statsmodels Alternatives

Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.

The ROOT data analysis framework is used much in High Energy Physics (HEP) and has its own output format (.root). ROOT can be easily interfaced with software written in C++. For software tools in Python there exists pyROOT. Unfortunately, pyROOT does not work well with python3.4. broot is a small library that converts data in python numpy ndarrays to ROOT files containing trees with a branch for each array. The goal of this library is to provide a generic way of writing python numpy datastructures to ROOT files. The library should be portable and supports both python2, python3, ROOT v5 and ROOT v6 (requiring no modifications on the ROOT part, just the default installation). Installation of the library should only require a user to compile to library once or install it as a python package.

Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Imageio is written in pure Python, so installation is easy. Imageio works on Python 3.5+. It also works on Pypy. Imageio depends on Numpy and Pillow. For some formats, imageio needs additional libraries/executables (e.g. ffmpeg), which imageio helps you to download/install. If something doesn’t work as it should, you need to know where to search for causes. The overview on this page aims to help you in this regard by giving you an idea of how things work, and - hence - where things may go sideways.

The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.

PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. For a brief introduction to the ideas behind the library, you can read the introductory notes or the paper. Visit the installation page to see how you can download the package and get started with it. You can browse the example gallery to see some of the things that you can do with seaborn, and then check out the tutorials or API reference to find out how. To see the code or report a bug, please visit the GitHub repository. General support questions are most at home on StackOverflow, which has a dedicated channel for seaborn.

The cross-platform windowing and multimedia library for Python. pyglet is a powerful, yet easy-to-use Python library for developing games and other visually-rich applications on Windows, Mac OS X, and Linux. It supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images, and videos, and playing sounds and music. All of this with a friendly Pythonic API, that's simple to learn and doesn't get in your way. pyglet is provided under the BSD open-source license, allowing you to use it for both commercial and other open-source projects with very little restriction. No external dependencies or installation requirements. For most application and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. This makes it easy to package your project with freezers such as PyInstaller. pyglet provides real platform native windows, allowing you to take advantage of multiple windows and multi-monitor desktops.

Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.

Requests is a simple, yet elegant, HTTP library. Requests allows you to send HTTP/1.1 requests extremely easily. There’s no need to manually add query strings to your URLs, or to form-encode your PUT & POST data, but nowadays, just use the JSON method! Requests is one of the most downloaded Python packages today, pulling in around 30M downloads/week, according to GitHub, Requests is currently depended upon by 1,000,000+ repositories. You may certainly put your trust in this code. Requests is available on PyPI. Requests is ready for the demands of building robust and reliable HTTP–speaking applications, for the needs of today. Automatic content decompression and decoding. International domains and URLs. Sessions with cookie persistence. Browser-style TLS/SSL verification. Basic & digest authentication, and familiar dict–like cookies. Multi-part file uploads. SOCKS proxy support. Connection timeouts and streaming downloads.

pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data.

tox aims to automate and standardize testing in Python. It is part of a larger vision of easing the packaging, testing and release process of Python software. tox is a generic virtualenv management and test command-line tool you can use for checking that your package installs correctly with different Python versions and interpreters, running your tests in each of the environments, configuring your test tool of choice, and acting as a frontend to continuous integration servers, greatly reducing boilerplate and merging CI and shell-based testing. First, install tox with pip install tox. Then put basic information about your project and the test environments you want your project to run in into a tox.ini file residing right next to your setup.py file. You can also try generating a tox.ini file automatically, by running tox-quickstart and then answering a few simple questions. Install and test your project against Python2.7 and Python3.6.

Pexpect makes Python a better tool for controlling other applications. Pexpect is a pure Python module for spawning child applications; controlling them, and responding to expected patterns in their output. Pexpect works like Don Libes’ Expect. Pexpect allows your script to spawn a child application and control it as if a human were typing commands. Pexpect can be used for automating interactive applications such as ssh, FTP, passwd, telnet, etc. It can be used to automate setup scripts for duplicating software package installations on different servers. It can be used for automated software testing. Pexpect is in the spirit of Don Libes’ Expect, but Pexpect is pure Python. Unlike other Expect-like modules for Python, Pexpect does not require TCL or Expect nor does it require C extensions to be compiled. It should work on any platform that supports the standard Python pty module. The Pexpect interface was designed to be easy to use.

Enhance performance and save development time with IMSL numerical libraries. Achieve your strategic objectives using IMSL's build tools. Model regression, make decision trees, establish neural networks, and forecast time series with your IMSL library. Rigorously tested and proven for decades across all industries, the IMSL C Numerical Library gives companies a dependable, high-ROI solution for building cutting-edge analytics tools. From data mining and forecasting, to advanced statistical analysis, the IMSL C Numerical Library can help teams quickly add sophisticated functionality to analytic applications. The IMSL C library makes integration and deployment easy. Enjoy easy migrations, support for common platforms and platform combinations, and no added infrastructure on embed in databases or applications.

urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. urllib3 brings many critical features that are missing from the Python standard libraries. Thread safety, connection pooling, client-side TLS/SSL verification. File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, and brotli encoding. Proxy support for HTTP and SOCKS. 100% test coverage. urllib3 is one of the most downloaded packages on PyPI and is a dependency of many popular Python packages like Requests, Pip, and more! urllib3 is made available under the MIT License. The API Reference documentation provides API-level documentation. The User Guide is the place to go to learn how to use the library and accomplish common tasks. The more in-depth Advanced Usage guide is the place to go for lower-level tweaking.

Ruffus is a computation pipeline library for python. It is open-sourced, powerful and user-friendly, and widely used in science and bioinformatics. Ruffus is designed to allow scientific and other analyses to be automated with the minimum of fuss and the least effort. Suitable for the simplest of tasks. Handles even fiendishly complicated pipelines which would cause make or scons to go cross-eyed and recursive. No "clever magic", no pre-processing. Unambitious, the lightweight syntax which tries to do this one small thing well. Ruffus is available under the permissive MIT free software license. This permits free use and inclusion even within proprietary software. It is good practice to run your pipeline in a temporary, “working” directory away from your original data. Ruffus is a lightweight python module for building computational pipelines. Ruffus requires Python 2.6 or higher or Python 3.0 or higher.

Unirest is a set of lightweight HTTP libraries available in multiple languages, built and maintained by Kong, who also maintains the open-source API Gateway Kong. To utilize Unirest for node.js install the npm module. You're probably wondering how using Unirest makes creating requests easier. Besides automatically supporting gzip, and parsing responses, you can start with basic examples. A request can be initiated by invoking the appropriate method on the Unirest object, then calling .end() to send the request. Alternatively, you can send the request directly by providing a callback along with the URL. Provides simple and easy-to-use methods for manipulating the request prior to being sent. This object is created when a Unirest method is invoked. This object contains methods that are chainable like other libraries such as jQuery and popular request module Superagent (which this library is modeled after slightly).

This package is intended to be independently reusable in any Python project. It is maintained by the Zope Toolkit project. This package provides an implementation of “object interfaces” for Python. Interfaces are a mechanism for labeling objects as conforming to a given API or contract. So, this package can be considered as an implementation of the Design By Contract methodology support in Python. Interfaces are objects that specify (document) the external behavior of objects that “provide” them. An interface specifies behavior through informal documentation in a doc string, attribute definitions, and invariants, which are conditions that must hold for objects that provide the interface. Attribute definitions specify specific attributes. They define the attribute name and provide documentation and constraints of attribute values. Attribute definitions can take a number of forms.

xlrd is a library for developers to extract data from Microsoft Excel (tm) .xls spreadsheet files. xlrd is a library for reading data and formatting information from Excel files in the historical .xls format. This library will no longer read anything other than .xls files. Ignores charts, macros, pictures, any other embedded object, including embedded worksheets, VBA modules, and formulas, but results of formula calculations are extracted, comments, hyperlinks, auto filters, advanced filters, pivot tables, conditional formatting, and data validation. Password-protected files are not supported and cannot be read by this library. From the command line, this will show the first, second, and last rows of each sheet in each file. xlrd is licensed under the BSD license.

openpyxl is a Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files. It was born from a lack of an existing library to read/write natively from Python in the Office Open XML format. All kudos to the PHPExcel team as openpyxl was initially based on PHPExcel. By default, openpyxl does not guard against quadratic blowup or billion laughs XML attacks. To guard against these attacks install defusedxml. Install openpyxl using pip. It is advisable to do this in a Python virtualenv without system packages. Sometimes you might want to work with the checkout of a particular version. This may be the case if bugs have been fixed but a release has not yet been made. There is no need to create a file on the filesystem to get started with openpyxl. Just import the Workbook class and start work. Sheets are given a name automatically when they are created. Once you gave a worksheet a name, you can get it as a key of the workbook.

An implementation of the WebSocket Protocol (RFC 6455 & 7692). websockets is a library for building WebSocket servers and clients in Python with a focus on correctness, simplicity, robustness, and performance. Built on top of asyncio, Python’s standard asynchronous I/O framework, it provides an elegant coroutine-based API. websockets is heavily tested for compliance with RFC 6455. Continuous integration fails under 100% branch coverage. websockets is built for production. For example, it was the only library to handle backpressure correctly before the issue became widely known in the Python community. Memory usage is optimized and configurable. A C extension accelerates expensive operations. It’s pre-compiled for Linux, macOS, and Windows and packaged in the wheel format for each system and Python version. websockets takes care of everything under the hood so you can focus on your application!

waiting is a small library for waiting for stuff to happen. It basically waits for a function to return True, in various modes. Waiting is compatible with flux for simulated timelines. The most basic usage is when you have a function you want to wait for. Waiting forever is very simple. If your predicate returns a value, it will be returned as the result of wait(). A timeout parameter can also be specified. When a timeout expires without the predicate being fulfilled, an exception is thrown. Sleeping polls the predicate at a certain interval (by default 1 second). The interval can be changed with the sleep_seconds argument. When waiting for multiple predicates, waiting provides two simple facilities to help aggregate them, any and all. They resemble Python’s built-in any() and all(), except that they don’t call a predicate once it has been satisfied (this is useful when the predicates are inefficient and take time to complete).

It provides a familiar, non-XML syntax that compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics. As templates are ultimately compiled into Python bytecode, Mako's approach is extremely efficient and was originally written to be just as fast as Cheetah. Today, Mako is very close in speed to Jinja2, which uses a similar approach and for which Mako was an inspiration. Can access variables from their enclosing scope as well as the template's request context

Pygame is a set of Python modules designed for writing video games. Pygame adds functionality on top of the excellent SDL library. This allows you to create fully featured games and multimedia programs in the python language. Pygame is highly portable and runs on nearly every platform and operating system. Pygame is free. Released under the LGPL license, you can create open-source, freeware, shareware, and commercial games with it. With dual-core CPUs common, and 8-core CPUs cheaply available on desktop systems, making use of multi-core CPUs allows you to do more in your game. Selected pygame functions release the dreaded python GIL, which is something you can do from C code. Uses optimized C and assembly code for core functions. C code is often 10-20 times faster than python code, and assembly code can easily be 100x or more times faster than python code. Comes with many operating systems. Just an apt-get, emerge, pkg_add, or just install away.

Scapy is a powerful interactive packet manipulation program. It is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. It can easily handle most classical tasks like scanning, tracerouting, probing, unit tests, attacks, or network discovery (it can replace hping, 85% of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, p0f, etc.). It also performs very well at a lot of other specific tasks that most other tools can’t handle, like sending invalid frames, injecting your own 802.11 frames, combining technics (VLAN hopping+ARP cache poisoning, VOIP decoding on WEP encrypted channel), etc. Scapy runs natively on Linux, Windows, OSX, and on most Unixes with libpcap. The same code base now runs natively on both Python 2 and Python 3. Scapy development uses the Git version control system. Scapy reference repository is hosted on GitHub.

Over the last years, high performance computing has become an affordable resource to many more researchers in the scientific community than ever before. The conjunction of quality open source software and commodity hardware strongly influenced the now widespread popularity of Beowulf class clusters and cluster of workstations. Among many parallel computational models, message-passing has proven to be an effective one. This paradigm is specially suited for (but not limited to) distributed memory architectures and is used in today’s most demanding scientific and engineering application related to modeling, simulation, design, and signal processing. However, portable message-passing parallel programming used to be a nightmare in the past because of the many incompatible options developers were faced to. Fortunately, this situation definitely changed after the MPI Forum released its standard specification.

The Pylons web framework is designed for building web applications and sites in an easy and concise manner. They can range from as small as a single Python module, to a substantial directory layout for larger and more complex web applications. Pylons comes with project templates that help boot-strap a new web application project, or you can start from scratch and set things up exactly as desired. A framework to make writing web applications in Python easy. Utilizes a minimalist, component-based philosophy that makes it easy to expand on. Harness existing knowledge about Python. Extensible application design. Fast and efficient, an incredibly small per-request call stack provides top performance. Uses existing and well-tested Python packages. Pylons 1.0 series is stable and production-ready but in maintenance-only mode. The Pylons Project now maintains the Pyramid web framework for future development. Pylons 1.0 users should strongly consider using Pyramid for their next project.

Dash & Dash Enterprise let you build & deploy analytic web apps using Python, R, and Julia. No JavaScript or DevOps required. Through Dash, the world's largest companies elevate AI, ML, and Python analytics to business users at 5% the cost of a full-stack development approach. Deliver apps and dashboards that run advanced analytics: ML, NLP, forecasting, computer vision and more. Work in the languages you love: Python, R, and Julia. Reduce costs by migrating legacy, per-seat licensed software to Dash Enterprise's open-core, unlimited end-user pricing model. Move faster by deploying and updating Dash apps without an IT or DevOps team. Create pixel-perfect dashboards & web apps, without writing any CSS. Scale effortlessly with Kubernetes. Support mission-critical Python applications with high availability.

Enjoy the highest performance and unlimited possibilities when working with SQLite. SQLite Data Access Components (LiteDAC) is a library of components that provides native connectivity to SQLite from Delphi and C++Builder including Community Edition, as well as Lazarus (and Free Pascal) on Windows, Linux, macOS, iOS, and Android for both 32-bit and 64-bit platforms. LiteDAC is designed for programmers to develop truly cross-platform desktop and mobile SQLite database applications with no need to deploy any additional libraries. LiteDAC-based DB applications are easy to deploy and do not require the installation of other data provider layers (such as BDE or ODBC), and that's why they can work faster than the ones based on standard Delphi data connectivity solutions. Moreover, LiteDAC provides an additional opportunity to work with SQLite in Delphi and C++Builder directly by linking the client library statically in your application.

The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool. Pillow for enterprise is available via the Tidelift subscription. The Python Imaging Library is ideal for image archival and batch processing applications. You can use the library to create thumbnails, convert between file formats, print images, etc. The current version identifies and reads a large number of formats. Write support is intentionally restricted to the most commonly used interchange and presentation formats. The library contains basic image processing functionality, including point operations, filtering with a set of built-in convolution kernels, and color space conversions.

Sencha Ext JS is a comprehensive JavaScript application framework for building feature-rich, cross-browser-compatible web and mobile applications. It includes a library with 140+ high-performance customizable components, a set of tools and a powerful UI Framework. Key Features Rich UI Components – Includes a variety of pre-built UI elements such as grids and trees, menus and toolbars, forms and buttons, etc. Cross-platform compatibility - Supports major desktop and mobile web browsers including IE Firefox Chrome Safari and Opera. Data Packages – Includes data components to interact with various data sources including JSON, XML and database connections. Theming and Skinning - Allow easy skinning and theming of the UI with CSS. Development Tools - Includes an extensive set of development tools including a visual designer and debugger. Large Community - Has an active and large community of developers who provide support, extensions, etc.

We put much effort into making ngx-bootstrap modular so you can implement your templates, styles, whatnot. All components are designed with extensibility and adaptivity in mind. You can expect them to work on Mobile and Desktop with the same level of performance. We have incorporated a set of style guides and guidelines to enhance both code maintainability and readability. Also, we always support the latest Angular versions and provide full unit-test coverage. Being developers ourselves, we understand the importance of documentation. Well-written and continually updated docs significantly ease up the life of developers and improve overall software quality. We are doing our best to provide you with the most complete and easy-to-understand documentation out there. While working with visually rich libraries, you need to know what you are getting without going through the installation hassle. That is why we have developed a great set of demos for most of the component’s methods.

Oracle Data Access Components (ODAC) are a set of Windows and .NET data access drivers and tools. They include support for .NET data access, Microsoft Visual Studio tools for developing Oracle database applications; and ASP.NET providers. ODAC provides comprehensive client support for advanced Oracle database functionality, including performance, high availability, and security, among other features. It is tightly integrated with Visual Studio to provide a seamless development experience for developers. Oracle Data Provider for .NET is an implementation of Microsoft's ADO.NET interface and provides access to Oracle databases. OLAP Data Manipulation Language (OLAP DML) is used to define and manipulate analytic workspace objects. High performance, a feature-rich mechanism for Microsoft ADO and OLE DB data access to Oracle databases, its usage, and its configuration. Provides introductory, installation, post-installation configuration, and usage information.

Tool and library for handling Web ARChive (WARC) files. Naively join archives into one. Extract files from archive. List commands available. List contents of archive. Load archive and write it back out. Split archives into individual records. Verify digest and validate conformance. The library may not be entirely thread-safe yet. The goal of the Warcat project is to create a tool and library as easily and fast as manipulating any other archive such as tar and zip archives. Warcat is designed to handle large, gzip-ed files by partially extracting them as needed. Warcat is provided without warranty and cannot guarantee the safety of your files. Remember to make backups and test them! A WARC file contains one or more records concatenated together. Each record contains named fields, newline, a content block, newline, and newline. A Content Block may be two types, {binary data} or {Named Fields, newline, and binary data}.

The Adaptive Calculation Engine for Java ACE4J provides a reliable platform for converting Excel-based applications into web applications at a low cost, efficiently, and with guaranteed easy maintenance and support in the future. At the same time ACE4J is a modern formula language based on a robust and efficient calculation engine, that is capable of evaluating complex Excel formulas. Thus it is also a great tool for new Java based Web applications that require heavy calculations. The Adaptive Calculation Engine (ACE4J) is a Java API used to evaluate the formulas written in Microsoft Excel style. This engine provides the most popular Microsoft Excel functions which are frequently encountered in applications that require heavy calculations. The number of available formulas and features increases with every Adaptive Calculation Engine release based on feedback from our customers. Adaptive Calculation Engine is capable of evaluating thousands of formulas within seconds.

CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. Efficient Python classes for dense and sparse matrices (real and complex), with Python indexing and slicing and overloaded operations for matrix arithmetic. Interfaces to the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and the linear, quadratic and second-order cone programming solvers in MOSEK.

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Generators for classic graphs, random graphs, and synthetic networks. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Network structure and analysis measures.

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy).

python-docx is a Python library for creating and updating Microsoft Word (.docx) files. Paragraphs are fundamental in Word. They’re used for body text, but also for headings and list items like bullets. You’re free to specify both width and height, but usually, you wouldn’t want to. If you specify only one, python-docx uses it to calculate the properly scaled value of the other. This way the aspect ratio is preserved and your picture doesn’t look stretched. If you don’t know what a Word paragraph style is you should definitely check it out. Basically, it allows you to apply a whole set of formatting options to a paragraph at once. python-docx allows you to create new documents as well as make changes to existing ones. Actually, it only lets you make changes to existing documents; it’s just that if you start with a document that doesn’t have any content, it might feel at first like you’re creating one from scratch.

zdaemon is a Unix (Unix, Linux, Mac OS X) Python program that wraps commands to make them behave as proper daemons. zdaemon provides a script, zdaemon, that can be used to run other programs as POSIX (Unix) daemons. (Of course, it is only usable on POSIX-complient systems.) Using zdaemon requires specifying a number of options, which can be given in a configuration file, or as command-line options. It also accepts commands teling it what to do. Start a process as a daemon. Stop a running daemon process. Stop and then restart a program. Find out if the program is running. Send a signal to the daemon process. Reopen the transcript log. Commands can be given on a command line, or can be given using an interactive interpreter. We can specify a program name and command-line options in the program command. Note, however, that the command-line parsing is pretty primitive.

litex.regon, a frontend for Polish REGON database. Simple, pythonic wrapper for REGON database. To access its SOAP API, one needs a user key issued by REGON administrators. REGONAPI accepts one argument, the service URL (provided by REGON administrators). After login, one can start querying the database. Single REGON number (either 9 or 14 digits long), single 10 digit KRS number, single NIP (10 digits strings), collection of REGONs (all of them have to be either 14 or 9 digits long), collection of KRSs, collection of NIPs. Only one parameter is used in the query. If multiple ones are passed, first from the above list is taken into account. Additionally, a detailed parameter can be passed, detailed=True causes the search method to fetch the default detailed report. If one knows the REGON of a business entity and a detailed report name, a full report can be fetched directly.

Program autotuning has been demonstrated in many domains to achieve better or more portable performance. However, autotuners themselves are often not very portable between projects because using a domain-informed search space representation is critical to achieving good results and because no single search technique performs best for all problems. OpenTuner is a new framework for building domain-specific multi-objective program autotuners. OpenTuner supports fully customizable configuration representations, an extensible technique representation to allow for domain-specific techniques, and an easy-to-use interface for communicating with the tuned program. A key capability inside OpenTuner is the use of ensembles of disparate search techniques simultaneously, techniques that perform well will receive larger testing budgets, and techniques which perform poorly will be disabled.

The most popular front-end framework rebuilt for React. React-Bootstrap replaces Bootstrap JavaScript. Each component has been built from scratch as a true React component, without unneeded dependencies like jQuery. As one of the oldest React libraries, React-Bootstrap has evolved and grown alongside React, making it an excellent choice as your UI foundation. Built with compatibility in mind, we embrace our bootstrap core and strive to be compatible with the world's largest UI ecosystem. By relying entirely on the Bootstrap stylesheet, React-Bootstrap just works with the thousands of Bootstrap themes you already love. The React component model gives us more control over form and function of each component. Each component is implemented with accessibility in mind. The result is a set of accessible-by-default components, over what is possible from plain Bootstrap.

Built upon next generation frameworks like Angular and Salesforce's Lightning Design System, rest ​assured that you are building an application to stand the test of time. We focus on building stateless functional components that depend only on their input properties, guaranteeing better performance, more development flexibility and seamless integration with your application's requirements. We put a lot of effort to follow Lightning Design System's accessibility guidelines, to assure that your product is operable by people with a wide range of abilities and meets all legal requirements. Including SLDS CSS files and a small set of structural styles of CDK, is required for your application to work correctly. If you are using the Angular CLI, you need to add the following to the styles array of your angular.json file.

gTTS (Google Text-to-Speech), a Python library and CLI tool to interface with Google Translate's text-to-speech API. Write spoken mp3 data to a file, a file-like object (bytestring) for further audio manipulation, or stdout. Or simply pre-generate Google Translate TTS request URLs to feed to an external program. Customizable speech-specific sentence tokenizer that allows for unlimited lengths of text to be read, all while keeping proper intonation, abbreviations, decimals and more. Customizable text pre-processors which can, for example, provide pronunciation corrections.

Victory is a set of modular charting components for React and React Native. Victory makes it easy to get started without sacrificing flexibility. Create one-of-a-kind data visualizations with fully customizable styles and behaviors. Victory uses the same API for web and React Native applications for easy cross-platform charting. Fully contained, reusable data visualization elements are responsible for their own styles and behaviors. A React.js based library for creating sleek presentations using JSX syntax with the ability to live demo your code! Universal React Query Library is a blazing-fast GraphQL client, exposed as a set of ReactJS components. A physics-based animation library for React inspired by the natural world.

Django-MySQL extends Django’s built-in MySQL and MariaDB support their specific features not available on other databases. A new cache backend that makes use of MySQL’s upsert statement and does compression. Named locks for easy locking of e.g. external resources. Extra checks added to Django’s check framework to ensure your Django and MySQL configurations are optimal. Django-MySQL comes with a number of extensions to QuerySet that can be installed in a number of ways - e.g. adding the QuerySetMixin to your existing QuerySet subclass.

Explore the possibilities of your .NET enterprise apps with these dependency-free .NET spreadsheet components. .NET spreadsheet components are advanced software components that allow professional developers to add complete Excel-like functionality to their desktop applications. The .NET spreadsheet control includes support for Excel import/export, full cell customization, an extensive calculation engine with over 450 functions and more, all with zero dependencies on Excel. Leverage the extensive .NET spreadsheet API and powerful calculation engine to create analysis, budgeting, dashboard, data collection and management, scientific, and financial applications. Every platform of Spread.NET ensures maximum performance and speed for your enterprise apps, and its modular structure means you only need to add what you use to your .NET spreadsheet apps.

WTForms is a flexible forms validation and rendering library for Python web development. It can work with whatever web framework and template engine you choose. It supports data validation, CSRF protection, internationalization (I18N), and more. There are various community libraries that provide closer integration with popular frameworks. WTForms tries to provide as usable an API as possible. We’ve listed here some of the known libraries to work with WTForms, but if it’s not listed, it doesn’t mean it won’t work. Pretty much any ORM or object-DB should work, as long as data objects allow attribute access to their members. WTForms uses unicode strings throughout the source code and assumes that form input has already been coerced to unicode by your framework. WTForms fields render to unicode strings by default, and therefore as long as your templating engine can work with that, you should have no unicode issues.

QtitanSolution - includes the components for Qt.C++ development in the single distributive: QtitanDataGrid, QtitanRibbon, QtitanDocking, QtitanNavigationDesignUI, QtitanChart, QtitanFastInfoset. The solution is set up to get you started right away.