yarl Alternatives

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.

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!

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.

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.

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.

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.

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.

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.

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.

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.

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.

Luminoth is an open source toolkit for computer vision. Currently, we support object detection, but we are aiming for much more. : Luminoth is still alpha-quality release, which means the internal and external interfaces (such as command line) are very likely to change as the codebase matures. . If you want GPU support, you should install the GPU version of TensorFlow with pip install tensorflow-gpu, or else you can use the CPU version using pip install tensorflow. Luminoth can also install TensorFlow for you if you install it with pip install luminoth[tf] or pip install luminoth[tf-gpu], depending on the version of TensorFlow you wish to use.

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.

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.

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.

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

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.

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.

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.

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.

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.

The Polymer library provides a set of features for creating custom elements. These features are designed to make it easier and faster to make custom elements that work like standard DOM elements. Similar to standard DOM elements, Polymer elements can be instantiated using a constructor or document creation element, configured using attributes or properties, populated with internal DOM inside each instance, responsive to property and attribute changes, styled with internal defaults or externally, and responsive to methods that manipulate its internal state. Registering an element associates a class with a custom element name. The element provides callbacks to manage its lifecycle. Polymer also lets you declare properties, to integrate your element's property API with the Polymer data system. Shadow DOM provides a local, encapsulated DOM tree for your element. Polymer can automatically create and populate a shadow tree for your element from a DOM template.

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.

Parsel is a BSD-licensed Python library to extract and remove data from HTML and XML using XPath and CSS selectors, optionally combined with regular expressions. Create a selector object for the HTML or XML text that you want to parse. Then use CSS or XPath expressions to select elements. CSS is a language for applying styles to HTML documents. It defines selectors to associate those styles with specific HTML elements. XPath is a language for selecting nodes in XML documents, which can also be used with HTML. You can use either CSS or XPath. CSS is usually more readable, but some things can only be done with XPath. Being built atop lxml, parsel selectors support some EXSLT extensions and come with pre-registered namespaces to use in XPath expressions. Parsel selectors allow you to chain selectors, so most of the time you can just select by class using CSS and then switch to XPath when needed.

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.

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.

statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.

Universal Data Access Components (UniDAC) is a library of components that provides direct access to multiple databases 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. Key Features: Universal access to different database servers; Support for most popular databases; Full support for the latest server versions; Support for the latest IDE versions; VCL, LCL and FMX versions of library available; High performance; Easy to deploy.

Full 100% Delphi source code is available to you as an option. Discover the user-friendly editor dialogs, available both at design time and also run-time, for almost every component and sub-component. Steema provides products and services aimed at meeting your highest expectations on getting the best value for your money. We have been innovating for TeeChart components since 1995 and endeavor to continue to bring you the best of new features in the future. You can also use TeeChart (sourcecode version only) with FMXLinux to port/build your charting applications to/for Linux with Embarcadero Delphi 10.2 Tokyo and up. TeeChart will scale and fit to any screen size. If you're building dashboards you can place multiple, resizeable charts on each dashboard panel. FireMonkey framework will handle most of the variations for the different platforms. See examples showing how to use TeeChart for FireMonkey apps.

Enjoy the highest performance and unlimited possibilities when working with SQL Server. SQL Server Data Access Components (SDAC) is a library of components that provides native connectivity to SQL Server from Delphi and C++Builder including Community Edition, as well as Lazarus (and Free Pascal) for Windows, Linux, macOS, iOS, and Android for both 32-bit and 64-bit platforms. SDAC-based applications connect to SQL Server directly through OLE DB, which is a native SQL Server interface. SDAC is designed to help programmers develop faster and cleaner SQL Server database applications. SDAC, a high-performance, and feature-rich SQL Server connectivity solution is a complete replacement for standard SQL Server connectivity solutions and presents an efficient native alternative to the Borland Database Engine (BDE) and standard dbExpress driver for access to SQL Server. SDAC-based DB applications are easy to deploy, and do not require the installation of other data provider layers.

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.

Beautiful Soup is a library that makes it easy to scrape information from web pages. It sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. Beautiful Soup's support for Python 2 was discontinued on December 31, 2020: one year after the sunset date for Python 2 itself. From this point onward, new Beautiful Soup development will exclusively target Python 3. The final release of Beautiful Soup 4 to support Python 2 was 4.9.3. Beautiful Soup is licensed under the MIT license, so you can also download the tarball, drop the bs4/ directory into almost any Python application (or into your library path) and start using it immediately.

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.

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.

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.

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).

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.

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.

python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.

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.

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.

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).

gevent is a coroutine-based Python networking library that uses greenlet to provide a high-level synchronous API on top of the libev or libuv event loop. gevent is inspired by eventlet but features a more consistent API, simpler implementation and better performance. Read why others use gevent and check out the list of the open source projects based on gevent.

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.

Flutter is Google’s UI toolkit for building beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. Paint your app to life in milliseconds with Stateful Hot Reload. Use a rich set of fully-customizable widgets to build native interfaces in minutes. Quickly ship features with a focus on native end-user experiences. Layered architecture allows for full customization, which results in incredibly fast rendering and expressive and flexible designs. Flutter’s widgets incorporate all critical platform differences such as scrolling, navigation, icons and fonts, and your Flutter code is compiled to native ARM machine code using Dart's native compilers. Flutter's hot reload helps you quickly and easily experiment, build UIs, add features, and fix bugs faster. Experience sub-second reload times without losing state on emulators, simulators, and hardware.

The Vega-Altair open-source project is not affiliated with Altair Engineering, Inc. With Vega-Altair, you can spend more time understanding your data and its meaning. Altair’s API is simple, friendly and consistent and built on top of the powerful Vega-Lite visualization grammar. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code. The key idea is that you are declaring links between data columns and visual encoding channels, such as the x-axis, y-axis, color, etc. The rest of the plot details are handled automatically. Building on this declarative plotting idea, a surprising range of simple to sophisticated plots and visualizations can be created using relatively concise grammar.

Bit is a scalable and collaborative way to build and reuse components. It's everything you need from local development to cross-project integrations. Try it for free. Bit is an open-source toolchain for component-driven development. Forget monolithic apps and distribute to composable software. Distribute component ownership across development teams. Components are easy to replace and refactor over time. Drive development standards and consistency across teams and products. Compose existing components into new ones instead of reinventing the wheel. Build a composable design system and UI. Create a consistent and reusable UI software. Distribute code and teams. Drive autonomy and standards. Scale to cross-team collaboration and bridge the gap between design, development and product. Create a scalable and composable backend that never repeats itself.

Accelerate your internal tools development. A low-code platform for developers to build internal tools in minutes. With the SQL Generate feature, you can input natural language and get SQL statements that can be run directly. This works in databases like MySQL, Postgre, Supabase, etc. We offer developers a high degree of freedom to implement richer functionality through JavaScript, wrapping JS statements with {{Template Syntax}} to place at any string type variable spaces for more variety in the output. ILLA can connect to the mainstream databases or any data connected through APIs and add actions to chain to user events. It tightly integrates the data obtained from the back-end with the front-end components, allowing developers to write simple data calls to achieve massive information interaction.

The IP class allows a comfortable parsing and handling for most notations in use for IPv4 and IPv6 addresses and networks. It was greatly inspired by RIPE’s Perl module NET::IP’s interface but doesn’t share the implementation. It doesn’t share non-CIDR netmasks, so funky stuff like a netmask of 0xffffff0f can’t be done here. It can detect about a dozen different ways of expressing IP addresses and networks, parse them and distinguish between IPv4 and IPv6 addresses. Nearly all class methods which return a string have an optional parameter ‘wantprefixlen’ which controls if the prefixlen or netmask is printed. Per default the prefilen is always shown if the network contains more than one address. You can also change the defaults on an per-object basis by fiddling with the class members.

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.