Mako Alternatives

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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!

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.

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.

Jinja is a fast, expressive, extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. Then the template is passed data to render the final document.

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.

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.

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.

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.

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.

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.

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.

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.

Bottle is a fast, simple and lightweight WSGI micro web-framework for Python. It is distributed as a single file module and has no dependencies other than the Python Standard Library. Requests to function-call mapping with support for clean and dynamic URLs. Fast and pythonic built-in template engine and support for mako, jinja2 and cheetah templates. Convenient access to form data, file uploads, cookies, headers and other HTTP-related metadata. Built-in HTTP development server and support for paste, bjoern, gae, cherrypy or any other WSGI capable HTTP server.

JavaScript UI library and framework for speeding up web development. JS Framework for cross-platform web Apps development 102 UI widgets and feature-rich CSS / HTML5 JavaScript controls. Save at least 3000+ development hours by using ready-made widgets and UI controls. Develop Web UI 30% faster. We have accumulated the best design ideas. We have meticulously considered UX of each Webix component for five conceptual designs. Our support service specialists know everything about our library and can help you solve any problem. We also have an official support forum where you can discuss issues with our developers. By using Webix JS framework you receive an elegant and lightweight code based on object-oriented programming concepts. Associate your project with jQuery JavaScript library, MVC frameworks AngularJS, React, Vue.js, Backbone.js, third party UI extensions.

Over 80 Angular UI components with top-notch quality to help you implement all your UI requirements in style. Crafted on a design-agnostic infrastructure, choose from a vast amount of themes such as material, bootstrap, tailwind, primeone, or develop your own. 280+ ready-to-copy-paste UI blocks to build spectacular applications in no time. The designer is the ultimate tool to create your own PrimeNG experience powered by a SASS-based theme engine with 500+ variables and a visual designer. Professionally designed highly customizable application templates to get started in style. Open source products of PrimeTek are used all around the world by millions of developers. The ultimate set of UI components to assist you with 90+ impressive Angular components. Connect with the other open source community members, collaborate, and have a voice in the project roadmap. Boost your productivity by achieving more in less time and accomplish amazing results.

As the name suggests, Hope UI is the revolutionary admin dashboard built with the developer's aspirations and needs in the first place. Hope UI Laravel Admin Dashboard Template and UI component set is designed with a modular component structure to help design and launch web applications in the fastest way possible. Being able to develop lightweight web applications and admin panels, Hope UI Admin Template comes with a Live Customizer to cut down on development time and coding hours. The Hope UI Bootstrap Admin Dashboard brings the future of admin UI to power your present and future development. Hope UI is available in 8 different technologies which are Bootstrap, Vue JS, React JS, Laravel, CodeIgniter, Figma, XD and Sketch UI Kit and more versions like Tailwind, Angular, React Native, etc are in the roadmap.

Antiqueruby React Native Material Design UI Components is every app developer’s dream. That’s because the app template, which is attractive and is designed to save developers hours of work by providing them with stylish and clever UI and UX components to customise their apps. Created using Material Design and offering over 140+ screens for profiles, sign-ins and sign-ups, social media, navigation, and for much more..! It’s no wonder that React Native Material Design UI Components has become one of CodeCanyon’s bestsellers.

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.

DHTMLX is a JavaScript UI library that provides a set of highly customizable and flexible components for building modern and responsive web applications. The library includes more than 30 UI components, such as Gantt, Scheduler, Kanban, diagrams, charts, grids, spreadsheets, calendars, trees, forms, and more. DHTMLX helps to advance web development and build feature-rich data-intensive applications of any complexity. One of the key advantages of DHTMLX is its compatibility with different web frameworks, including React, Angular, and Vue.js, which makes it a great choice for developers who are already working with these frameworks. DHTMLX is also designed with performance in mind. Its components are optimized for fast rendering. A comprehensive and rich API provides a straightforward way to manipulate JavaScript/HTML5 UI widgets. The library has detailed API documentation, tutorials, and examples that help developers quickly get up to speed and start building their apps.

Bootstrap your application with beautiful Material Design components. React Toolbox is a set of React components that implements Google Material Design specification. It's built on top of some of the trendiest proposals like CSS Modules (written in SASS), Webpack, and ES6. The library harmoniously integrates with your Webpack workflow and it's easily customizable and very flexible. Check our awesome documentation (which is built using React Toolbox) and try all the components with live examples. We've created a playground so you don't need to install anything to fall in love with our components, so fun! The app bar is a special kind of toolbar that’s used for branding, navigation, search, and actions. Usually, it contains controls on the right and left side and a title with the current section or app name. You should give the content with children elements. Consists of text, an image, or both, designed in accordance with your app’s color theme.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.