Alternatives to urllib3

If you are developing software for Logistics Dispatch Solutions, which contain challenges: -For staff dispatching, such as sales reps, mobile service, or workforce? -For truck shipment allocation in daily transportation and logistics (scheduling, tour optimization, etc.)? -For waste management and District Planning? -Generally, highly constrained problem sets? And your product does not have an automized optimization engine? Then JOpt is the perfect fit for your product and can help you to save money, time, and workforce, letting you concentrate on your core business. JOpt.TourOptimizer is an adaptable component to solve VRP, CVRP, and VRPTW class problems for any route optimization in logistics or similar fields. It comes as a Java library or in Docker Container utilizing the Spring Framework and Swagger.

Properties allow you to access all URL parts, such as scheme, user password, host, path, query, path, port, and password. All URL manipulations result in a new URL object. Strings passed to constructor or modification methods are automatically encoded and give canonical representations as a result. Regular properties are percent-decoded. To get encoded strings, you can use raw_ versions. As.human_repr(), URLs can be represented in a human-readable format. PyPI has binary wheels for Linux and MacOS. You can use the tarball to compile yarl from the source code if you want to install it on another operating system (such as Alpine Linux, which isn't manylinux-compliant due to the missing glibc). It requires Python headers and a C compiler. The pure-Python version (uncompiled) is slower. PyPy uses a pure Python implementation and is therefore unaffected by this variable.

Requests is an elegant and simple HTTP library. Requests makes it easy to send HTTP/1.1 queries. You don't need to manually add query strings or form-encode your PUT and POST data to your URLs. Instead, you can use the JSON method. Requests is the most downloaded Python package today, pulling in approximately 30M downloads per week, according to GitHub. Requests is currently dependent upon 1,000,000+ repositories. This code is certainly worth your trust. PyPI has Requests. Requests is available to meet the demands of building reliable and robust HTTP-speaking applications for today's needs. Automated content decompression and decoding. International URLs and domains. Sessions with cookie persistence. Browser-style TLS/SSL verification. Basic and digest authentication, as well as familiar dict-like cookies. Multi-part file uploads. SOCKS proxy support. Connection timeouts and streaming downloading.

CVXOPT, a free software package that allows convex optimization using the Python programming language, is available for download. It can be used with Python's interactive interpreter, the command line to execute Python scripts or integrated into other software via Python extension module. Its primary purpose is to simplify the development of software for convex optimization by using Python's extensive standard library as well as the strengths of Python, a high-level programming languages. Efficient Python classes that can handle dense and sparse (real and complicated) matrices. Includes Python indexing, slicing, and overloaded operations for matrix mathmetic. Interfaces to the linear programming solution in GLPK, semidefinite programming solvers DSDP5 and linear, quadratic, and second-order cone programming solutions in MOSEK.

Unirest is a collection of lightweight HTTP libraries that are available in multiple languages. It was created and maintained by Kong who also maintains the open source API Gateway Kong. Install the npm module to use Unirest for node.js. Unirest makes it easier to create requests. Unirest supports gzip and can parse responses. You can also start with basic examples. To initiate a request, invoke the appropriate method on Unirest object and then call.end() to send it. You can also send the request directly by sending a callback with the URL. This provides simple and straightforward methods to manipulate the request before it is sent. This object is created when Unirest is invoked. This object has methods that can be chained like other libraries, such as jQuery or the popular request module Superagent (which is slightly modeled after this library).

The ROOT data analysis framework can be used extensively in High Energy Physics (HEP). It also has its own output format (.root). ROOT can be interfaced with C++ software. pyROOT is a Python software tool. Unfortunately, pyROOT is not compatible with python3.4. broot is a small library which converts data from python numpy to ROOT files. These ROOT files contain trees with a branch each array. This library provides a generic way to convert python numpy datastructures into ROOT files. The library should be portable, and it should support python2, ROOT v5 or ROOT v6 (no modifications to the ROOT part required). The library should be easy to install. Users will only need to compile the library once.

Imageio is an image library written in Python that allows you to easily read and write a variety of image data including animated images, volumetrics data, and scientific formats. It runs on Python 3.5+ and is cross-platform. Imageio is written entirely in Python, making it easy to install. Imageio is compatible with Python 3.5+. It works with Pypy. Imageio is dependent on Numpy, Pillow. For some formats, imageio needs additional libraries/executables (e.g. Imageio can help you download/install ffmpeg. You need to know where to look for the causes of problems if something doesn't work. This overview will help you understand how things work and where they might go wrong.

It uses a familiar, non XML syntax and compiles into Python modules to maximize performance. Mako's syntax borrows from many other sources, including Jinja2 templates, Cheetah and Myghty, as well as the best ideas of Genshi and Django. Conceptually Mako is embedded Python (i.e. Python Server Page) language. It refines the familiar ideas o componentized layout and inheritance to create one of the most flexible and straightforward models. While still keeping close ties to Python scoping and calling semantics, Mako is conceptually an embedded Python (i.e. Mako's method is very efficient, and was originally designed to be as fast as Cheetah. Today Mako is very similar in speed to Jinja2, who uses a similar approach, and for which Mako was an inspiration. You can access variables from the template's request context as well as their enclosing scope.

Implementation of the WebSocket Protocol. RFC 6455 & RFC 7692. websockets is an open-source library that allows you to build WebSocket clients and servers in Python. It focuses on correctness and simplicity, robustness and performance. It is built on top of Python's standard asynchronous I/O framework asyncio and provides an elegant coroutine-based API. websockets has been rigorously tested to ensure compliance with RFC 6455. Continuous integration fails below 100% branch coverage. websockets was designed for production. It was the first library to correctly handle backpressure before the issue became well-known in the Python community. Memory usage is optimized and configurable. C extensions accelerate expensive operations. It is pre-compiled for Linux and macOS and packaged in the wheel format according to each Python version. websockets handles everything so you can concentrate on your application.

Matplotlib is a Python library that allows you to create interactive, animated, or static visualizations. Matplotlib makes difficult things simple and easy. Many third-party packages extend and build upon Matplotlib functionality. These include several higher-level plotting interfaces such as seaborn, HoloViews and ggplot.

The Python multi-platform windowing and multimedia library. pyglet, a powerful and easy-to-use Python library, allows you to create games and other visually rich applications on Windows, Mac OS X and Linux. It supports windowing, user event handling, Joysticks and OpenGL graphics. It also supports loading images and videos. This is all done with a friendly Pythonic API that's easy to use and doesn't get in the way. pyglet is available under the BSD open source license. This allows you to use it for commercial and open-source projects without restriction. No external dependencies or installation requirements. pyglet doesn't require any additional Python to meet most application or game requirements. This simplifies distribution and installation. This makes it easy for you to package your project using freezers like PyInstaller. pyglet offers real platform native windows that allow you to use multiple windows and multi-monitor desktops.

Pygame is a collection of Python modules that can be used to create video games. Pygame is an extension of the SDL library. This allows you create full-featured games and multimedia programs using the python programming language. Pygame is portable and can be used on almost every platform and operating system. Pygame is completely free. Pygame is free and open-source. You can use it to create commercial, freeware, shareware, or open-source games. Dual-core CPUs are common and 8-core CPUs easily available on desktop systems, multi-core CPUs allow you to do more with your game. Select pygame functions will release the dreaded Python GIL. This is something you can do with C code. Optimized C and assembly code are used for core functions. C code is often 10-20x faster than Python code, while assembly code can easily be 100x faster than Python code. It is compatible with many operating systems. You just need to apt-get or emerge.

Openpyxl is an open-source Python library that can read/write Excel 2010 files xlsx/xlsm/xltx/xltm. It was created because there wasn't an existing library that could natively read/write Python in the Office Open XML format. Openpyxl was originally built on PHPExcel. All credit to the PHPExcel team. Openpyxl doesn't guard against quadratic blowup attacks or billion laughs XML attacks by default. Defusedxml can be installed to protect against these attacks. Install openpyxl with pip This should be done in a Python virtualenv with no system packages. Sometimes, you may want to work with a particular version's checkout. This could be true if bugs have been fixed, but no release has been made. To get started with openpyxl, you don't need to create a file in the filesystem. Simply import the Workbook class to get started. When a sheet is created, it automatically gives it a name. You can give a worksheet a name to make it a key in the workbook.

Seaborn is a Python data visualization tool that uses matplotlib. It provides a high-level interface to draw attractive and informative statistical graphs. The paper and introductory notes provide a brief overview of the library's ideas. To download the package and get started, visit the installation page. To see some of the seaborn-related tasks, you can look through the example gallery. Then, check out the tutorials and API reference. Visit the GitHub repository to view the code and report a bug. You can find general support questions on StackOverflow. There is also a channel for seaborn.

The Pylons web framework was designed to make it easy and quick to build web applications and websites. They can be as simple as one Python module or as complex as a directory layout for larger, more complex web applications. Pylons includes project templates to help you set up a new web app project. Or, you can create your own and customize it as you wish. This framework makes it easy to write Python web applications. It is simple to expand on the minimalist, component-based philosophy. Use existing Python knowledge. Extensible application design. High performance, fast and efficient with a very small per-request stack. Uses well-tested Python packages. The Pylons 1.0 series is stable, production-ready, but in maintenance-only mode. The Pylons Project maintains the Pyramid web framework to support future development. Pylons 1.0 users are strongly encouraged to use Pyramid for their next project.

Web ARChive (WARC), files can be handled with this tool and library. Naively join archives into one. Extract files from archive. List commands available. List contents of archive. Write out the contents of the archive. Split archives into individual records. Verify the digest and verify conformance. The library may not yet be thread-safe. Warcat's goal is to create a tool that can be used to manipulate any archive, such as zip or tar archives, as quickly and as efficiently as other tools. Warcat can partially extract large files that have been gzip-ed. Warcat is not a warranty and cannot guarantee your files' safety. Make backups and make sure to test them! A WARC file is a collection of one or more records that are concatenated together. Each record has named fields, newline and a content block. A Content Block can be one of two types: binary data or named fields, newline and binary data.

gTTS (Google Text-to-Speech) is a Python library and CLI to interface with Google Translate’s text-to-speech API. For further audio manipulation or to write spoken mp3 data to files, you can use bytestring (file-like object) or stdout. You can also pre-generate Google Translate request URLs to feed an external program. A speech-specific sentence tokenizer that can be customized to allow for unlimited text lengths, while maintaining proper intonation, abbreviations and decimals. You can also make pronunciation corrections with custom-designed text pre-processors.

Beautiful Soup is a library that allows you to easily scrape information from web pages. It sits atop an HTML/XML parser and provides Pythonic idioms to iterate, search, and modify the parse tree. Beautiful Soup's support of Python 2 was terminated on December 31, 2020, one year after the sunset date. New Beautiful Soup development will now exclusively target Python 3. Beautiful Soup 4's final release to support Python 2 was 4.9.3. Beautiful Soup is licensed under MIT license. You can download the tarball and drop the bs4/ directory in almost any Python program (or into your library path), and then start using it immediately.

statsmodels is an Python module that provides classes, functions, and methods for the estimation of various statistical models. It also allows for statistical data exploration and statistical tests. Each estimator has a comprehensive list of available result statistics. To ensure accuracy, the results are compared to existing statistical packages. The package is available under the Modified BSD (3 clause) license. statsmodels allows you to specify models using R-style formulas or pandas DataFrames. To see the available results, take a look at dir (results). Results describe attributes. __doc__, results methods have their own documentation strings. Numpy arrays can be used in place of formulas. Installing statsmodels as part of the Anaconda distribution is the easiest way to do so. This cross-platform distribution allows for data analysis and scientific computing. This is the preferred method of installation for most users.

Pexpect makes Python an easier tool for controlling other programs. Pexpect can be used to create child applications, control them and respond to their output. Pexpect works like Don Libes' Expect. Your script can use Pexpect to create a child application. You can also control it like a human would. Pexpect is a tool that automates interactive applications like ssh and FTP, passwd and telnet. It can also be used to automate setup scripts that duplicate software package installations on different servers. It can also be used to automate software testing. Pexpect has a similar spirit to Don Libes' Expect but is pure Python. Pexpect is not like other Expect-like Python modules. It doesn't require Expect or TCL to be compiled. It should work on any platform that can support the standard Python pty modules. The Pexpect interface is easy to use.

NetworkX is a Python package that allows you to create, manipulate, and study the structure, dynamics, as well as the functions, of complex networks. Generators for classic, random, and synthetic graphs. Python offers additional benefits such as fast prototyping and easy teaching. Network structure and analysis measures.

Ruffus is a Python computation pipeline library. It is open-sourced and powerful, user-friendly, and widely used for science and bioinformatics. Ruffus was designed to automate scientific and other analyses with minimal fuss and effort. It is suitable for even the most basic tasks. Even complex pipelines can be handled. This will prevent make or scons from becoming cross-eyed and recursive. No "clever magic", no pre-processing. The lightweight syntax, which does one small thing well, is unambitious. Ruffus is licensed under the permissive MIT-free software license. This license allows for free use and inclusion in proprietary software. It is a good idea to run your pipeline in a temporary directory that is not connected to your original data. Ruffus is a lightweight Python module that can be used to build computational pipelines. Ruffus requires Python 2.6 and higher, or Python 3.0 and higher.

This package can be used in any Python project independently. It is maintained by Zope Toolkit. This package implements Python's "object interfaces". Interfaces allow objects to be labeled as conforming to a contract or API. This package can be considered an implementation of Python's Design By Contract support. Interfaces are objects that document the external behavior of objects "provided" by them. An interface describes behavior through informal documentation, such as doc strings, attribute definitions and invariants. These are conditions that must be met for objects to provide the interface. Attribute definitions specify specific attributes. They provide documentation and constraints for attribute values. There are many ways to define attributes.

Tox aims automate and standardize Python testing. It is part of a larger vision to simplify the packaging, testing, and release of Python software. Tox is a generic virtualenv management tool and test command-line tool that you can use to verify that your package works with different Python versions. You can also run your tests in each environment. It also acts as a frontend for continuous integration servers, reducing boilerplate and merging CI. First, install tox using pip install tox. Next, add basic information about your project as well as the test environments that you would like your project to run into a tox.ini.py file. To generate a tox.ini automatically, run tox-quickstart. Answer a few questions. Test your project against Python2.7 or Python3.6.

The Python Imaging Library provides image processing capabilities for your Python interpreter. This library supports many file formats, an efficient internal representation, as well as powerful image processing capabilities. The core image library allows for quick access to data stored only in basic pixel formats. It should be a solid foundation for an image processing tool. Tidelift subscribers can get Pillow for Enterprise. The Python Imaging Library is perfect for batch processing and image archival applications. The library can be used to create thumbnails, convert file formats, and print images. The current version can identify and read a wide range of formats. The most common interchange and presentation formats are the only ones that support writing. The library includes basic image processing functionality such as point operations, filtering using a set of convolution kernels and color space conversions.

python_docx is a Python library that allows you to create and update Microsoft Word (.docx), files. Word's fundamental structure is the paragraph. They are used for body text as well as headings and list items such bullets. Although you can specify width and height, it is not recommended. If you only specify one, python docx uses it for the correct scaled value of both. This ensures that your image doesn't look stretched and preserves the aspect ratio. You should learn what a Word paragraph format is. It allows you to apply multiple formatting options to a paragraph at a time. Python-docx can be used to create new documents and make changes to existing documents. It only allows you to make changes to existing documents. However, if you start with a blank document, it may feel like you are creating one from scratch.

Python-sql allows you to create SQL queries in a pythonic manner. Select with where condition, simple selects Select with multiple joins or with join. Select with group_by or select with the output name Select with order_by or sub-select. Select another schema and insert query using default values. Insert query with query and values. Update query with values. Update query with where condition. Update query with from list. Delete query with where condition and delete query using sub-query. Provides limit style and qmark style as well as numeric style.

Waiting is a small library that waits for things to happen. It simply waits for a function in various modes to return True. Flux can be used to simulate timelines. Waiting is compatible. When you have a function that you need to wait for, waiting is the most basic use. It is easy to wait forever. If your predicate returns value, it will be returned by wait(). You can also specify a timeout parameter. An exception is made if the timeout expires and the predicate has not been fulfilled. The predicate is polled at a specified interval (default 1 second). You can change the interval with the sleep_seconds argument. Waiting provides two simple options to aggregate multiple predicates. They are similar to Python's built in any() and all() but don't call predicates once they have been satisfied. This is useful for predicates that are slow or inefficient.

The NumPy vectorization and indexing concepts are fast and flexible. They are the current de-facto standard in array computing. NumPy provides comprehensive mathematical functions, random numbers generators, linear algebra routines and Fourier transforms. NumPy is compatible with a wide variety of hardware and computing platforms. It also works well with sparse array libraries, distributed, GPU, or GPU. NumPy's core is C code that has been optimized. Enjoy Python's flexibility with the speed and efficiency of compiled code. NumPy's high-level syntax makes it easy for programmers of all backgrounds and experience levels. NumPy brings the computational power and simplicity of languages such as C and Fortran into Python, making it a language that is much easier to learn and to use. This power is often accompanied by simplicity: NumPy solutions are often simple and elegant.

PyQtGraph is a pure Python graphics and GUI library based on PyQt/PySide or NumPy. It is intended for use in mathematics/scientific/engineering applications. Although written entirely in Python, the library is extremely fast thanks to its heavy use of NumPy to perform number crunching and Qt GraphicsView framework for fast display. PyQtGraph is available under the MIT open source license. Interactive view boxes for basic 2D plotting. Line and scatter plots. Data can be scaled/panned with the mouse. Rapid drawing allows for real-time data display. Displays all data types (int, float, any bit depth, RGB, RGBA or luminance). Multidimensional images can be sliced at arbitrary angles using these functions (great for MRI data). Rapid update for video display and real-time interaction Image display with interactive level control and lookup tables. Mesh rendering with isosurface generator. Interactive viewports can be rotated/zoomed with the mouse. For easier programming, use the basic 3D scenegraph.

Gevent is a Python networking library that uses coroutine. It uses greenlet to provide an API for high-level synchronous APIs on top of the event loops libev and libuv. Gevent is inspired by Eventlet, but has a more consistent API and simpler implementation. It also offers better performance. See why gevent is used by others and see the list of open-source projects that are based on gevent.

WTForms allows you to easily validate and render forms for Python web development. It works with any web framework or template engine. It supports data validation, CSRF Protection, Internationalization (I18N), among other features. There are many community libraries that allow for closer integration with popular frameworks. WTForms strives to make APIs as easy as possible. WTForms can be used by a variety of libraries. However, if a library is not listed it doesn't necessarily mean it won't work. Any ORM or object-DB should be able to work as long as they allow access to members via data objects. WTForms uses unicode string throughout the source code. It assumes that input to forms has been forced to unicode by your framework. WTForms fields default to unicode strings. As long as your templating engine is capable of handling that, you should not have unicode issues.

The h5py package provides a Pythonic interface for the HDF5 binary data format. It allows you to store large amounts of numerical data and allow you to easily manipulate that data using NumPy. You can cut into multi-terabyte datasets on disk as if they were NumPy arrays. You can store thousands of datasets in one file. You can categorize and tag them however you like. H5py makes use of simple NumPy and Python metaphors like dictionary syntax and NumPy array syntax. You can, for example, iterate over files or examine the.shape and.dtype attributes of data. To get started, you don't need any knowledge about HDF5. In addition to an easy-to-use interface, h5py relies on an object-oriented Cython wrap of the HDF5 CAP API. You can do almost anything from C in HDF5 with h5py.

Parsel is a BSD licensed Python library that extracts and removes data from HTML and XML. It uses XPath, CSS selectors and regular expressions. Make a selector object to parse the HTML or XML text. Next, use CSS or XPath expressions for selecting elements. CSS is a language that allows you to apply styles to HTML documents. It defines selectors that allow you to associate styles with specific HTML elements. XPath, which can be used with HTML, is a language that allows you to select nodes from XML documents. You can choose to use CSS or XPath. While CSS is more readable than XPath, some things cannot be done with XPath. Parsel selectors are built on top of lxml and support certain EXSLT extensions. They also come with pre-registered namesspaces for use in XPath statements. Parsel selectors let you chain selectors. This means that you can select by class using CSS, and then switch to XPath if necessary.

Scapy is an interactive packet manipulation program. It can forge and decode packets from a variety of protocols, send them over the wire, capture them and match requests and responses. It can handle most of the classic tasks such as scanning, tracerouting and probing, attacks, or network detection (it can replace Hping, 85% nmap, arpspoofsk, arping), tcpdumpshark, p0f and tshark). It can also handle a lot more specific tasks than most other tools, such as sending invalid frames, injecting 802.11 frames, combining technologynics (VLAN hopping+ARP caching poisoning, VOIP descoding on WEP encrypted channel), and so forth. Scapy works natively on Linux and Windows as well as OSX and most Unixes that have libpcap. The same code base runs natively on Python 2 and Python 3 Scapy development uses Git version control system. The GitHub repository hosts the Scapy reference repository.

Blazor allows you to create interactive web UIs with C# instead JavaScript. Blazor apps consist of reusable web UI components that are implemented using HTML, CSS, and C#. C# is used to write both client and server code, which allows you to share code as well as libraries. Blazor is a feature in ASP.NET, the popular web-development framework. It extends the.NET platform with tools and libraries to build web apps. Blazor allows you to run client-side C# code in your browser using WebAssembly. It's real.NET running in WebAssembly so you can reuse code and libraries from the server-side of your application. Blazor can also run your client logic on the web server. SignalR - a real time messaging framework - is used to send client UI events back to the server. After execution is complete, the required UI modifications are sent to clients and merged into DOM.

WebDataRocks, a free JS library that creates functional pivot tables with ease of use, is a simple and straightforward JS library. It can be used in conjunction with Angular Vue React or other frameworks. Free Customization is flexible JavaScript client-side component Loads up to 1MB of JSON and CSV data files Enterprise features in full Integration with third party charting libraries Enterprise features in full For efficient data management, you can use features like filtering and sorting, number formatting, conditional formatting, calculated values and totals. It allows you to print or export web reports in PDF, Excel, or HTML by using just one click. Modern UI ready-to-use The tool has a spreadsheet-like interface that is optimized for both browsers and mobile apps. This web reporting tool already incorporates all the principles of reliability and an excellent user experience.

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GuideChimp is easily integrated with any web application and can be dropped into your application using Vue.js or Angular, plain JavaScript, HTML, or plain JavaScript. GuideChimp can be customized using SCSS and clean CSS to make it look like an integral part your product. GuideChimp can be extended using third-party plugins and out-of-the box plugins. These plugins enhance functionality, usability, feedback, analytics, and more. tools. GuideChimp is well-documented. The open-source library is easy and has a short learning curve. GuideChimp is easy to use and robust enough that it can deliver results quickly. It takes only 3 minutes to set it up! Configure GuideChimp to look and feel like an integral part your software product. Add a beacon to any element of the web page to grab their attention.

Cryptography can include both high-level instructions and low-level interfaces for common cryptographic algorithms like symmetric ciphers and message digests. Use cryptography's high level symmetric encryption recipe to encrypt. Cryptography can be broadly divided into two levels. One that uses safe cryptographic recipes and requires very few configuration options. These are safe and simple to use, and don't require developers make many decisions. The second level is low-level cryptographic primitives. These can be dangerous and could be misused incorrectly. These require the ability to make decisions and have a deep understanding of cryptographic concepts. This layer is known as the "hazardous materials" (or "hazmat") because of the danger involved in working at this level. These materials live in the cryptography.hazmat packaging, and their documentation will always include an admonition at its top.

We have put a lot of effort into making ngx_bootstrap modular. This allows you to implement your templates, styles, and whatnot. All components are designed with adaptability and extensibility in mind. They will work on both Mobile and Desktop with equal performance. To improve code readability and maintainability, we have included a set style guidelines and guidelines. We provide full coverage for unit-test coverage and support all Angular versions. We are developers ourselves so we know the importance of documentation. Documentation that is well-written and regularly updated can greatly simplify the lives of developers and improve the quality of software. We do our best to provide the best documentation possible. You need to understand what you are getting when working with visually rich libraries. We have created a set of great demos for the majority of the component's methods.

Semantic UI React, the official React integration for Semantic UI, is Semantic UI React. jQuery-free declarative API, augmentation and sub-components. Auto-controlled state. jQuery is a DOM manipulator library. It can read from and write to the DOM. React uses a virtualDOM (a JavaScript representation) of the real DOM. React writes only patch updates to the DOM and never reads from it. React's virtual DOM makes it impossible to keep real DOM manipulations in sync. React has reimplemented all jQuery functionality. You can control the rendered HTML tag or render one component as another. Additional props are passed to your component. Augmentation is powerful. Composing component features and props is possible without the need to add nested components. Shorthand props can generate markup for your use, making it easy to create many different uses cases. All object props can be spread on the child parts.

More than 1,600 components and frameworks are included for Windows Forms (WPF, ASP.NET Core), UWP and WinUI (Web Forms MVC, Core), UWP and WinUI (Xamarin and Flutter), Angular, Blazor and Vue, and React. You will find the most requested components like charts, grids and schedulers, diagrams maps gauges docking, ribbons and more! To streamline your business, we work with the best and brightest minds in the industry.

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

Any app development project's time to market is crucial. Many developers, agencies, and enterprises slow down innovation by spending countless hours creating core functionality from scratch and increasing development timelines. If you can get the Features you need for your app out of the box, you can start development quickly. You can cut down on development time by up to 80% When you use Onymos' ready-made, full-stack capabilities, your app can be deployed in days instead of months. Onymos features take over 1000 hours to develop on average, and that number is only growing. Our features are updated as software and APIs are updated. Front-end logic, UI/UX and integrated cloud services such as Stripe, APNs and Amazon S3. You get everything when you use Onymos features. Onymos is used by companies like Walmart, CVS Pharmacy, Walmart, and Albertsons to build their apps.

Pandas is an open-source data analysis and manipulation tool that is fast, flexible, flexible, and easy to use. It was built on top the Python programming language. Tools for reading and writing data between memory data structures and various formats: CSV, text files, Microsoft Excel, SQL databases and the fast HDF5 format. Intelligent data alignment and integrated handling missing data: Use a powerful group engine to perform split-apply/combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. You can even create domain-specific offsets and join time sequences without losing data.

Bokeh allows you to create simple plots but can also handle custom or specialized use cases. Apps, dashboards and plots can be published on web pages or in Jupyter notebooks. Python offers a wide range of powerful analytics tools, including NumPy and Scipy, Pandas. Scikit-Learn, OpenCV and Scikit-Learn. Bokeh server allows you to connect these tools to rich interactive visualizations in your browser. It has a wide range of widgets, plot tools and UI events that trigger Python callbacks. Researchers at Monash University maintain Microscopium. Researchers can use it to explore large image datasets using Bokeh's interactive tools. Panel is a tool that allows for polished data presentation and makes use of the Bokeh server. Anaconda created it and supports it. Panel allows you to easily create interactive web apps and dashboards using user-definable widgets. These widgets can be connected to plots, images or tables, text, or any other data.

zdaemon, a Unix (Unix Linux, Mac OS X, Mac OS X), Python program, wraps commands to make them behave like proper daemons. zdaemon offers a script, zdaemon that can be used to execute other programs as POSIX(Unix) daemons. It is only compatible with POSIX systems. Using zdaemon means that you need to specify a number options. These options can be given as either a configuration file or as command-line options. It can also accept commands that tell it what to do. Start a process by creating a daemon. Stop a daemon process. Stop and then start a program. Check if the program is still running. Send a signal for the daemon process. The transcript log can be reopened. You can give commands on a command-line or by using an interactive interpreter. The program command can include a program name and options. However, the command-line parsing can be quite primitive.

Litex.regon is a frontend to the Polish REGON database. Simple, pythonic wrapper to REGON database. REGON administrators issue a user key to access the SOAP API. REGONAPI only accepts one argument: the service URL, which is provided by REGON administrators. Once you have logged in, you can query the database. One REGON number (9 or 14 digits in length), single 10 digit KRS Number, single NIP (10 characters strings), collection REGONs (all must be 14 or 9 digits in length), collection KRSs, and collection of NIPs. The query only uses one parameter. If more than one parameter is passed, the first one from the list above will be considered. You can also pass a detailed parameter. detailed=True will cause the search method to fetch a default detailed report. A full report can be obtained if one has the REGON and name of the business entity.

Altair Engineering, Inc. is not affiliated with the Vega-Altair open-source projects. Altair's API is easy to use, consistent, and friendly. It is built on top VegaLite's powerful visualization grammar. This simple design produces beautiful and efficient visualizations with minimal code. The idea behind linking data columns to visual encoding channels is the key. All other details of the plot are handled automatically. This declarative plotting idea allows for a surprising variety of plots and visualizations. It is possible to create them using relatively simple grammar.