Scarping Meaning: Definition, Examples, and Translations
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scarping
[ˈskɛr.pɪŋ ]
Definitions
data extraction
Scraping refers to the automated process of extracting data from websites. It is commonly used to gather data for various purposes such as research, analysis, and monitoring information from online sources. Web scraping involves making requests to a web server and then parsing the HTML or other formats to retrieve the desired data. It can be performed using various programming languages and tools specifically designed for scraping tasks.
Synonyms
content extraction, data harvesting, web crawling.
Examples of usage
- I was scraping data from the e-commerce site to analyze pricing trends.
- Web developers often use scraping to collect data for their applications.
- She built a script for scraping job listings from multiple websites.
website data
Scraping is a method used for obtaining data from websites through automated scripts or software. It involves fetching the web pages and extracting necessary information in a structured format. Scraping is frequently used in industries such as marketing, finance, and journalism to gather large volumes of data efficiently. Because scraping can sometimes infringe on copyright or website usage policies, it is important for users to be aware of legal implications.
Synonyms
data mining, information extraction, web scraping.
Examples of usage
- The scraping of social media data has led to privacy concerns.
- Scraping techniques can help businesses stay competitive by monitoring market trends.
- Ethical scraping practices are vital in maintaining data integrity.
Translations
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Interesting Facts
Geology
- Scarps are often formed by geological processes such as erosion, tectonic faulting, or landslides.
- They can provide important information about the earth's history and geological activity in an area.
- Studies of scarps can help scientists understand the stability of slopes and assess risks for landslides.
Civil Engineering
- Scarps may be created intentionally to help with road building or construction by providing stable, flat areas.
- Proper scarping is crucial to prevent landslides and soil erosion in construction projects.
- Engineers utilize various techniques when scarping to maintain the integrity of the surrounding landscape.
Environmental Impact
- Scarps can affect local ecosystems, changing water drainage patterns and soil composition.
- Excessive scarping can lead to habitat loss for wildlife and increase the risk of soil erosion.
- Environmental assessments are often conducted before major scarping projects to mitigate negative impacts.
Cultural References
- The idea of scarping can be found in various landscapes, influencing agricultural practices, especially in hilly areas.
- In literature, steep hillsides and scarps often symbolize challenges or obstacles characters must overcome.
- Art and photography celebrating natural landscapes frequently highlight the beauty of scarps and their formations.
Origin of 'scarping'
Main points about word origin
- Derived from the word 'scarpa', meaning 'to cut' in Italian, relating to the act of making steep cuts in land.
- The term is a combination of 'scar' and the suffix '-ing', showing an action that changes a surface.
- Used in engineering and geology to describe modifications to land for various purposes.
The term 'scraping' draws its roots from the verb 'scrape,' which originally means to remove a thin layer or unwanted material from a surface. This word has been in use since Middle English, derived from the Old Norse word 'skrapa,' meaning 'to scrape off or to erase.' With the advent of the internet in the late 20th century, the term 'scraping' evolved to encompass the extraction of data from websites. Since data is often presented in a format that requires processing, the concept of scraping became crucial for technology and data analysis sectors. The rise in demand for data-driven decisions further cemented scraping's relevance, leading to the development of various tools and frameworks designed to perform scraping tasks more efficiently. Today, scraping is an integral part of data science, often used by companies and researchers alike to harness information for diverse applications.