Alternatives to statsmodels

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

urllib3 is a powerful and user-friendly HTTP client that Python uses. You should use urllib3 as a client for your Python environment. Many critical features are missing from the Python standard library, and urllib3 provides them. Thread safety, connection pooling and client-side SSL/TLS verification. Multipart encryption is used for file uploads. Helpers for dealing with HTTP redirects and retrying requests. Support for deflate, gzip, and brotli encryption. Proxy support for HTTPS and SOCKS. 100% coverage of the test. urllib3 is one the most downloaded Python packages. It is a dependency on many popular Python packages such as Requests, Pip and more! urllib3 is available under the MIT License. API Reference documentation provides API-level documentation. The User Guide explains how to use the library to accomplish common tasks. For lower-level tweaking, the Advanced Usage Guide is a more detailed guide.

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.

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.

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).

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.

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.

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.

IMSL numerical libraries can improve performance and reduce development time. IMSL's tools allow you to achieve your strategic goals. Your IMSL library can be used to model regression, create decision trees, build neural networks, forecast time series, and make decisions. The IMSL C Numerical Library has been proven reliable and robust across all industries. It provides companies with a high-ROI solution to building cutting-edge analytics tools. The IMSL C Numerical Library is able to quickly add sophisticated functionality to your analytic applications, including data mining, forecasting, and advanced statistical analysis. Integration and deployment are easy with the IMSL C library. Easy migrations, support common platforms and combination of platforms, and no additional infrastructure to embed in applications or databases, all possible with the IMSL C library.

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.

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.

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.

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.

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.

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.

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.

High performance computing has become a more affordable resource for researchers in the scientific community over the past years. The popularity of clusters of workstations and clusters of Beowulf classes has been strongly influenced by the combination of high quality open-source software and cheap hardware. Message-passing is one of the most effective parallel computational models. This paradigm is especially suited for distributed memory architectures. It is used in today’s most complex engineering and scientific applications related to modeling, simulation and design. Because of the incompatible options developers had to choose from, portable message-passing parallel programming used to be a nightmare. This situation has changed significantly since the MPI Forum published its standard specification.

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.

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

Xlrd is a library that allows developers to extract data from Microsoft Excel™,.xls spreadsheet files. Xlrd is a library that reads and formats data from Excel files in the historical format.xls. This library cannot read files other than.xls. Charts, macros and pictures are ignored. However, formula calculations are extracted and comments, hyperlinks, advanced filters, pivot table, conditional formatting and data validation are all possible. This library cannot read password-protected files. This command will display the first, second, or last rows of each sheet within each file. xlrd is licensed by the BSD license.

The Adaptive calculation engine for Java ACE4J is a reliable platform that converts Excel-based applications to web applications at a low price, efficiently, and with easy maintenance and support in future. ACE4J is a modern formula engine that can evaluate complex Excel formulas. It is a great tool for Java-based Web applications that need heavy calculations. The Adaptive Calculation Engine, (ACE4J), is a Java API that allows you to evaluate formulas written in Microsoft Excel. This engine provides the most commonly used Microsoft Excel functions that are often encountered in applications that require complex calculations. Based on customer feedback, the number of available functions and formulas increases with each Adaptive Calculation engine release. Adaptive Calculation Engine can evaluate thousands of formulas in just seconds.

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.

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.

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.

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 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.

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.

DaisyUI is a Tailwind CSS library that improves development efficiency through semantic class names. It provides these names for UI components such as cards and toggles. This approach reduces the requirement to write extensive utility class, resulting in a cleaner and more maintainable HTML. DaisyUI is built upon Tailwind CSS and allows developers to customize components by using Tailwind's Utility Classes. It is a pure CSS plug-in that does not require JavaScript, which ensures compatibility with various JavaScript frameworks. It is easy to install and supports unlimited themes with customizable color names using CSS variables. This allows features like dark mode to be implemented without the need for additional class names. DaisyUI is built over Tailwind CSS, so you can customize all of it using utility classes. DaisyUI is an extension for Tailwind CSS. It works with all JS frameworks, and does not require a JS package file.

SQLite offers unparalleled performance and endless possibilities. SQLite Data Access Components, also known as LiteDAC, is a collection of components that allows native connectivity to SQLite using C++Builder and Delphi. It also includes Lazarus (and Free Pascal), as well as C++Builder and Community Edition. This library can be used on Windows, Linux and macOS as well as Android for 32-bit and 64 bit platforms. LiteDAC allows programmers to create truly cross-platform desktop or mobile SQLite databases applications without the need to deploy additional libraries. LiteDAC-based DB apps are simple to deploy and don't require additional data provider layers (such BDE or ODBC). They work faster than those based on standard Delphi data connectivity options. LiteDAC also allows you to directly work with SQLite and C++Builder by linking the client library statically to your application.

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.

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Oracle Data Access Components are a collection of Windows and.NET data accessibility drivers and tools. They support.NET data access, Microsoft Visual Studio tools to develop Oracle database applications, and ASP.NET providers. ODAC offers comprehensive client support for advanced Oracle database functionality. This includes performance, high availability, security, and many other features. Visual Studio is seamlessly integrated with ODAC to offer developers a seamless development experience. Oracle Data Provider is a Microsoft implementation of ADO.NET that provides access to Oracle databases. OLAP Data Manipulation Language is used to create and manipulate analytic workspace objects. It is a high-performance, feature-rich tool for Microsoft ADO and OLE DB access to Oracle databases. It also allows for its configuration and usage. This section provides information about the usage, installation, configuration, and post-installation.

Many domains have shown program autotuning to be more efficient and portable. Autotuners are not always portable between projects. This is because they need to be able to use a domain-informed search space representation. Also, no single search technique will work for all problems. OpenTuner is a new framework that allows you to create multi-objective, domain-specific program autotuners. OpenTuner allows for fully customizable configuration representations and extensible technique representations to allow for domain-specific methods. It also provides an easy-to use interface for communicating with the tuned programs. OpenTuner allows you to use multiple search techniques simultaneously. Techniques that perform well will get larger testing budgets while techniques that perform poorly will be disabled.

You can be confident that your application will stand the test of times, thanks to its foundation in next-generation frameworks such as Angular and Salesforce Lightning Design System. Our focus is on building stateless functional components that only depend on their input properties. This guarantees better performance, greater development flexibility, and seamless integration with your application requirements. To ensure that your product is accessible to all users, and meets all legal requirements, we have taken great care to adhere to Lightning Design System's accessibility guidelines. Your application must include SLDS CSS files as well as a small number of structural styles from CDK in order to function properly. You will need to add the following code to your angular.json file if you are using the Angular CSSLI.

React-Bootstrap is the most popular front-end framework. React-Bootstrap replaces Bootstrap JavaScript. Each component was built as a React component from scratch, with no unneeded dependencies such as jQuery. React-Bootstrap is one of the oldest React libraries. It has grown and changed with React, making it an excellent choice for your UI foundation. We built React-Bootstrap with compatibility in our mind. We embrace our bootstrap core, and strive to be compatible the largest UI ecosystem in the world. React-Bootstrap is based entirely on Bootstrap's stylesheet. This means that it works with all the Bootstrap themes you already love. React's component model allows us to have more control over the form and function each component. Each component is designed with accessibility in mind. The result is a set of accessible-by-default components, over what is possible from plain Bootstrap.

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.

Django-MySQL extends Django’s built-in MySQL support and MariaDB support. A cache backend that makes MySQL's upsert statements available and performs compression. Named locks allow for easy locking of e.g. External resources. Django's check framework has additional checks to ensure optimal Django/MySQL configurations. Django-MySQL includes a variety of extensions to QuerySet. These extensions can be installed in a variety of ways, e.g. QuerySetMixin can be added to an existing QuerySet subclass.

Quadratic allows your team to collaborate on data analysis and deliver faster results. You're already familiar with spreadsheets, but this is the first time you have had so much power. Quadratic is fluent in Formulas, Python and SQL (JavaScript & SQL coming soon). Use the language that you and your team are already familiar with. Single-line formulas can be difficult to read. Quadratic allows you to expand your recipes as many times as you want. Quadratic comes with Python library support. Bring the latest open source tools to your spreadsheet. The last line of the code is returned to your spreadsheet. By default, raw values, 1/2D arrays and Pandas DataFrames can be used. Quadratic updates its cells automatically when data is pulled or fetched from an external API. Zoom out to see the big picture and zoom in for the details. Arrange your data and navigate it the way you see it in your mind, not as a tool would have it.

TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.

Luminoth is an open-source toolkit for computer vision. We currently support object detection, but are working towards more. Luminoth is still an alpha-quality release. This means that the interfaces between the internal and external (such as command line) will likely change as the codebase matures. . You can install TensorFlow's GPU version with pip tensorflow.gpu or the CPU version with pip tensorflow. Luminoth can also install TensorFlow if you use pip install luminoth[tf]-gpu, depending on which version of TensorFlow.

PyRasgo, an open-source Python library, allows you to install Rasgo into your Python environment. Or, use our powerful, beautifully designed UI to get the Rasgo experience. You can create intuitive and detailed feature profiles in your panda's Rasgo UI or in its dataframe. Analyze key data statistics, quality issues, data drift, value distribution, and other data. Select features can be pruned to create a final set for modeling. Our extensive library of feature transformation functions can transform your raw data into useful features. Before you spend time training your model, visualize critical insights such as feature importance, explainability, and correlation. Collaborate with colleagues to create feature collection or duplicate existing feature collection to tailor for your model.