Development of a Python script for cross-checking leads in Google Sheets with the client's internal database

Hello!

My name is Nick and I am a Python developer with over 2 years of experience. I specialize in automation and data parsing, so this project is right up my alley. For some projects in my portfolio, you can check my website: https://nixlxcky.github.io/

For solving the project, I see two options:

1) A fairly basic approach, writing everything based on selenium + Python. It’s quite feasible to implement the data parsing itself, and for comparing tables, using pandas is perfect for working with large data. This solution is implementable and doesn’t require much effort, then it can easily be uploaded to a remote VPS server on Windows or Linux.

2) If we talk about elegant solutions, I would use N8N. A quite powerful automation tool, and most importantly — it requires almost no coding. So it will be easy to maintain and won’t require much effort in setup. However, N8N uses the API from Google Sheets, so that option is definitely out.
…
So let’s discuss the specific details of the project and get started on collaboration!

Best regards, Nick

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Good day. I am interested in your project. I have done similar work. I am ready to dedicate time only to this task and create a parser (scraper) for you. The deadlines are approximate. The cost includes the service fee charged to the performer. I would be glad to cooperate.

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Hello. I am ready to complete your task, I will write a script that can interact with Google Sheets and perform all the necessary functions according to your technical specifications.

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1. Reading data from Google Sheets

Technology:
• CSV export via requests or pandas.read_csv()
Why:
• If the Google Sheet is published or accessible via a link (or in a domain), you can get CSV via the URL:
https://docs.google.com/spreadsheets/d/{SPREADSHEET_ID}/export?format=csv&gid={SHEET_GID}
• This works stably, does not require authorization, simple and fast.

… Alternative (if access is denied):
• Selenium or Playwright (in Python)
— emulates logging in and exporting a table to a file.

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2. Reconciliation with an internal database

Technology:
• Pandas
Why:
• Conveniently load CSV/Excel/Sheets, compare by the required fields (phone, email, company) via merge, isin, duplicated.

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3. Determining the lead status

Logic in Pandas:
• If the email or phone matches the database — “Current client”.
• If found in the same table more than once — “Duplicate”.
• Otherwise — “New lead”.

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4. Outputting the result

Technologies:
• pandas.to_excel() or Google Sheets via automation
Options:
• Save a new table (Excel/CSV) with the lead_status column.
• Or use Selenium to paste the results back into Google Sheet (if you really need it there — you can use Google Drive synchronization or a colab script).

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5. Restart and instructions

Solution:
• Python script in .py or Jupyter Notebook with parameters at the beginning.
• Folder with a template table and instructions:
— “Download the table from the link”
— “Put the database file in this folder”
— “Run the script by double-clicking or via python script.py”

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Conclusion

Stack: Python + Pandas + Requests or Selenium
Why: does not require an API, easy to customize, convenient to automate, suitable for a technically literate user without a programmer.

Hello. Ready to take on your project. I have extensive work experience.

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Hello. I have extensive experience with Python. Ready to collaborate

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Good afternoon. Ready to execute.
I have extensive experience in developing parsers.
I write in Python, ranked 2nd on the platform.

I will develop a system for reading data from Google Sheets without using the API.
I will create logic for comparing data with the client's database and obtaining the lead status.
There will be a user-friendly interface for management and manual launching. The results will be output in the required format. I will optimize. I will do deployment.
I will conduct testing and provide documentation.

… My portfolio: Freelancehunt
Write to me, we will discuss the details and I will start working.
Methods of solution, deadlines, and cost will be provided in private messages.

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Good morning,

I’m Patryk Samson, co-owner of WebyJuice, a Poland-based agency registered and issuing VAT invoices. We’re ready to build a standalone Python script to extract data from Google Sheets without using the official API, compare leads against your internal database (CSV/Excel/Google Sheets), assign statuses (“Current Client,” “New Lead,” “Duplicate”) based on phone, email, and company name, and present results in a user-friendly format (e.g., updated Google Sheet or new file).

We’ll provide:
- Data extraction from Google Sheets using alternative methods (e.g., CSV parsing or browser automation).
- Efficient lead comparison with robust error handling for reliability.
- Results output in a reusable format, with clear, non-technical instructions for future use.
- Well-documented, clean code optimized for Linux/Windows and large datasets (>5000 rows).
…
Proposed Solution (without API): For publicly accessible Google Sheets, we’d use the `gspread` library with a public share link to fetch data directly as a CSV, avoiding API restrictions. We’d parse the CSV using pandas for fast, scalable processing, load your internal database (CSV/Excel) into pandas, and compare fields (phone, email, company name) to assign statuses. Results would be written to a new column in the original Sheet or a separate Excel/CSV file.

If the Sheet requires authentication, we’d employ `pygsheets` with browser automation (e.g., Selenium) to access exported data securely. This approach uses open-source libraries, ensures easy re-runs, and includes error handling for cases like temporary Sheet unavailability.

WebyJuice has deep expertise in automation, data parsing, and lead processing for premium brands like Jaguar, Porsche, BMW, Hymer, Land Rover, Mini, and Toyota. Explore our portfolio at: https://webyjuice.pl/portfolio.

We’re open to communication via Freelancehunt or Telegram and excited about potential future complex tasks.

Let’s discuss specifics and kick off your script development ASAP!

Good afternoon! I will make such a bot. You can read directly into pandas or use Google's gspread to access public spreadsheets without an API key.

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Good afternoon. I have worked with both Google Sheets and Excel/CSV tables in a real estate parsing project. I want to note right away that not using the Google Sheets API will be very difficult to achieve stable operation. I have worked with files containing more than 50k rows. I am ready to take on the order.

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Good day. I implement through Selenium Python for Windows. The Pandas library is the best library for data analysis.

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Good day, I have experience in parsing and data analysis in Python, here is how I would perform this task:

If the Google Sheets table is open for viewing without authorization, I would simply download it in CSV format via a direct request (requests) to a link like https://docs.google.com/spreadsheets/d/{id}/export?format=csv, substituting my User-Agent to mimic a browser. Then I would load the CSV into pandas, read the local database (CSV or Excel) using pandas, compare by fields (phone number, email, company name), and add a new column with the status. The result would be saved into a new file (for example, Excel or CSV).
If the table is closed — I would use Selenium with headless Chrome for authorization and downloading through the interface.

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Good afternoon
ready to start working today
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If the table is published as a web page, you can parse the HTML code using libraries such as BeautifulSoup.

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Hello, I have experience with original solutions in Python, I made a CAPTCHA decoder, so we can discuss the details and I think we can work together)

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