How to scrape company listing data from Tradebulls
- Minexa.ai
- 6 days ago
- 3 min read
Indian equity markets list thousands of companies across BSE and NSE, and finding a clean, structured version of that company directory is harder than it should be. Tradebulls maintains a browsable company listing at tradebulls.in/company-list/n that covers company names, BSE codes, NSE ticker symbols, and direct profile links. The data is there, but it is paginated across multiple pages and not downloadable out of the box.
This guide shows how to extract that data into a clean, structured file using the Minexa.ai Chrome extension, with no code required.
What data is available on the Tradebulls company listing
Each row in the Tradebulls company directory exposes five core fields:
Company name: the registered name of the listed entity
BSE code: the Bombay Stock Exchange numeric identifier
NSE code: the National Stock Exchange ticker symbol, or the string Not Listed when the company trades only on BSE
Company profile link: a relative path to the company's smart-quotes page on Tradebulls
Company code: an additional identifier field present in the page structure
The NSE code field is particularly useful for filtering. Companies showing Not Listed are BSE-only, while those with a ticker value trade on NSE. This distinction matters when building watchlists, screening tools, or cross-referencing against other data sources that use NSE symbols as a primary key.
The company profile link follows a consistent pattern: /company-profile/smart-quotes/TICKERSYMBOL. Once extracted, these relative paths can be prefixed with the base domain to generate a full list of direct profile URLs, which can then be fed into a second scraping pass to pull fundamentals, price history, or financials for each company.
How to extract the data with Minexa.ai
The extraction process takes a few minutes from start to finish. Here is how each phase looks.
Step 1: Open the page and launch the extension
Navigate to https://www.tradebulls.in/company-list/n in Chrome, then click the Minexa.ai extension icon. The popup appears with a confirmation prompt.
Step 2: Confirm pagination detection
Minexa scans the page and identifies the pagination controls automatically. The extension shows which navigation element it detected and asks you to confirm before continuing. For the Tradebulls company listing, the next-page button is detected correctly without any manual adjustment.
Step 3: Choose list-only or list with detail pages
After confirming pagination, Minexa asks whether you want to scrape the listing only, or follow each company profile link and extract detail page data as well. For a full company directory export, selecting the list-only option is the right starting point.
Step 4: Select the data container and create the scraper
Minexa highlights the HTML container holding the company rows automatically. You confirm the selection, and the extension generates a reusable scraper. All data columns within that container are identified and named without any manual field mapping.
Watch the full walkthrough below to see each step in context.
Sample extracted data
Below is a representative sample of what Minexa returns from the Tradebulls company listing. Meta fields are removed for clarity.
Company name | BSE code | NSE code | Profile link |
NACDAC INFRASTRUCTURE LIMITED | 544313 | Not Listed | /company-profile/smart-quotes/NACDAC |
NACL INDUSTRIES LIMITED | 524709 | NACLIND | /company-profile/smart-quotes/NACLIND |
NATCO PHARMA LTD. | 524816 | NATCOPHARM | /company-profile/smart-quotes/NATCOPHARM |
Each row maps to one company. The profile link field is a relative URL that can be combined with the base domain to build a complete list of deep-link URLs for any follow-up extraction pass.
Running the job and exporting results
Once the scraper is created, the job summary screen gives you the option to connect a Google Sheet for live output, or set a recurring schedule to re-run the extraction automatically. After the job completes, results are exportable as Excel or JSON directly from the results table.
Reusing the scraper across other listing pages
The Tradebulls company directory is organised alphabetically. The URL pattern is consistent: tradebulls.in/company-list/a, tradebulls.in/company-list/b, and so on through the alphabet. Because each alphabetical page shares the same HTML structure, the scraper trained on the /n page works on every other letter page without retraining. You point it at a new URL and the same columns are extracted in the same format.
This is the core reuse model in Minexa: train once on a representative page, then apply that scraper to as many structurally identical pages as needed. The scraper_id stays constant across all runs.
Install the Minexa.ai Chrome extension, open any Tradebulls company listing page, and your first structured export is ready in a few minutes.
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