Synchredible makes it easy to synchronize, copy, and back up individual folders or entire drives with just a single click. Its intuitive assistant guides you step by step in setting up tasks that can be scheduled, triggered by changes (real-time monitoring), or executed automatically when an external storage device is connected. Keep your data synchronized effortlessly and manage it seamlessly!
With years of proven technology, Synchredible not only transfers data from A to B but also supports bidirectional synchronization. It automatically detects changes and reliably syncs the most recently edited files. Thanks to advanced duplicate detection, Synchredible saves valuable time by skipping unchanged files, enabling fast synchronization of large datasets in seconds!
Synchredible is highly versatile, supporting local folder synchronization, network and USB device synchronization, as well as synchronization with cloud storage.
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SurveyJS is a set of four open-source JavaScript libraries that offer the benefits of a tailor-made in-house survey application, while considerably reducing the time and resources needed to deploy the system. These libraries are independent of specific server code or database requirements and seamlessly integrate with popular JavaScript frameworks, including React, Angular, Vue.js, jQuery, Knockout, and more. They are designed to communicate with any server that can handle JSON requests, ensuring compatibility with various server architectures and databases.
The product family is composed of:
- An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
- A self-hosted drag & drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules. It automatically generates JSON definitions (schemas) of your forms in real time.
- PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser;
- The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
Visit our website to try out and evaluate our full-scale demo for free.
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Cython
Cython serves as an optimizing static compiler designed for both the Python language and the enhanced Cython language, which is rooted in Pyrex. It simplifies the process of creating C extensions for Python, making it as straightforward as writing Python itself. With Cython, developers can harness the strengths of both Python and C, enabling seamless interactions between Python code and C or C++ code at any point. By incorporating static type declarations in a Python-like syntax, users can easily enhance the performance of their readable Python code to that of plain C. The tool also provides combined source code level debugging, allowing developers to efficiently identify issues within their Python, Cython, and C code. Cython is particularly adept at managing large datasets, such as multi-dimensional NumPy arrays, facilitating the development of applications within the expansive and robust CPython ecosystem. Notably, the Cython language extends the capabilities of Python by allowing direct calls to C functions and the declaration of C types for variables and class attributes, ultimately enhancing the development experience. This fusion of languages not only broadens the possibilities for developers but also streamlines the process of optimizing Python applications.
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NumPy
Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.
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