Search Results for "python-gtksourceview2" - Page 22
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2168 projects for "python-gtksourceview2" with 2 filters applied:
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The TRANSIMS Studio application is an integrated development environment for the TRansportation ANalysis and SIMulation System (TRANSIMS). Components include a run time environment to execute TRANSIMS in parallel, as well as a full featured GUI.
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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The GUIDOLib provides a powerful engine for the graphic rendering of music scores, based on the Guido Music Notation format. It supports Linux, Mac OS X, Windows, Android and iOS operating systems. A Java JNI interface is available as well as a Javascript version of the library. A Web API has also been designed, allowing to deploy the engine as a Web service.
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jpathpy
Select items from JSON by using JPath syntax
Package ``jpathpy`` is easy way for selecting items from objects, that can be iterate by keys or indices (such as dictionaries or lists). See full doc at <https://github.com/vowatchka/jpathpy>. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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StarsAndClown
Github Star Gathering Treatment List
StarsAndClown is a repository by the same maintainer that seems intended as a lighthearted “ranking / listing” project, possibly gathering interesting or amusing GitHub repositories, trending topics, or community “stars” — perhaps with a humorous or satirical twist given the name. The concept suggests a curated (or semi-automated) list of GitHub repos worth noting: whether because of popularity, novelty, or community interest — giving “people who eat grapes” (i.e. spectators) a way to enjoy... -
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Twint
An advanced Twitter scraping & OSINT tool written in Python
Twint is an advanced open-source Twitter scraping and OSINT tool written in Python that extracts tweets, user data, followers, likes, and more—without relying on Twitter’s API—making it highly useful for researchers, analysts, and hobbyists who want to bypass rate limits and access public Twitter data. -
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12306 Ticket Buying Assistant
12306 Smart ticket swiping, ticket booking
12306 is an automation and ticket-purchasing tool designed to interact with China’s official railway booking system, providing users with a programmatic way to search, reserve, and purchase train tickets. The project replicates the workflow of the official platform while adding automation features that help users secure tickets in high-demand scenarios. It supports querying schedules, checking seat availability, and performing booking actions through scripts, which reduces the need for... -
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tkcalendar
Calendar widget for Tkinter
tkcalendar is a python module that provides the Calendar and DateEntry widgets for Tkinter. The DateEntry widget is similar to a Combobox, but the drop-down is not a list but a Calendar to select a date. tkcalendar is compatible with both Python 2 and Python 3. It support all locale settings supported by the system and the colors are customizable. -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and Windows - Python2, Python3 - CPython, PyPy Object addresses within modules - Object Identifier OID - and the display of the runtime call flow are supported by 'PyStackInfo'. ... -
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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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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. -
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yz-next-apyref
Arno-Can's Python based API Reference Generator.
Multi-Syntax-Version and Multi-Implementation API reference documentation generator. Supports local and remote sources. -
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
The ‘setupdocx‘ provides a control layer for continuous documentation by the simplified creation, packaging, and installation of documentation. The provided commands are distributed as entry points and optional base classes for further customization into 'setup.py' - setuptools / distutils. Manages arbitrary document templates for the supported builder, supports multiple builds with arbitrary document layouts, designs, and patched contents. The current release supports the following... -
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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. -
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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. ... -
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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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setuplibcore
Internal functions to avoid dependency issues
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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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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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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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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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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... -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The...