Alternatives to Bokeh

Seaborn is a versatile data visualization library for Python that builds upon matplotlib. It offers a user-friendly interface for creating visually appealing and insightful statistical graphics. To gain a foundational understanding of the library's concepts, you can explore the introductory notes or relevant academic papers. For installation instructions, check out the dedicated page that guides you on how to download and set up the package. You can also explore the example gallery to discover various visualizations you can create with Seaborn, and further your knowledge by diving into the tutorials or API reference for detailed guidance. If you wish to examine the source code or report any issues, the GitHub repository is the place to go. Additionally, for general inquiries and community support, StackOverflow features a specific section for Seaborn discussions. Engaging with these resources will enhance your ability to effectively use the library.

Dash & Dash Enterprise allow you to build and deploy analytic web applications using Python, R, or Julia. No JavaScript or DevOps are required. The world's most successful companies offer AI, ML and Python analytics at a fraction of the cost of full-stack development. Dash is the way they do it. Apps and dashboards that run advanced analytics such as NLP, forecasting and computer vision can be delivered. You can work in Python, R, or Julia. Reduce costs by migrating legacy per-seat license software to Dash Enterprise's unlimited end-user pricing model. You can deploy and update Dash apps faster without an IT or DevOps staff. You can create pixel-perfect web apps and dashboards without having to write any CSS. Kubernetes makes it easy to scale. High availability support for mission-critical Python apps

The Vega-Altair open-source initiative operates independently from Altair Engineering, Inc. By utilizing Vega-Altair, users can focus more on grasping their data and its significance. Altair’s API is designed to be straightforward, user-friendly, and consistent, functioning atop the robust Vega-Lite visualization framework. This refined simplicity allows for the creation of stunning and impactful visualizations with minimal coding effort. The fundamental concept revolves around defining relationships between data columns and visual encoding channels, including the x-axis, y-axis, and color. Consequently, the intricate aspects of the plot are managed automatically. Expanding on this declarative plotting concept, a remarkable variety of both basic and advanced visualizations can be crafted using relatively succinct grammar, offering flexibility for different levels of data presentation. With its focus on ease of use, the Vega-Altair project empowers users to visualize complex data insights efficiently.

Matplotlib serves as a versatile library for generating static, animated, and interactive visual representations in Python. It simplifies the creation of straightforward plots while also enabling the execution of more complex visualizations. Numerous third-party extensions enhance Matplotlib's capabilities, featuring various advanced plotting interfaces such as Seaborn, HoloViews, and ggplot, along with tools for projections and mapping like Cartopy. This extensive ecosystem allows users to tailor their visualizations to meet specific needs and preferences.

PyQtGraph is a graphics and GUI library developed in pure Python, utilizing PyQt/PySide alongside NumPy, designed primarily for applications in mathematics, science, and engineering. Despite its complete implementation in Python, the library achieves impressive speed by effectively utilizing NumPy for numerical computations and the Qt GraphicsView framework for efficient rendering. Released under the MIT open-source license, PyQtGraph supports fundamental 2D plotting through interactive view boxes, enabling line and scatter plots with user-friendly mouse control for panning and scaling. Its ability to handle various data types, including integers, floats, and different bit depths, is complemented by functionalities for slicing multidimensional images at various angles, making it particularly useful for MRI data analysis. Furthermore, it facilitates rapid updates suitable for video display or real-time interactions, along with image display features that include interactive lookup tables and level adjustments. The library also provides mesh rendering capabilities with isosurface generation, while interactive viewports allow users to rotate and zoom with ease using the mouse. Additionally, it incorporates a basic 3D scenegraph, simplifying the programming process for three-dimensional data visualization. With its robust set of features, PyQtGraph caters to a wide range of visualization needs and enhances user experience through interactivity.

ggplot2 is a framework for creating graphics in a declarative manner, drawing on the principles outlined in The Grammar of Graphics. Users supply their data and specify how to map variables to aesthetics and which graphical elements to employ, while ggplot2 manages the intricate details. Having been around for over a decade, ggplot2 is utilized by hundreds of thousands of individuals, resulting in the creation of millions of plots. This extensive usage typically means that ggplot2 itself remains relatively stable over time. When updates do occur, they are primarily aimed at introducing new functions or parameters rather than altering the functionality of pre-existing ones; any modifications to current behaviors are made only when absolutely necessary. For those who are just beginning their journey with ggplot2, it is advisable to seek out a structured introduction instead of attempting to learn by perusing isolated documentation pages, as this approach will provide a more comprehensive understanding of the system. Engaging with tutorials and resources designed for beginners can significantly enhance your learning experience.

Easily switch between command and editor modes using just one keystroke while navigating through cells with arrow keys. Take advantage of all standard Jupyter shortcuts for a smoother experience. Experience fully interactive outputs positioned directly beneath the cell for enhanced visibility. When working within code cells, benefit from intelligent code suggestions, real-time error detection, quick-fix options, streamlined navigation, and many additional features. You can operate with local Jupyter notebooks or effortlessly connect to remote Jupyter, JupyterHub, or JupyterLab servers directly within the IDE. Execute Python scripts or any expressions interactively in a Python Console, observing outputs and variable states as they happen. Split your Python scripts into code cells using the #%% separator, allowing you to execute them one at a time like in a Jupyter notebook. Additionally, explore DataFrames and visual representations in situ through interactive controls, all while enjoying support for a wide range of popular Python scientific libraries, including Plotly, Bokeh, Altair, ipywidgets, and many others, for a comprehensive data analysis experience. This integration allows for a more efficient workflow and enhances productivity while coding.

Statsmodels is a Python library designed for the estimation of various statistical models, enabling users to perform statistical tests and explore data effectively. Each estimator comes with a comprehensive array of result statistics, which are validated against established statistical software to ensure accuracy. This package is distributed under the open-source Modified BSD (3-clause) license, promoting free use and modification. Users can specify models using R-style formulas or utilize pandas DataFrames for convenience. To discover available results, you can check dir(results), and you will find that attributes are detailed in results.__doc__, while methods include their own docstrings for further guidance. Additionally, numpy arrays can be employed as an alternative to formulas. For most users, the simplest way to install statsmodels is through the Anaconda distribution, which caters to data analysis and scientific computing across various platforms. Overall, statsmodels serves as a powerful tool for statisticians and data analysts alike.

The ROOT data analysis framework is widely utilized in High Energy Physics (HEP) and features its own file output format (.root). It seamlessly integrates with software developed in C++, while for Python users, there is an interface called pyROOT. However, pyROOT has compatibility issues with python3.4. To address this, broot is a compact library designed to transform data stored in Python's numpy ndarrays into ROOT files, structuring them with a branch for each array. This library aims to offer a standardized approach for exporting Python numpy data structures into ROOT files. Furthermore, it is designed to be portable and compatible with both Python2 and Python3, as well as ROOT versions 5 and 6, without necessitating changes to the ROOT components themselves—only a standard installation is needed. Users should find that installing the library requires minimal effort, as they only need to compile the library once or choose to install it as a Python package, making it a convenient tool for data analysis. Additionally, this ease of use encourages more researchers to adopt ROOT in their workflows.

Pexpect enhances the functionality of Python when it comes to managing other applications. This pure Python library excels at spawning child processes, overseeing them, and reacting to predefined output patterns. Similar to Don Libes’ Expect, Pexpect allows your scripts to interact with child applications as if a human were entering commands. It is particularly useful for automating the control of interactive applications such as ssh, FTP, passwd, and telnet. Additionally, Pexpect can facilitate the automation of setup scripts, making it easier to replicate software package installations across various servers. It is also valuable for conducting automated software testing. While Pexpect is inspired by the principles of Expect, it is entirely implemented in Python, setting it apart from other similar modules. Notably, Pexpect does not necessitate the use of TCL or Expect, nor does it require the compilation of C extensions. This feature makes it versatile across any platform that supports Python's standard pty module. The user-friendly design of the Pexpect interface ensures ease of use for developers. Overall, Pexpect stands out as an effective tool for automating and controlling various applications seamlessly.

The Python Imaging Library enhances your Python interpreter with advanced image processing features. This library offers a wide range of file format compatibility, an efficient internal structure, and robust image processing functionalities. Its core design focuses on enabling quick access to data in several fundamental pixel formats, serving as a reliable base for general image processing applications. For enterprises, Pillow is accessible through a Tidelift subscription, catering to professional needs. The Python Imaging Library is particularly well-suited for tasks related to image archiving and batch processing workflows. Users can leverage the library to generate thumbnails, switch between file formats, print images, and more. The latest version supports a diverse array of formats, while write capabilities are carefully limited to the most prevalent interchange and display formats. Additionally, the library includes essential image processing features such as point operations, filtering through built-in convolution kernels, and converting color spaces, making it a comprehensive tool for both casual and advanced users alike. Its versatility ensures that developers can efficiently handle various image-related tasks with ease.

Imageio is a versatile Python library that simplifies the process of reading and writing various types of image data, such as animated images, volumetric data, and scientific formats. It is designed to be cross-platform, compatible with Python versions 3.5 and later, and installation is straightforward. Since Imageio is developed entirely in Python, users can expect a seamless setup. It supports Python 3.5+ and is also functional on Pypy. The library relies on Numpy and Pillow for its operations, and for certain image formats, additional libraries or executables like ffmpeg may be required, which Imageio assists users in acquiring. In case of issues, understanding where to look for potential problems is crucial. This overview aims to provide insights into the workings of Imageio, enabling users to identify possible points of failure. By familiarizing yourself with these functionalities, you can enhance your troubleshooting skills when using the library.

tox is designed to streamline and automate the testing process in Python. This tool is a key component of a broader initiative to simplify the packaging, testing, and deployment workflow for Python applications. Serving as a universal virtualenv management tool and a test command-line interface, tox allows developers to verify that their packages can be installed correctly across multiple Python versions and interpreters. It facilitates running tests in each environment, configuring the preferred testing tools, and integrating seamlessly with continuous integration servers, which significantly minimizes redundant code and merges CI with shell-based testing. To get started, you can install tox by executing `pip install tox`. Next, create a `tox.ini` file adjacent to your `setup.py` file, detailing essential information about your project and the various test environments you plan to utilize. Alternatively, you can generate a `tox.ini` file automatically by running `tox-quickstart`, which will guide you through a series of straightforward questions. After setting up, be sure to install and validate your project with both Python 2.7 and Python 3.6 to ensure compatibility. This thorough approach helps maintain the reliability and functionality of your Python software across different versions.

Pandas is an open-source data analysis and manipulation tool that is not only fast and powerful but also highly flexible and user-friendly, all within the Python programming ecosystem. It provides various tools for importing and exporting data across different formats, including CSV, text files, Microsoft Excel, SQL databases, and the efficient HDF5 format. With its intelligent data alignment capabilities and integrated management of missing values, users benefit from automatic label-based alignment during computations, which simplifies the process of organizing disordered data. The library features a robust group-by engine that allows for sophisticated aggregating and transforming operations, enabling users to easily perform split-apply-combine actions on their datasets. Additionally, pandas offers extensive time series functionality, including the ability to generate date ranges, convert frequencies, and apply moving window statistics, as well as manage date shifting and lagging. Users can even create custom time offsets tailored to specific domains and join time series data without the risk of losing any information. This comprehensive set of features makes pandas an essential tool for anyone working with data in Python.

Scapy is an advanced, interactive tool designed for packet manipulation. It excels in crafting and interpreting packets across a multitude of protocols, facilitating their transmission, capturing data, and correlating requests with responses, among various other functionalities. This versatile program can efficiently perform traditional tasks such as scanning, tracerouting, probing, unit testing, executing attacks, and discovering networks, effectively replacing tools like hping, a significant portion of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, and p0f. Furthermore, Scapy stands out in executing specialized tasks that other utilities struggle with, including the transmission of invalid frames and the injection of custom 802.11 frames, as well as employing techniques like VLAN hopping combined with ARP cache poisoning or VOIP decoding over WEP-encrypted channels. It is compatible with various operating systems, including Linux, Windows, OSX, and most Unix variants that utilize libpcap. Notably, the same codebase supports both Python 2 and Python 3, showcasing its versatility. The development of Scapy is managed through the Git version control system, with its primary repository available on GitHub, allowing for collaborative improvements and updates. As a result, users benefit from continuous enhancements that keep pace with the evolving landscape of network security and analysis.

JDeli can read and write images in HEIC format. It also provides a complete HEIC conversion between HEIC file formats and many other image file formats. JDeli can convert the image in one step. You can also read and write the HEIC file separately if you need to process the image using Java. Threading can improve the performance of your code reading and writing. JDeli can be used with threads, unlike ImageIO. JDeli has a similar API to ImageIO. It is also easy to switch between the two in your code. JDeli is actively being developed by IDRsolutions' development team, who use it in their other products. Unable to add a platform dependence? JDeli is 100% Java, and does not require plugins or native dependencies.

Scikit-learn offers a user-friendly and effective suite of tools for predictive data analysis, making it an indispensable resource for those in the field. This powerful, open-source machine learning library is built for the Python programming language and aims to simplify the process of data analysis and modeling. Drawing from established scientific libraries like NumPy, SciPy, and Matplotlib, Scikit-learn presents a diverse array of both supervised and unsupervised learning algorithms, positioning itself as a crucial asset for data scientists, machine learning developers, and researchers alike. Its structure is designed to be both consistent and adaptable, allowing users to mix and match different components to meet their unique requirements. This modularity empowers users to create intricate workflows, streamline repetitive processes, and effectively incorporate Scikit-learn into expansive machine learning projects. Furthermore, the library prioritizes interoperability, ensuring seamless compatibility with other Python libraries, which greatly enhances data processing capabilities and overall efficiency. As a result, Scikit-learn stands out as a go-to toolkit for anyone looking to delve into the world of machine learning.

Components designed for international use and accessibility are available for all users. They undergo thorough testing to guarantee optimal performance and dependability. APIs are simple and ensure uniform behavior across different platforms. Developers are equipped with tools to create their own personalized components that utilize standard interaction patterns. Customization is possible while adhering to the Material Design guidelines. Developed by the Angular team, these components are intended to blend effortlessly with Angular applications. You can either build from the ground up or integrate them into your existing projects. Begin by designing the autocomplete panel along with the options that will be presented within it. Each option should be encapsulated in a mat-option tag, and the value property of each option can be set to determine the corresponding text input value when that option is selected. Additionally, consider adding unique styles or features to enhance the user experience further.

Blazor enables the creation of dynamic web user interfaces using C# rather than JavaScript. Its applications consist of modular web UI components crafted with C#, HTML, and CSS. You can write both the client-side and server-side code in C#, facilitating code and library sharing. As a component of ASP.NET, which is a widely-used web development framework, Blazor enhances the .NET developer ecosystem by providing tools and libraries tailored for web application development. Notably, Blazor can execute your client-side C# code within the browser via WebAssembly, allowing for the reuse of code and libraries from the server-side components of your application. Alternatively, client logic can be processed on the server, where client UI events are relayed back to the server using SignalR, a framework for real-time messaging. After processing, the necessary UI updates are sent back to the client and integrated into the Document Object Model (DOM), ensuring a seamless user experience. This capability of Blazor to combine client and server resources opens up new possibilities for developers looking to streamline their web applications.

Bunifu Framework UI tools offer a comprehensive suite for developing contemporary desktop applications efficiently. By utilizing Bunifu Framework UI tools, you can unleash your creativity, enhance your productivity, and reduce costs while working in Visual Studio .NET for C# and VB.NET. These tools empower you to realize any design concept you envision, thanks to the customizable properties that accompany each feature. Additionally, the efficient creation of various views within a form or user control can be achieved through the use of Bunifu pages. With the Bunifu Image Button, you can effortlessly introduce interactivity and animation to your images, enhancing user engagement. Furthermore, Bunifu Shapes allows for the straightforward design of various geometric figures, providing flexibility in your projects. You can also effectively deliver rich contextual notifications by utilizing Bunifu Tooltip, which comes with event support to enhance user interaction even further. Overall, Bunifu Framework UI tools streamline the app development process, making it accessible and dynamic for developers.

The h5py library serves as a user-friendly interface for the HDF5 binary data format in Python. It allows users to handle vast quantities of numerical data and efficiently work with it alongside NumPy. For instance, you can access and manipulate multi-terabyte datasets stored on your disk as if they were standard NumPy arrays. You can organize thousands of datasets within a single file, applying your own categorization and tagging methods. H5py embraces familiar NumPy and Python concepts, such as dictionary and array syntax. For example, it enables you to loop through datasets in a file or examine the .shape and .dtype properties of those datasets. Getting started with h5py requires no prior knowledge of HDF5, making it accessible for newcomers. Besides its intuitive high-level interface, h5py is built on an object-oriented Cython wrapper for the HDF5 C API, ensuring that nearly any operation possible in C with HDF5 can also be performed using h5py. This combination of simplicity and power makes it a popular choice for data handling in the scientific community.

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.

BeakerX is an ensemble of kernels and extensions designed to enhance the Jupyter interactive computing platform. It offers support for JVM and Spark clusters, facilitates polyglot programming, and includes features for creating interactive visualizations such as plots, tables, forms, and publishing capabilities. The APIs available for BeakerX encompass all JVM languages in addition to Python and JavaScript, enabling the creation of interactive time-series, scatter plots, histograms, heatmaps, and treemaps. Notably, the widgets maintain their interactivity in notebooks that are either saved locally or shared online, featuring distinctive tools to manage large datasets, nanosecond precision, zoom functionality, and options for exporting data. The table widget in BeakerX seamlessly identifies pandas data frames, granting users the ability to search, sort, drag, filter, format, select, graph, hide, pin, and export data to CSV or clipboard, thereby streamlining integration with spreadsheets. Additionally, BeakerX includes a Spark magic interface equipped with graphical user interfaces for monitoring configuration, status, progress, and interruption of Spark jobs, allowing users to choose between utilizing the GUI or writing code to create their own SparkSession. This flexibility makes BeakerX a powerful tool for data scientists and developers working with complex datasets.

CVXOPT is an open-source software library designed for convex optimization, leveraging the capabilities of the Python programming language. Users can interact with it through the Python interpreter, execute scripts from the command line, or incorporate it into other applications as Python extension modules. The primary goal of CVXOPT is to facilitate the development of convex optimization software by utilizing Python's rich standard library and the inherent advantages of Python as a high-level programming tool. It provides efficient Python classes for both dense and sparse matrices, supporting real and complex numbers, along with features like indexing, slicing, and overloaded operations for performing matrix arithmetic. Additionally, CVXOPT includes interfaces to various solvers, such as the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and solvers for linear, quadratic, and second-order cone programming available in MOSEK, making it a versatile tool for researchers and developers in the field of optimization. This comprehensive set of features enhances its utility in tackling a wide range of optimization problems.

The websockets library offers a comprehensive implementation of the WebSocket Protocol (RFC 6455 & 7692) for creating both WebSocket servers and clients in Python, emphasizing accuracy, simplicity, durability, and high performance. Utilizing asyncio, which is Python’s built-in asynchronous I/O framework, it presents a sophisticated coroutine-based API that streamlines development. The library has undergone extensive testing to ensure it meets the requirements outlined in RFC 6455, and its continuous integration process mandates that every branch achieves 100% coverage. Designed specifically for production environments, websockets was notably the first library to effectively address backpressure issues before they gained widespread attention in the Python ecosystem. Furthermore, it offers optimized and adjustable memory usage, and utilizes a C extension to enhance performance for demanding operations. The library is conveniently pre-compiled for Linux, macOS, and Windows, and is distributed in wheel format tailored for each system and Python version. With websockets managing the intricate details, developers can dedicate their efforts to building robust applications without concern for the underlying complexities. This makes it an essential tool for developers looking to harness the full potential of WebSocket technology.

Mako offers a user-friendly, non-XML syntax that compiles into Python modules, ensuring optimal performance. Its syntax and API draw inspiration from various sources, such as Django, Jinja2, Cheetah, Myghty, and Genshi, integrating the best elements from each. At its core, Mako functions as an embedded Python language (akin to Python Server Pages), enhancing conventional concepts of componentized layout and inheritance to create a highly efficient and adaptable model. This design maintains a close relationship with Python's calling and scoping semantics, allowing for seamless integration. Since templates are ultimately compiled into Python bytecode, Mako's methodology is remarkably efficient, having been designed to match the speed of Cheetah initially. Presently, Mako's performance is nearly on par with Jinja2, which employs a similar technique and was influenced by Mako. Furthermore, it can access variables from both its enclosing scope and the request context of the template, providing additional flexibility for developers. This capability allows for greater dynamic content generation in web applications.

Dask is a freely available open-source library that is developed in collaboration with various community initiatives such as NumPy, pandas, and scikit-learn. It leverages the existing Python APIs and data structures, allowing users to seamlessly transition between NumPy, pandas, and scikit-learn and their Dask-enhanced versions. The schedulers in Dask are capable of scaling across extensive clusters with thousands of nodes, and its algorithms have been validated on some of the most powerful supercomputers globally. However, getting started doesn't require access to a large cluster; Dask includes schedulers tailored for personal computing environments. Many individuals currently utilize Dask to enhance computations on their laptops, taking advantage of multiple processing cores and utilizing disk space for additional storage. Furthermore, Dask provides lower-level APIs that enable the creation of customized systems for internal applications. This functionality is particularly beneficial for open-source innovators looking to parallelize their own software packages, as well as business executives aiming to scale their unique business strategies efficiently. In essence, Dask serves as a versatile tool that bridges the gap between simple local computations and complex distributed processing.

Pyglet is a versatile and user-friendly library designed for Python, enabling the creation of games and visually engaging applications across various operating systems, including Windows, Mac OS X, and Linux. It offers a comprehensive range of features such as window management, event handling for user interfaces, support for joysticks, OpenGL graphics, image and video loading, as well as sound and music playback. The library boasts a user-friendly Pythonic API that is straightforward to grasp, ensuring a smooth development experience. Licensed under the BSD open-source license, pyglet allows for both commercial use and contributions to other open-source projects with minimal restrictions. It requires no external dependencies or complex installation processes, as it operates solely on Python, which streamlines both distribution and installation. This simplicity makes it convenient to bundle your project using tools like PyInstaller. Additionally, pyglet facilitates the use of genuine platform-native windows, giving developers the ability to leverage multiple windows and accommodate multi-monitor setups efficiently. With such capabilities, pyglet stands out as an excellent choice for developers looking to create rich multimedia applications in Python.

gTTS, which stands for Google Text-to-Speech, is a Python library and command-line interface tool that allows users to interact with the text-to-speech API provided by Google Translate. This tool enables users to write spoken audio data in mp3 format to various outputs, such as a file, a bytestring for additional audio processing, or even directly to stdout. Additionally, it offers the option to pre-generate URLs for Google Translate TTS requests, which can be utilized by other external applications. The library features a customizable tokenizer specifically designed for speech, allowing for arbitrary lengths of text to be processed while maintaining correct intonation, handling of abbreviations, decimal numbers, and more. Furthermore, it includes customizable text preprocessing capabilities that can address pronunciation issues, enhancing the overall quality of the speech output. With these diverse functionalities, gTTS serves as a versatile tool for generating high-quality spoken audio from text.

litex.regon serves as a user-friendly interface for the Polish REGON database by providing a straightforward, Python-based wrapper. To utilize its SOAP API, users must obtain a user key from the administrators of REGON. The REGONAPI requires just one argument, which is the service URL provided by these administrators. Once logged in, users can initiate queries against the database. Queries can be made using a single REGON number (which can be either 9 or 14 digits), a single 10-digit KRS number, or a single NIP (which consists of a 10-digit string). Furthermore, users can query collections of REGONs, KRSs, or NIPs, ensuring that all items in a collection conform to the respective length requirements. The method only processes one parameter at a time, prioritizing the first one provided from the list. Additionally, users can request a more comprehensive report by including the detailed=True parameter, which prompts the search method to return a default detailed report. If a user is familiar with the REGON of a specific business entity and the name of the detailed report, they can retrieve the complete report directly, enhancing the accessibility of information within the database. This feature makes litex.regon a valuable tool for anyone needing detailed insights into Polish business entities.

Hope UI, as the name suggests is a revolutionary admin dashboard that was built with the developer in mind. Hope UI Laravel Admin Dashboard Template is available with a UI component set. It features a modular component structure that makes it easy to design and launch web apps in the fastest possible way. Hope UI Admin Template is capable of developing lightweight web applications and admin panels. It also includes a Live Customizer that reduces development time and coding hours. The Hope UI Bootstrap Admin Dashboard is the future of admin UI. It will power your present and future development. Hope UI is available for 8 technologies: Bootstrap and Vue JS and React JS.

Zdaemon is a Python application designed for Unix-based systems, including Linux and Mac OS X, that simplifies the process of running commands as standard daemons. The primary utility, zdaemon, allows users to execute other programs in compliance with POSIX daemon standards, making it essential for those working in Unix-like environments. To utilize zdaemon, users must provide various options, either through a configuration file or directly via command-line inputs. The program supports several commands that facilitate different actions, such as initiating a process as a daemon, halting an active daemon, restarting a program after stopping it, checking the status of a running program, signaling the daemon, and reopening the transcript log. These commands can be entered through the command line or an interactive interpreter, enhancing user flexibility. Furthermore, users can specify both the program name and accompanying command-line options, though it's important to note that the command-line parsing feature is somewhat basic. Overall, zdaemon is a crucial tool for managing daemon processes effectively in a Unix environment.

Experience the speed of genuine Excel-like spreadsheet functionality without relying on Excel at all. You can develop a variety of financial applications, dashboards, charts, pivot tables, performance metrics, science lab notebooks, and other similar applications using JavaScript. These JavaScript spreadsheet components serve as essential tools for developers seeking to integrate Excel-like capabilities into their web applications. SpreadJS offers a comprehensive suite of JavaScript spreadsheet controls that feature capabilities such as import/export, data input management, cell personalization, and a powerful calculation engine equipped with more than 500 functions. With a rich history spanning over 25 years in creating award-winning spreadsheet solutions tailored for professional developers, we fully understand your requirements and desires. Our unparalleled experience in the spreadsheet domain sets us apart from competitors. Leverage our expertise to enhance your projects and streamline your development process today.

Appsmith is an open-source low code platform to build custom applications and internal tools. Appsmith has an intuitive drag and drop interface, along with the flexibility to connect databases and APIs. Add to this, the ease of sharing and collaborating with teammates. Build dashboards, admin panels, CRUD apps, forms, etc, and make them more dynamic and robust by writing custom logic with JavaScript.

Xafari serves as a comprehensive application framework tailored for .NET developers, offering a diverse array of components, modules, and utilities that enhance the functionality of the XAF (eXpressApp Framework) from DevExpress. This framework not only provides additional modules specifically for the DevExpress XAF UI, including Workplaces, Doc Panels, and Wizards, but it also enriches business logic with features like XafariModuleBase, AppModule, and application settings. Designed to facilitate the development of intricate business applications, Xafari supports both two-tier and three-tier architectures, making it a versatile choice. By subscribing for one year, developers gain access to an extensive toolkit of components aimed at streamlining business application development. You can experience it firsthand with a free 30-day trial, allowing you to dive into app creation immediately. With over 100 supplementary modules, more than 50 added functions and solutions, 40+ new editors, as well as 10+ examples and online BI platforms, the possibilities for innovation are vast. Additionally, Xafari includes a robust set of ERP components and offers support for WinForms, WebForms, and ASP.NET MVC platforms, ensuring a broad range of application development needs are met. Alongside these features, you can also count on qualified and responsive technical support to assist you throughout your development journey.

You have the option to access the complete Delphi source code. Explore the intuitive editor dialogs that are accessible during both design and run-time for nearly every component and its subcomponents. Steema is committed to providing products and services that fulfill your highest expectations for value and quality. Since 1995, we have been continuously innovating TeeChart components and aim to keep introducing exciting new features in the years ahead. Additionally, with the source code version of TeeChart, you can utilize FMXLinux to develop and adapt your charting applications for Linux when using Embarcadero Delphi 10.2 Tokyo or later. TeeChart is designed to automatically adjust and fit any screen size, making it ideal for dashboard creation where you can include multiple resizable charts on each panel. The FireMonkey framework effectively manages most variations across different platforms, and there are numerous examples available that demonstrate how to implement TeeChart in FireMonkey applications for various needs. This versatility ensures that developers can create visually appealing and functional charting solutions for a wide range of applications.

Sencha Ext JS is a comprehensive JavaScript framework designed for building data-intensive, cross-platform web applications. It offers a powerful collection of over 140 UI components, including grids, charts, forms, and pivot grids, to help developers create high-performance, responsive applications. Ext JS is known for its integrated tools like Sencha Architect and Themer, which accelerate the development process through drag-and-drop features and easy styling options. With robust support for testing and debugging, Ext JS ensures that developers can create scalable, maintainable applications faster and more efficiently.

FormVu provides HTML/JavaScript/CSS content for Chrome, Edge, Firefox, and Safari on Linux/MacOS/Windows and also mobile/tablet devices running Android or iOS. The PDF forms will appear in the Browser as they appeared in Acrobat with the correct layout, formatting, and styles. Embedded fonts are converted. FormVu supports both AcroForms and XFA Forms. All forms are converted into HTML5/CSS and JavaScript preserving style and layout. JavaScript is converted to run inside the browser, preserving validation and calculations in the forms. XFA FormCalc is also supported. FormVu provides an easy-to-use converter. It does not require a dedicated server or infrastructure and generates clean, standalone HTML content. FormVu is designed to integrate easily into the existing PDF workflow. Data can be edited, updated, and resaved back into the original PDF document or sent back to the server.

Bryntum provides high-performance web scheduling solutions. Our suite of JavaScript components--including Gantt, Scheduler, Task Board, and Calendar--enables developers to build modern project management applications with features like drag-and-drop scheduling, resource management, and interactive timelines. Flexible and rapid implementation is ensured by seamless integration with popular frameworks like React, Angular Vue and Ext JS. Bryntum solutions enable organizations to deliver robust and intuitive project planning tools to scale.

DevExpress UI components are designed to create elegant and high-impact user experiences that mimic the capabilities of the most popular business productivity apps. Our fully integrated suite of UI controls and reporting tools allows you to create high-performance analytics dashboards and decision support systems across all platforms and devices. DevExpress Reports are our royalty-free component library and reporting tool for the.NET ecosystem. DevExpress Reports include an intuitive Visual Studio report designer, runtime Report Designers for WinForms/WPF/Web and a rich set report controls, including cross tabs, charts and charts, so you and your users create reports of unparalleled elegance and informational clarity.

Dedupe.io serves as an innovative solution that effectively identifies similar entries within your data sets. By employing advanced machine learning techniques, we can swiftly and accurately pinpoint matches in your Excel files or databases, ultimately conserving both your time and financial resources. In an era dominated by vast amounts of data, the volume of information accessible for analysis has never been greater. However, managing this data can be challenging, particularly when it originates from various sources or has been manually inputted. The seemingly straightforward process of discerning individual identities within a spreadsheet or database can quickly become overwhelming and labor-intensive. This is precisely where Dedupe.io proves invaluable. We have crafted an optimal, dynamic, and scalable approach for eliminating duplicates and linking datasets, complemented by an intuitive step-by-step guide that makes it accessible for users of all skill levels. With Dedupe.io, you can streamline your data management process and make the most of your information effortlessly.

SVAR offers a collection of user interface components and widgets designed to streamline web application development using React, Svelte, and Vue frameworks. By using these ready-made UI tools, web developers can dramatically cut development time and costs while maintaining high-quality standards for their projects. SVAR UI components: - DataGrid: Build powerful, high-performance tables with features like inline editing, multi-column sorting, tree structures, context menu and keyboard navigation. - Gantt Chart: Add interactive task management and scheduling capabilities to your app. With intuitive drag-and-drop functionality, customizable timeline scales, and support for hierarchical subtasks, dependencies, and progress tracking, SVAR Gantt offers everything you need to visualize project workflows. - File manager: Add a user-friendly file explorer to your web app. Supports advanced features like split views, file previews, a built-in search box, and basic file operations such as copy, delete, upload, and download. - UI core library: Access a collection of essential UI controls, including buttons, date pickers, checkboxes, combo boxes, and popups. Build data-driven web apps faster and smarter with SVAR UI!

Experience a seamless development process with instant setup, utilizing the familiar technologies you already appreciate—JavaScript, HTML, and CSS. If you're concerned about the performance of PhoneGap or Cordova applications, there's no need to worry! Onsen UI ensures that all animations are finely tuned and optimized for smooth performance across a diverse range of devices. We prioritize delivering a fluid experience for apps created with Onsen UI, even on less powerful devices. This framework is not only straightforward to master but also a robust solution for developing intricate mobile applications. A wealth of learning materials is available, including comprehensive documentation, an interactive tutorial, and a supportive community forum where you can get your queries resolved. Onsen UI boasts a wide array of UI components specifically crafted for mobile applications, offering features like tabs, side menus, stack navigation, and numerous other components such as lists and forms, allowing developers to create user-friendly interfaces effortlessly. With its extensive toolkit, Onsen UI empowers you to design engaging mobile experiences with ease and confidence.

Accelerate your internal tools development. Low-code platform that allows developers to create internal tools in just minutes. SQL Generate allows you to input natural language and generate SQL statements. This works with databases such as MySQL, Postgre and Supabase. We give developers a great deal of freedom in implementing richer functionality with JavaScript. Wrapping JS statements using Template syntax allows them to place any string type variables at any space for more variety. ILLA is able to connect to any data via APIs or mainstream databases and add actions that are chained to user events. It integrates data from the backend with the frontend components. Developers can write simple data calls for massive information interaction.

Develop both the frontend and backend of a feature within a singular component, allowing the framework to determine the execution context. Nullstack equips you with comprehensive tools to maintain your focus on product development. Upon initial render, you will receive SEO-optimized HTML tailored for swift first paint of your route, all delivered in a single request utilizing local functions, without any JavaScript dependencies in the client bundle. Once the content is delivered and the network becomes idle, Nullstack JavaScript activates, restoring the application's state through hydration, transforming it into a single-page application. Future server functions will seamlessly retrieve JSON from an auto-generated microservice API, deserialize the data, refresh the application state, and automatically rerender the page without extra configuration. This holistic stack lifecycle, paired with a feature-focused approach, empowers you to produce clean, reusable code while eliminating the necessity for manual API creation, allowing for a more efficient development process. Additionally, this integration fosters a streamlined workflow that enhances collaboration and accelerates delivery timelines.

Material serves as a versatile framework of principles, elements, and resources that enhance user interface design practices. With its foundation in open-source code, Material fosters collaboration between designers and developers, enabling teams to efficiently create visually appealing products. Drawing inspiration from the tangible aspects of the world, such as textures and light dynamics, Material Design innovatively reinterprets traditional mediums like paper and ink. The approach is anchored in print design techniques, including typography, grids, spacing, scaling, color usage, and imagery, to establish hierarchy and meaning that engage users in a deeper experience. Additionally, motion plays a crucial role by directing focus and ensuring smooth continuity through subtle feedback and seamless transitions. As various components appear on the screen, they not only evolve but also reshape the surrounding environment, creating a dynamic interaction that leads to further transformations. This interconnectedness of design elements enhances the overall user experience, making it more immersive and enjoyable.

Bokeh is a sophisticated portfolio platform designed specifically for professional photographers that evolves alongside your creative journey. Transform your photo collection into an eye-catching website in no time. You can upload high-resolution images, organize galleries, and develop a professional portfolio that adapts to your growth. There's no need for complex page building or template editing; simply create a modern portfolio from your images. Bokeh handles the technical aspects for you. Enhance your online photo collection with intelligent albums, metadata, and additional features to elevate your portfolio. You can manually upload photos or directly publish client work and update your portfolio through Adobe Lightroom. Additionally, you can upload videos in stunning 4K resolution and seamlessly incorporate them with still images in your portfolio and client galleries. Bokeh optimizes your photos in a non-destructive manner, ensuring they are fast and visually impeccable on any device. Moreover, Bokeh leverages AI technology to help you achieve high rankings on Google and social media platforms effortlessly. This way, your work can reach a wider audience without requiring additional effort on your part.

Introducing an innovative reactive notebook designed for Python, which allows you to conduct repeatable experiments, run scripts seamlessly, launch applications, and manage versions using git. 🚀 Comprehensive: it serves as a substitute for jupyter, streamlit, jupytext, ipywidgets, papermill, and additional tools. ⚡️ Dynamic: when you execute a cell, marimo automatically runs all related cells or flags them as outdated. 🖐️ Engaging: easily connect sliders, tables, and plots to your Python code without the need for callbacks. 🔬 Reliable: ensures no hidden states, guarantees deterministic execution, and includes built-in package management for consistency. 🏃 Functional: capable of being executed as a Python script, allowing for customization via CLI arguments. 🛜 Accessible: can be transformed into an interactive web application or presentation, and functions in the browser using WASM. 🛢️ Tailored for data: efficiently query dataframes and databases using SQL, plus filter and search through dataframes effortlessly. 🐍 git-compatible: stores notebooks as .py files, making version control straightforward. ⌨️ A contemporary editor: features include GitHub Copilot, AI helpers, vim keybindings, a variable explorer, and an array of other enhancements to streamline your workflow. With these capabilities, this notebook elevates the way you work with Python, promoting a more efficient and collaborative coding environment.

Beautiful Soup is a powerful library designed for the easy extraction of data from web pages. It operates on top of HTML or XML parsers and offers Pythonic methods for navigating, searching, and altering the parse tree. Support for Python 2 was officially ended on December 31, 2020, which was a year after the official discontinuation of Python 2 itself. Consequently, all new development for Beautiful Soup will now focus exclusively on Python 3. The last version of Beautiful Soup 4 that supported Python 2 was 4.9.3. Additionally, Beautiful Soup is distributed under the MIT license, allowing users to download the tarball, place the bs4/ directory into nearly any Python application or library path, and begin utilizing it right away. This ease of integration makes Beautiful Soup a popular choice among developers working with web scraping.

Focos transforms your iPhone into a powerful photography tool that mimics the quality of DSLR cameras, featuring a large aperture and authentic bokeh effects that enthusiasts have long sought after. With the ability to capture portrait photos complete with depth data, users can adjust focus even after the image has been taken, akin to advanced technology used by professionals. The app offers a range of diaphragm settings that produce unique bokeh styles, while its professional features replicate the nuances of high-end lenses, showcasing options like creamy, bilinear, and swirly effects. The creamy bokeh, indicative of high-quality lenses, gives a softer edge to the blurred spots, whereas the bilinear effect can enhance certain areas despite being a less desirable outcome in other lenses. The swirly bokeh style emphasizes the focal point by surrounding it with a distinctive swirl pattern. Additionally, Focos includes an innovative lighting tool that allows you to visualize your portrait in a genuine 3D environment, enabling you to manipulate lights and fine-tune aspects like color and brightness, offering a level of versatility that surpasses the standard portrait lighting features provided by Apple. This makes Focos an invaluable asset for anyone looking to elevate their mobile photography experience significantly.