catch to make automation resilient to slow loads, missing elements, and pop-ups instead of crashing on the first surprise.
• Passing data between workflows with In / InOut arguments and moving structured data around using DataTables.
• Integrating Excel read/write and SMTP email to turn raw scraped data into a finished, deliverable report.
• Adding interactive input dialogs so the same bot can be re-run with different keywords, filter criteria, and recipients without touching the workflow.

🔮 Future Improvements

• Stronger error handling & logging — Structured logs, retry scopes, and failure screenshots.
• Selector resilience — Anchor-based / fuzzy selectors to reduce maintenance as sites change.
• Deduplication & validation — Drop duplicate listings and validate fields before export.
• Scheduling — Run unattended via UiPath Orchestrator/Assistant for automated daily digests.
• Auth handling — Gracefully handle login walls (e.g. LinkedIn's auth wall) that block guest scraping.

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