Beautiful Soup Experts in Germany
for reliable web data extraction, matched in minutesHire experts who extract, clean and structure data from HTML and XML with Beautiful Soup, Python and tools such as requests or pandas. FRATCH connects you with precise matches among vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Beautiful Soup
Volker H.
Last position:
Data Analyst at Optaro GmbH
Creation of workflows for generating the data basis for the article import of a web shop: combining data from several sources, analyzing the requirements, designing the process with Jupyter Notebooks and Knime. Also creating code for automation in Python using Polars and Pandas.
Processing the source data, filtering and merging the source files and creating the needed intermediate products, creating the upload files, plausibility checks, quality checks.
Technologies used: PyCharm, Python, Jupyter Notebooks, SQL, Knime. Pandas, Polars
Manoj K.
Last position:
Data Analyst Work Student at Biebelhausener Mühle seit 1647 GmbH
- Managed and maintained daily sales and transaction data, ensuring data accuracy and integrity for operational reporting and analysis.
- Analyzed customer purchasing patterns to support inventory planning and improve product availability.
Peter A.
Last position:
IT Consultant at Mercedes-Benz Tech Innovation
- Development of automated software tests (unit, integration, regression and end-to-end tests).
- Applied technologies: Playwright, Vitest, JavaScript, TypeScript, Vue3, Go, Laravel, REST API, CI/CD, Docker, Git, GitHub, Scrum, Jira.
Olusina F.
Last position:
Cyber Job Simulation at Deloitte Australia
- Completed a job simulation involving reading web activity logs.
- Supported a client in a cybersecurity breach.
- Answered questions to identify suspicious user activity.
Arman A.
Last position:
Research Associate (Machine Learning & Signal Analysis) at Technical University of Clausthal
- Built end-to-end pipelines for sensor-driven time-series vibration signals: data cleaning, feature engineering, model selection for unsupervised learning, and validation for size classification tasks.
- Applied statistical feature extraction to characterize dynamic responses.
- Developed Python algorithms for signal processing (FFT, PSD) and classification; compared multiple model architectures with uncertainty-aware evaluation.
- Supervised students in labs and projects (analysis methods, interpretation, reporting); delivered a practical laboratory course and contributed to documentation and presentations.
- Prepared academic outputs: Master’s thesis and conference contribution (SimScience 2025).
Daniel C.
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Apoorv S.
Last position:
AI Interviewer
- Built an AI Research Assistant with RAG, LangChain, LangGraph, and OpenAI LLMs integrated with vector search.
Ekaansh K.
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Krupali P.
Last position:
Research Associate at Institute of Anatomy and Cell Biology
- Led single-cell and bulk RNA-seq analyses to identify rare airway and immune cell populations
- Designed and deployed multiple interactive R Shiny and Streamlit dashboards for real-time data exploration and communication with clinical partners
- Developed machine learning models for immunotherapy response prediction using single-cell transcriptomics and immune profiling data
- Built reproducible pipelines for single-cell and bulk RNA-seq analyses aligned with clinical and research standards
- Analyzed patient-derived datasets for biological marker identification using reproducible pipelines aligned with research and clinical standards
- Translated computational outputs into clear biological insights for mixed technical and non-technical audiences
Discover over 15,000 top freelancers
Statistics of experts using Beautiful Soup
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
1.7 years
Positions per freelancer
11
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Business Intelligence, Information Technology, Logistics
Bachelor's degree or higher
100%
Master's degree or higher
78%
Doctorate
22%
Certifications per freelancer
2
Most common languages
English, German, French
Speak two or more languages
89%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using Beautiful Soup
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Beautiful Soup experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (89%)
- Education (67%)
- Healthcare (56%)
- Manufacturing (56%)
- Food and Beverage (44%)
- Banking and Finance (33%)
- Transportation (33%)
- Retail (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Beautiful Soup does
Beautiful Soup is a Python library for parsing HTML and XML documents. It turns complex page markup into a navigable tree, so professionals can locate elements, read text, inspect attributes and extract structured content without handling raw strings manually.
Typical applications
Beautiful Soup is useful when companies need targeted web data extraction rather than a complete crawling system.
- Collect product details, listings or editorial content
- Extract links, metadata, tables and embedded attributes
- Clean inconsistent HTML from internal or public sources
- Prepare source data for analysis, migration or monitoring
Python ecosystem
Strong work with Beautiful Soup usually includes Python, requests or httpx for fetching pages, and pandas for tabular processing. lxml can provide a faster parser for suitable workloads, while Scrapy is often considered when a project needs scheduled crawling, queues, retries and broader spider management.
When specialists help
Companies bring in freelance specialists when a one-off script must become a dependable data workflow, when markup changes break an existing extractor, or when internal teams need support with a time-sensitive migration. In Germany, remote collaboration is common, while clear documentation and suitable German or English communication help teams coordinate with local stakeholders.
Quality and reliability
A robust solution separates fetching, parsing, validation and storage. It handles missing elements, duplicate records, encoding issues, pagination and changing selectors instead of assuming every page has identical markup.
- Use semantic selectors and defensive fallback logic
- Respect access rules, robots guidance and site terms
- Log failures and validate extracted fields
- Add tests for representative page structures
Skills to look for
The right professional understands the target HTML, HTTP behaviour and the boundaries of responsible collection. They can explain parser choices, preserve provenance, design maintainable transformations and deliver readable Python with setup instructions, tests and a clear handover.
Frequently asked questions
Questions about Beautiful Soup? Start with the answers below.
Beautiful Soup is used to parse HTML and XML and extract selected content from documents. A professional may use it for product data, links, tables, metadata, text cleaning or migration preparation.
Beautiful Soup focuses on parsing documents after they have been fetched, making it useful for targeted extraction and smaller workflows. Scrapy provides a broader crawling framework with scheduling, concurrency and request management, so the choice depends on the scale and structure of the collection task.
Beautiful Soup is often chosen for readable, flexible parsing code and irregular markup. lxml can be preferable when parsing speed, XPath support or tighter integration with XML processing matters; capable professionals can assess both against the input and delivery requirements.
A strong Beautiful Soup specialist usually works comfortably with Python, HTTP clients such as requests or httpx, and data tools such as pandas. Knowledge of HTML, CSS selectors, XPath, encoding, validation, storage and responsible web collection is also valuable.
The right level for Beautiful Soup depends on the page structure, number of sources, change frequency and required reliability. A simple extraction may need focused scripting, while a business-critical workflow calls for testing, monitoring, retries, data validation and clear maintenance documentation.
Beautiful Soup projects are well suited to remote collaboration when requirements, sample pages and expected output are documented clearly. Teams in Germany may work in German or English, but the professional should provide reproducible setup steps, transparent assumptions and concise progress updates.
Ask a Beautiful Soup specialist to explain selector choices, failure handling and how the result will be tested against changing markup. Review whether the delivery includes validation, logging, duplicate handling, encoding support and documentation rather than only a script that works on one page.
Beautiful Soup parses content that is already available to the Python program; it does not replace an HTTP client or browser automation tool. Professionals commonly combine it with requests or httpx for ordinary pages, and may use browser automation when content depends on client-side rendering.
The average hourly rate of freelancers in Germany who have used Beautiful Soup in their recent projects is 65 €, which corresponds to a daily rate of about 521 € based on an 8-hour working day.
Of the freelancers in Germany who have used Beautiful Soup in their recent projects, 100% hold at least a Bachelor's degree, 78% hold at least a Master's degree, and 22% hold a doctorate.
On average, freelancers in Germany who have used Beautiful Soup in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Germany who have used Beautiful Soup in their recent projects are English (100%), German (89%), and French (22%).
The most common industries among freelancers in Germany who have used Beautiful Soup in their recent projects are Information Technology (89%), Education (67%), and Healthcare (56%).
The most common business areas among freelancers in Germany who have used Beautiful Soup in their recent projects are Information Technology (100%), Business Intelligence (89%), and Product Development (89%).
Main locations of FRATCH Experts, who have recently used Beautiful Soup
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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FRATCH CEO
