Search Results for "python 3.7 decompiler"
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Showing 14 open source projects for "python 3.7 decompiler"
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Amazon Braket Python Schemas
A library that contains schemas for Amazon Braket
Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs. Schemas for the S3 results of each quantum task. Schemas for the device capabilities of each device. The preferred way to get Amazon Braket Python Schemas... -
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AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the best detailed configuration for you. ... -
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PyExcelerate
Accelerated Excel XLSX Writing Library for Python 2/3
Accelerated Excel XLSX writing library for Python. PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed. -
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fpdf2
Simple PDF generation for Python
fpdf2 is a library for simple & fast PDF document generation in Python. It is a fork and the successor of PyFPDF. Compared with other PDF libraries, fpdf2 is fast, versatile, easy to learn and to extend (example). It is also entirely written in Python and has very few dependencies: Pillow, defusedxml, & fontTools. It is a fork and the successor of PyFPDF. -
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rich
Rich is a Python library for rich text and beautiful formatting
The Rich API makes it easy to add color and style to terminal output. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, and more, out of the box. Rich is a Python library for rich text and beautiful formatting in the terminal. Rich works with Linux, OSX, and Windows. True color/emoji works with new Windows Terminal, classic terminal is limited to 16 colors. Rich requires Python 3.7 or later. Effortlessly add rich output to your application, you can import the rich print method, which has the same signature as the builtin Python function. ... -
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Yandex Music API
Non-official Python library for works with API service Index
This library provides Python interface for anyone undocumented and self-made API Yandex Music. It is compatible with Python 3.7 + and supports working with both synchronous and asyncio code. In addition to implementing a clean API, this library has a number of — high-level wrapping classes in order to make the development of customers and scripts simple and understandable. -
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Secdev Scapy
Scapy: the Python-based interactive packet manipulation program
...It is published under GPLv2. Starting from version 2.5.0+, it supports Python 3.7+ (and PyPy). Scapy supports Python 2.7 and Python 3 (3.4 to 3.9). It's intended to be cross platform, and runs on many different platforms (Linux, OSX, *BSD, and Windows). Scapy can easily be used as an interactive shell to interact with the network. Scapy works without any external Python modules on Linux and BSD like operating systems. -
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Boltons
250+ constructs, recipes, and snippets which extend the Python library
Boltons is a set of pure-Python utilities in the same spirit as, and yet conspicuously missing from, the standard library. Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. -
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Lightly
A python library for self-supervised learning on images
...This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions. -
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10
Darts
A python library for easy manipulation and forecasting of time series
...The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper). -
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Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms. -
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SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
...For unit tests, tox will use pytest to run the unit tests in a Python 3.7 interpreter. tox will also run flake8 and pylint for style checks. -
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Spyne
A transport agnostic sync/async RPC library
Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple... -
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Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each...
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