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Automated job parser from German websites to Google Sheets

Data Parsing, Python — incorrectly specified categories?

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📄 Technical Specification (TS)

🎯 Goal:

Create an automated script/bot that:
— collects job vacancies weekly from leading German websites;
— allows changing keywords, city, and radius before running;
— filters out vacancies from intermediaries (Zeitarbeit / Arbeitnehmerüberlassung);
— records data into Google Sheets, organized by months, without duplicates;
— prepares the system for future integration with CRM (e.g., Pipedrive).

📋 Requirements for the solution:

🔗 Data sources:

✅ Indeed.de
✅ StepStone.de
✅ LinkedIn Jobs
✅ Xing Jobs
✅ Bundesagentur für Arbeit (via official API)
✅ (other sources — based on your recommendation)

📝 User settings:

Before each run, the user can specify:
— keywords for searching in the title;
— keywords for searching in the description;
— search city + radius (if supported by the site).

Implementation options:
🔹 as a configuration file (e.g., config.json),
or
🔹 a separate sheet in Google Sheets,
or
🔹 another convenient method of your choice.

📄 Output:

✅ All vacancies are recorded in one Google Sheet via API.
✅ For each month, a separate sheet is created with the name YYYY-MM (e.g., 2025-07).
✅ Vacancies are placed on the sheet corresponding to the publication date.
✅ If the sheet does not exist — it is created automatically.
✅ Headings on each sheet in German:

Titel der Stelle
Name des Unternehmens
Ort
Beschreibung
Ansprechpartner Name
Ansprechpartner E‑Mail
Ansprechpartner Telefonnummer
Link zur Anzeige
Veröffentlichungsdatum
Art der Beschäftigung (Vollzeit/Teilzeit/Minijob)
Datum/Zeit der Eintragung

🧹 Filters:

✅ First run → collect vacancies from the last 3 months → fill corresponding monthly sheets.
✅ Regular runs → collect vacancies from the last 7 days → add to the current month.
✅ Exclude vacancies from Zeitarbeit / Personalvermittlung / Arbeitnehmerüberlassung — by company name and vacancy description (keywords: Zeitarbeit, Leiharbeit, Arbeitnehmerüberlassung, Personalservice, Personaldienstleistung, Personalleasing etc.).
✅ Where possible, use built-in site filters or API to exclude Zeitarbeit at the query level.
✅ Check for duplicates (by Link zur Anzeige or another unique identifier).

🔄 Operating modes:

— First run: vacancies from the last 3 months, divided by months.
— Then — weekly (e.g., Monday) → vacancies from 7 days, added to the current month sheet.
— Old data is not overwritten.

🛠️ Technologies:

✅ preferably Python (or suggest an alternative with justification);
✅ use official APIs where possible (especially for BA);
✅ for the rest — scraping with delays and respecting site rules;
✅ integrate anti‑CAPTCHA (via 2Captcha, Anti‑Captcha, or similar) to bypass CAPTCHA.

🚀 Other requirements:

✅ automatic weekly launch (via cloud or server);
✅ manual launch option;
✅ error and missed vacancy logging;
✅ ability to specify your own anti‑CAPTCHA API key;
✅ well-documented, clean, and understandable code;
✅ system designed for ≥ 100 000 vacancies per year (~300 per day) without performance loss.

📦 Deliverables:

— code with documentation;
— user manual (how to change keywords, run, view results);
— hosting recommendations (Google Cloud, AWS, Azure, etc.);
— example Google Sheet with test data.

📩 What we expect from you:

✅ brief description of implementation;
✅ examples of similar projects (portfolio);
✅ estimated timelines and cost;
✅ recommendations for integration and support.

📌 Notes:

— If site filters for excluding Zeitarbeit are absent — filtering is done at the script level.
— If Google Sheets limit (more than 50,000–100,000 rows) is exceeded, suggest solutions (archiving, database, splitting).

📬 We look forward to your proposal with price, timelines, a brief approach description, and examples of implemented solutions.
Thank you!

Proposals 10 Withdrawn 1

Nikita S.

2 0

Projects -
Rating -
Rating 704

Budget: 80000 UAH Deadline: 30 days

There is experience and development of similar solutions and specified technologies for more than 5 years

Maksim Ivantsiv

12 0

Budget: 25000 UAH Deadline: 7 days

Good day
I have extensive experience in developing parsers
Write to me

Oleksandr D.

70 1

Budget: 27000 UAH Deadline: 14 days

Hello.
Create a parser that can collect information about groups.
The parser will receive a request as input and process all groups according to this request, or we can discuss.

Yelena Druzenko

5 0

Budget: 1111 UAH Deadline: 1 day

Good afternoon
can do it with Python + Scrapy + AWS
contact me

Oleksandr Stinkovyi

117 0

Budget: 20000 UAH Deadline: 20 days

Hello!

I am a NodeJS developer. Ready to take on the task. Write to me, we will discuss.

Artem Krylov

10 2

Budget: 1000 UAH Deadline: 1 day

Good day!
I have extensive experience in creating various parsers
Ready to help you with data collection
I will implement a high-quality parser that will instantly gather all the necessary information.
Contact me!

Kilimnik Oleksandra
Hamburg, Germany

Projects -
Rating -
Rating 215

Automated job parser from German websites to Google Sheets

📄 Technical Specification (TS)

🎯 Goal:

📋 Requirements for the solution:

🔗 Data sources:

📝 User settings:

📄 Output:

🧹 Filters:

🔄 Operating modes:

🛠️ Technologies:

🚀 Other requirements:

📦 Deliverables:

📩 What we expect from you:

📌 Notes:

Nikita S.

Maksim Ivantsiv

Oleksandr D.

Yelena Druzenko

Oleksandr Stinkovyi

Artem Krylov

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Proposals concealed

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