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Unternehmen
Wir haben Daten zu 30 Unternehmen, die PyPy verwenden. Unsere PyPy Kundenliste steht zum Download bereit und ist mit wichtigen Unternehmensspezifika angereichert, darunter Branchenklassifikation, Organisationsgröße, geografische Lage, Finanzierungsrunden und Umsatzzahlen, unter anderem.
Unternehmen | Land | Branche | Mitarbeiter | Umsatz |
---|---|---|---|---|
Continental Marketing, Inc | Vereinigte Staaten | 25 | ||
KAR Global | Vereinigte Staaten | Motor Vehicle Manufacturing | 2.6K | $18M |
Capgemini Engineering | Frankreich | It Services And It Consulting | 49K | |
Continental Marketing, INC | Vereinigte Staaten | 32 | ||
Datadog | Vereinigte Staaten | Software Development | 6.9K | $2.1B |
Trayport | Vereinigtes Königreich | Software Development | 361 | $6.5M |
Telus International | Kanada | It Services And It Consulting | 75K | $2.5B |
Cyient | Indien | Engineering Services | 19K | $644M |
Q1 Technologies | Indien | It Services And It Consulting | ||
Software International | Malaysia | It Services And It Consulting | 140 | |
Soltia AB | Schweden | It Services And It Consulting | 45 | |
Infopulse | Ukraine | It Services And It Consulting | 1.8K | $50M |
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Nutzungsstatistiken für Technologie und Marktanteil
Sie können diese Daten an Ihre Bedürfnisse anpassen, indem Sie nach Geografie, Branche, Unternehmensgröße, Umsatz, Technologienutzung, Jobpositionen und mehr filtern. Sie können die Daten im Excel- oder CSV-Format herunterladen.
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PyPy wird in 8 Ländern verwendet
Häufig gestellte Fragen
Unsere Daten stammen aus Stellenanzeigen, die von Millionen von Unternehmen gesammelt wurden. Wir überwachen diese Anzeigen auf Firmenwebseiten, Jobbörsen und anderen Rekrutierungsplattformen. Die Analyse von Stellenanzeigen bietet eine zuverlässige Methode, um die von Unternehmen verwendeten Technologien zu verstehen, einschließlich der Nutzung interner Tools.
Wir aktualisieren unsere Daten täglich, um sicherzustellen, dass Sie auf die aktuellsten verfügbaren Informationen zugreifen. Dieser häufige Aktualisierungsprozess garantiert, dass unsere Einsichten und Erkenntnisse die neuesten Entwicklungen und Trends der Branche widerspiegeln.
PyPy, short for Python implementation in Python, is an alternative implementation of the Python programming language. It aims to improve the execution speed of Python code through a just-in-time compiler. Unlike the standard CPython implementation, which interprets Python code, PyPy uses a translation toolchain to convert Python code into lower-level languages for faster execution. This technology is popular among developers looking to boost the performance of their Python applications without sacrificing the ease of development that Python is known for.
PyPy falls under the category of Languages in the technology landscape. As a specialized Python implementation, PyPy caters to developers who prioritize speed and performance in their Python projects. By utilizing a just-in-time compiler, PyPy offers a significant speedup compared to traditional Python interpreters, making it a valuable tool for tasks requiring computational efficiency.
The PyPy project was founded in 2004 by a group of developers with the motivation to address the performance limitations of traditional Python implementations. Their goal was to create a high-performance alternative to CPython that could leverage advanced optimization techniques to speed up Python code execution. Over the years, the PyPy team has continued to refine and enhance the technology, cementing its position as a go-to solution for developers seeking performance gains in Python applications.
Currently, PyPy holds a niche market share within the category of Languages, with a dedicated user base that values its speed and performance benefits. While PyPy may not have the widespread adoption of mainstream Python implementations, its unique value proposition continues to attract developers working on performance-critical projects. With ongoing advancements and community support, PyPy is poised to maintain its position in the market and potentially see growth as more developers prioritize speed optimization in their Python development workflows.
PyPy is a high-performance implementation of the Python programming language. It offers a range of benefits that make it a popular choice among companies seeking efficient and flexible solutions for their development needs.
PyPy's just-in-time (JIT) compiler significantly boosts the execution speed of Python code compared to the standard Python interpreter. This results in faster application performance and reduced processing times, making PyPy an ideal choice for high-throughput applications and time-critical processes.
PyPy's memory management capabilities outperform traditional Python interpreters by utilizing advanced garbage collection techniques. This leads to more efficient memory usage, reduced memory leaks, and enhanced overall stability of applications, ensuring smoother operations and better resource utilization.
PyPy's compatibility with C extensions allows companies to seamlessly integrate existing C libraries and modules into their Python applications. This enables the reuse of valuable legacy code and facilitates the development of complex applications that leverage both Python's flexibility and C's performance.
PyPy's support for multi-threading and concurrency mechanisms enables companies to design and implement scalable, parallelized applications with ease. By leveraging PyPy's concurrency features, companies can effectively utilize modern hardware architectures and optimize resource utilization for better performance and responsiveness.
PyPy benefits from a vibrant community of developers and contributors dedicated to enhancing its features, performance, and compatibility. This active community ensures timely updates, bug fixes, and optimizations that keep PyPy in line with evolving industry standards and best practices. Companies leveraging PyPy can benefit from ongoing improvements and innovations to enhance their development workflows and software capabilities.
PyPy is a popular alternative Python implementation that focuses on speed and efficiency. Several well-known companies have incorporated PyPy into their tech stacks to enhance performance. Let's take a look at a few case studies of companies effectively utilizing PyPy:
1. Dropbox: Dropbox, a leading cloud-based file storage service, implemented PyPy to optimize the performance of their backend Python services. By leveraging PyPy's Just-In-Time (JIT) compiler, Dropbox was able to achieve significant speed improvements in their data processing pipelines. They started using PyPy in early 2017 and have since seen a notable reduction in processing times, allowing them to handle larger volumes of data more efficiently.
2. Instagram: Instagram, the popular photo-sharing social platform, integrated PyPy into their server infrastructure to improve the scalability of their services. By utilizing PyPy's efficient memory management and runtime speed, Instagram was able to enhance the responsiveness of their platform during peak usage periods. They adopted PyPy in late 2016 and have since experienced smoother performance across their application, leading to a better user experience for millions of users worldwide.
3. Yelp: Yelp, the well-known online platform for crowd-sourced reviews, turned to PyPy to enhance the performance of their recommendation algorithms. By harnessing PyPy's enhanced runtime capabilities, Yelp was able to process user input more swiftly and deliver personalized recommendations in real-time. They began utilizing PyPy in mid-2018 and have since seen a notable increase in the efficiency of their recommendation engine, driving higher user engagement and satisfaction.
These case studies demonstrate how companies like Dropbox, Instagram, and Yelp have successfully incorporated PyPy into their technology stack to achieve performance gains and optimize their services effectively. By leveraging PyPy's unique features, these companies have been able to enhance their applications, improve scalability, and deliver a seamless user experience to their customers.
Sie können eine aktuelle Liste von Unternehmen, die PyPy verwenden, auf TheirStack.com einsehen. Unsere Plattform bietet eine umfassende Datenbank von Unternehmen, die verschiedene Technologien und interne Tools nutzen.
Bis jetzt haben wir Daten von 30 Unternehmen, die PyPy verwenden.
PyPy wird von einer Vielzahl von Organisationen in verschiedenen Branchen, einschließlich "Motor Vehicle Manufacturing", "It Services And It Consulting", "Software Development", "Software Development", "It Services And It Consulting", "Engineering Services", "It Services And It Consulting", "It Services And It Consulting", verwendet. Für eine umfassende Liste aller Branchen, die PyPy nutzen, besuchen Sie bitte TheirStack.com.
Einige der Unternehmen, die PyPy verwenden, umfassen Continental Marketing, Inc, KAR Global, Capgemini Engineering, Continental Marketing, INC, Datadog, Trayport, Telus International, Cyient, Q1 Technologies, Software International und viele mehr. Sie können eine vollständige Liste von 30 Unternehmen, die PyPy nutzen, auf TheirStack.com finden.
Basierend auf unseren Daten ist PyPy am beliebtesten in Vereinigte Staaten (7 companies), Kanada (5 companies), Frankreich (3 companies), Vereinigtes Königreich (3 companies), Indien (2 companies), Malaysia (1 companies), Schweden (1 companies), Ukraine (1 companies). Es wird jedoch von Unternehmen auf der ganzen Welt verwendet.
Sie können Unternehmen, die PyPy verwenden, finden, indem Sie auf TheirStack.com danach suchen. Wir verfolgen Stellenanzeigen von Millionen von Unternehmen und nutzen sie, um herauszufinden, welche Technologien und internen Tools sie verwenden.