This tutorial shows how to scrape Annuaire 118000 listing pages into a local CSV with the Annuaire 118000 Data Scraper for UScraper. If your search is comment scraper 118000, the practical answer is: import the workflow, replace the starting directory URL, set the export path, run pagination, and validate names, addresses, postcodes, phone numbers, and notes before using the file.
Before you start
Prerequisites, scope, and policy checks
You need UScraper installed as a local desktop app, the Annuaire 118000 Data Scraper template, one Annuaire 118000 listing URL you are allowed to process, and a folder where CSV files can be written. Start with one narrow search rather than a whole directory section: a city, activity, region, name query, or professional category is easier to inspect.
This guide covers visible directory listing pages from the professional Annuaire 118000 site and related 118000 directory surfaces, not private dashboards, login-only data, CAPTCHA bypassing, or enrichment from unrelated databases. Before automation, review the current 118000 home page, activity index, regional directory pages, and robots.txt so your run matches the site's current access guidance.
Technical access is not permission. Keep batches modest, avoid access-control bypassing, document your purpose, and treat exported rows as contact data that may trigger privacy and marketing rules.
Start URL
Choose the right Annuaire 118000 URL
The best starting URL is the narrowest page that still answers your research question. A broad directory page creates noisy rows and makes validation slower. A focused URL makes the CSV easier to defend because every row shares the same source context.
For a scraper annuaire professionnel workflow, start from a professional category, regional directory page, or activity search on www.118000.fr. For surname, city, or private-directory checks, review the annuaire.118000.fr surface and confirm that the rows you intend to process are appropriate for your use case. For reverse lookup pages, be especially careful: a reverse directory can involve phone-number lookup behavior rather than ordinary listing discovery, so it may not match this template's listing-card selector.
Use one of these starting patterns for the first test:
| Goal | Safer first URL shape | Why it helps |
|---|---|---|
| Local business research | One activity in one city or region | Keeps names, addresses, and postcodes comparable. |
| Data cleanup | One known name or company query | Makes row matching easier against an internal file. |
| Coverage review | One professional category page | Lets you check whether pagination and cards remain stable. |
| Phone validation | A small result set with visible phone values | Helps test telephone extraction before scaling. |
Avoid mixing several intentions in one run. If you need Paris plumbers, Lyon dentists, and a surname query, run three separate exports with dated filenames. That makes deduping, consent review, and deletion requests much easier later.
Workflow anatomy
What the Annuaire 118000 scraper template does
The JSON export is the authoritative workflow definition. In plain English, the flow is:
Navigate -> Wait for Page Load -> Wait for listing cards
-> Structured Export -> check link[rel="next"]
-> open the next page -> wait again -> export again
-> End when no next page remains
The important selectors are intentionally small. The row selector targets section.card.part, which maps to visible listing cards in the workflow. The pagination test checks link[rel="next"]. The Structured Export block writes five columns and uses append mode so each page adds rows to the same CSV instead of overwriting the first page.
That export shape matters because the workflow is not a generic page dump. It is configured to extraire donnees 118000 into a spreadsheet-ready structure: identity, location, postcode, phone, and a short note. If you add columns later, keep them tied to visible listing-card data rather than page chrome, ads, navigation, or unrelated recommendations.
| CSV field | What it captures | Validation check |
|---|---|---|
nom | Listing name from the card title or linked name area | Compare the first rows against the browser titles. |
adresse | Visible address text cleaned into one line | Confirm street, city, and spacing survived the export. |
cp | Five-digit French postcode parsed from the address | Filter blanks and spot-check mixed city searches. |
telephone | Visible phone text, tel: link, or best-effort decoded image-rendered number | Expect some blanks; verify before outreach. |
remarque | Short listing note from the result card bubble | Treat as optional context, not a required field. |
annuaire_118000_data_scraper.csvColumn
nom
Business or person name from the listing card.
Column
adresse
Address text normalized into one line.
Column
cp
Five-digit postcode extracted from the address.
Column
telephone
Visible, tel-link, or decoded image-rendered phone value where available.
Column
remarque
Optional note text from the card bubble.
Runbook
How to scrape Annuaire 118000 data to CSV
Import the template
Open Annuaire 118000 Data Scraper, download the workflow JSON, and import it into UScraper.
Replace the start URL
Edit the Navigate block. Use one approved 118000 result URL from a city, activity, region, name, professional category, or other narrow directory search.
Confirm waits and listing cards
Keep the page-load wait and visible section.card.part check. If the page loads slowly, extend the wait before changing selectors.
Set the CSV destination
In Structured Export, confirm annuaire_118000_data_scraper.csv, headers, append mode, and a project-specific save folder.
Run, review, then widen
Run one page, compare the CSV against the browser, then allow the next-link loop to collect additional pages when the sample is clean.
After the first run, sort by nom and telephone. If rows repeat, you likely reran into the same append-mode file or restarted the workflow after the export block had already written rows. Use a dated filename for test runs so validation rows do not mix with production rows.
Do not skip the export-path check. The bundled JSON includes a sample local save location from the template build machine. Change that folder before a real run, especially when several team members share the workflow. A predictable path such as Documents/UScraper/annuaire-118000/2026-06-test.csv is easier to audit than a default downloads folder.
Validation
Validate phone numbers, pagination, and export quality
Use validation as part of the scraping process, not as cleanup after the fact. Keep the source page open beside the CSV and verify at least one listing from the first page, one from the middle of the pagination sequence, and one from the final page.
| Symptom | Likely cause | Fix |
|---|---|---|
| Zero rows exported | Listing cards did not render or the selector no longer matches | Wait for the page visually, then inspect whether section.card.part still exists. |
Blank telephone | Phone is hidden, image-rendered differently, not present, or not decoded | Treat blanks as normal, then update the phone selector only after manual review. |
| Repeated rows | Append file reused or pagination revisited a page | Clear the CSV, use a dated filename, and confirm the next-link path. |
| Missing postcode | Address text changed or contains no five-digit code | Recheck the visible address and adjust postcode parsing for that page type. |
| Early stop | No link[rel="next"] was found or a challenge page interrupted navigation | Open the browser state, solve allowed prompts manually, and rerun a short sample. |
The highest-risk column is usually telephone, not nom. Names and addresses are easier to compare visually, while phone values may be hidden until interaction, rendered as images, or absent for some listings. Treat missing phone numbers as a signal to inspect, not as a reason to force extraction around site controls.
Alternatives
UScraper vs Octoparse and hosted annuaire scraping tools
If you searched for alternative Octoparse annuaire or scraper annuaire professionnel, the main decision is not just features. It is custody and workflow style. UScraper is strongest when you want a supervised local CSV, visible browser QA, and editable blocks that an analyst can adjust without building a scraper from scratch.
UScraper template
Local CSVHosted scraper
Cloud runRuns in the local desktop app
Best for reviewable exports where the operator wants to inspect the browser and file path.
Runs on vendor infrastructure
Useful for managed scheduling, but URLs and outputs usually pass through a third party.
Import JSON and edit blocks
Change the start URL, wait times, output folder, and columns directly in the workflow.
Configure a cloud actor or project
Can be better for centralized teams, proxies, recurring jobs, and larger managed queues.
Template is free to import
Good for controlled research exports and one-off directory cleanup.
Usage or subscription based
Often sensible when infrastructure, scheduling, and monitoring matter more than local custody.
Hosted tools such as Octoparse, Apify, Datablist, Thunderbit, or dedicated French directory extractors can still be the right choice for cloud throughput and scheduled jobs. For a local workflow that teaches extraire donnees 118000 and extraire numeros telephone annuaire into CSV, start with UScraper and validate the file before scaling.
FAQ
Frequently asked questions
Annuaire 118000 pages may be accessible in a browser, but automated collection can still be limited by site terms, robots guidance, database rights, GDPR, privacy law, and your purpose of processing. Review the current rules, keep runs proportionate, avoid bypassing access controls, and get legal review before commercial use.