Open Source Python Frameworks
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Python Frameworks
View 161 business solutionsBrowse free open source Python Frameworks and projects below. Use the toggles on the left to filter open source Python Frameworks by OS, license, language, programming language, and project status.
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Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Linderdaum Engine is an open source purely object-oriented 3D gaming engine written in C++. It is designed to be an integrated solution for the development of interactive 3D applications, for game, industrial and scientific visualization.
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setuplib
Extensions for setuptools - detailed information on entry points
The *setuplib* package provides core functions for the query of meta information and installation repositories of *Python* packages. It provides query and filter options on the installed packages and the available information, while displaying the result data in various formats, e.g. as table, list, or JSON, XML, YAML, CSV, etc. The provided commands and extension points integrate seamless into the standard *setuptools* and/or *distutils*. The *setuplib* is member of the group *setuplib* of extension components for the common *setup.py* installer. The targeted users are mainly developers, advanced users, and system administrators. -
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setuplibcore
Internal functions to avoid dependency issues
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FreeImagePy is a FreeImage library python wrapper. It export the FreeImage library functions, so a python developer can simple use it into python programs. It need a compiled FreeImage library and ctypes for work.
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All-in-one security tool helps you prevent ransomware and breaches.Blumira’s detection and response platform enables faster resolution of threats to help you stop ransomware attacks and prevent data breaches. We surface real threats, providing meaningful findings so you know what to prioritize. With our 3-step rapid response, you can automatically block known threats, use our playbooks for easy remediation, or contact our security team for additional guidance. Our responsive security team helps with onboarding, triage and ongoing consultations to continuously help your organization improve your security coverage.
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The LisBON Framework is an adaptable framework for developing new parallel Memetic Algorithms (hybrid search algorithms for efficiently solving optimisation problems).
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PONY - ORM & web publication framework
Pony is a fast and easy to use Python ORM
Pony is an object-relational mapper. The most interesting feature of Pony is its ability to write queries to the database using generator expressions. Pony works with entities which are mapped to a SQL database. Using generator syntax for writing queries allows the user to formulate very eloquent queries. It increases the level of abstraction and allows a programmer to concentrate on the business logic of the application. Following is an example of a query in Pony: select(p for p in Product if p.name.startswith('A') and p.cost <= 1000) Pony translates queries to SQL using a specific database dialect. Currently Pony works with SQLite, MySQL, PostgreSQL and Oracle databases. Pony ORM also include the ER Diagram Editor which is a great tool for prototyping. You can create your ER diagram online at https://editor.ponyorm.com, generate the database schema based on the diagram and start working with the database using declarative queries in seconds. -
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PyMultimethods is a library that allows multimethods (aka multiple dispatch, generic functions) to be written in the python programming language. Functionality is exposed via function decorator or, optionally, a direct class interface.
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Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
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"Yet Another Do-It-Yourself (Test) Automation Framework" specification. Use or modify one of the existing software implementations (hosted/referenced here), or implement the framework yourself. Download and read the spec for more details.
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Deliver trusted data with dbtData teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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namedtupledefs
Pacthed namedtuple for field defaults.
The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2. -
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namedtupledefs2
Pacthed namedtuple for field defaults.
The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python3 see namedtupledefs3 or namedtupledefs -
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namedtupledefs3
Pacthed namedtuple for field defaults.
The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2. -
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namedtuplex
Pacthed namedtuple for field defaults.
The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2. -
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platformids
OS and Distribution Release Enumeration
The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. The supported version numbering comprise various release schemes such as classical version numbers with variable segments and optional release names, * AlpineLinux-3.8.1 * CentOS-6.10 * Debian-9.6 * Fedora31 * OS-X-10.6.8 * Ubuntu-18.04 * armbian-5.76 * cygwin-2.9.0 * opensuse-15.1 * raspbian-9.4 * slackware-14.2 * solaris-11.3 variations of numbering schemes and continous deployment * CentOS-7.6-1810 * NT-6.3.9600 * archlinux-2018.12.01 * kali-linux-2019.1 * NT-10.0.1809 -
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pythonids
Enumeration of Python implementations and releases
The ‘pythonids‘ package provides the enumeration of Python syntaxes and the categorization of Python implementations. This enables the development of fast and easy portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The current supported syntaxes are Python2.7+ and Python3 for the Python implementations: CPython IPython (based on CPython) IronPython Jython PyPy -
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setupjavax
Provides Java and integrated Jython/Pyhon + Java builds
The ‘setupjavax‘ package provides extension modules for the build of Java and Jython packages. The current release supports the following commands, additional are coming soon: - build_java - Java build and packaging for Python. Supports Java packaging for Python projects, adds native Java modules for Jython. - build_jy - Integrated Python and Java builds for Jython. Supports combined Java and Python / Jython packaging. Calls build_py and build_java. -
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setuptestx
Support of unit tests on multiple platforms and implementations.
The 'setuptestx' supports a common call interface for the major implementations and releases of Python on various operating systems and their variants of distributions. The current provided implementations are: - CPython, IPython, PyPY : Python2.7, and Python3.5+ - IronPython, Jython : Python2.7 For the OS see *Tested Platforms* in the manuals. -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
The yapydata - Yet Another Python Data - provides a unified interface for the access to various data syntaxes. Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. The initial supported DDLs are: * JSON, XML, YAML and the formats * INI, CFG, .properties The yapydata in particular supports the advanced access to data entries by mapping the dotted-OID notation onto mixed in-memory data types, optional including non-conformant tyeps such as tuple and set. -
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yapyutils
Utilities for platform indepentent low-level system APIs.
The 'yapyutils' - Yet Another Python Utils - package provides miscellaneous *Python* utilities for the adaptation of platform independent APIs of the low-level part of the software stack. These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. The more complex and complete data packages are provided for higher application layer functionality. The current release contains: * *yapyutils.modules* A utility to locate and load modules by a given name and/or file system path name, based on the *sys.path* variable. * *yapyutils.files* Search and location of files, e.g. modules and configuration files. * *yapyutils.help* Simple help for command line interfaces. * *yapyutils.config* Configuration file support, in particular for the initial setup of software packages.
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