Search Results for "python 3.10 decompiler"
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Showing 35 open source projects for "python 3.10 decompiler"
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Thonny
Python IDE for beginners
Thonny is a Python IDE meant for learning programming. -
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TinyDB
Document oriented database optimized for you
...TinyDB neither needs an external server (as e.g. PyMongo) nor any dependencies from PyPI. TinyDB works on all modern versions of Python and PyPy. You can easily extend TinyDB by writing new storages or modify the behaviour of storages with Middlewares. TinyDB has been tested with Python 3.6 - 3.10 and PyPy3. -
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REST APIs with Flask and Python
Projects and e-book for our course, REST APIs with Flask and Python
A full course to teach you how to use Flask and Python to make REST APIs using multiple Flask extensions and PostgreSQL. Learn Flask, Docker, PostgreSQL, and more. Build professional-grade REST APIs with Python. No more outdated tutorials. Use Python 3.10+ and the latest versions of every Flask extension and library. Run your apps in Docker, host your code with Git, write documentation with Swagger, and test your APIs while developing. -
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Claude Code SDK Python
Python SDK for Claude Agent
...The repo is MIT-licensed and includes documentation and installation instructions (requires Python 3.10+, Node installation of Claude Code). Example usage shows how to stream responses, parse structured message blocks, or create persistent client sessions. -
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Zeep
A Python SOAP client
A fast and modern Python SOAP client. Compatible with Python 3.7, 3.8, 3.9, 3.10, 3.11, and PyPy. Build on top of lxml and requests. Support for Soap 1.1, Soap 1.2 and HTTP bindings. Support for WS-Addressing headers. Support for WSSE (UserNameToken / x.509 signing) Support for asyncio via httpx. Experimental support for XOP messages. Zeep inspects the WSDL document and generates the corresponding code to use the services and types in the document. -
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Django Cachalot
No effort, no worry, maximum performance
Caches your Django ORM queries and automatically invalidates them. Cachalot officially supports Python 3.7-3.10 and Django 2.2, 3.2, and 4.0-4.1 with the databases PostgreSQL, SQLite, and MySQL. Note: an upper limit on Django version is set for your safety. Please do not ignore it. To start developing, install the requirements and run the tests via tox. Currently, benchmarks are supported on Linux and Mac/Darwin. You will need a database called "cachalot" on MySQL and PostgreSQL. ... -
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PyGlossary
A tool for converting dictionary files aka glossaries
A tool for converting dictionary files aka glossaries. The primary purpose is to be able to use our offline glossaries in any Open Source dictionary we like on any OS/device. There are countless formats, and my time is limited, so I implement formats that seem more useful for myself, or for Open Source community. Also diversity of languages is taken into account. Pull requests are welcome. -
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Basic Pitch
A lightweight audio-to-MIDI converter with pitch bend detection
Basic Pitch is a Python library for Automatic Music Transcription (AMT), using lightweight neural network developed by Spotify's Audio Intelligence Lab. It's small, easy-to-use, pip install-able and npm install-able via its sibling repo. Basic Pitch may be simple, but it's is far from "basic"! basic-pitch is efficient and easy to use, and its multi pitch support, its ability to generalize across instruments, and its note accuracy compete with much larger and more resource-hungry AMT systems.... -
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Kor
LLM
This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back. -
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10
Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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django-money
Money fields for Django forms and models
A little Django app that uses py-moneyed to add support for Money fields in your models and forms. The default currency code length is 3 but you can change it with the CURRENCY_CODE_MAX_LENGTH setting. Currencies are listed on moneyed, and these modules use this to provide a choice list on the admin, also for validation. Django-money leaves you to use any custom model managers you like for your models, but it needs to wrap some of the methods to allow searching for models with money values.... -
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orjson
Fast, correct Python JSON library supporting dataclasses, datetimes
orjson is a fast, correct JSON library for Python. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively. orjson supports CPython 3.8, 3.9, 3.10, 3.11, and 3.12. It distributes amd64/x86_64, aarch64/armv8, arm7, POWER/ppc64le, and s390x wheels for Linux, amd64 and aarch64 wheels for macOS, and amd64 and i686/x86 wheels for Windows. orjson does not support PyPy. ... -
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AutoMLOps
Build MLOps Pipelines in Minutes
AutoMLOps is a service that generates, provisions, and deploys CI/CD integrated MLOps pipelines, bridging the gap between Data Science and DevOps. AutoMLOps provides a repeatable process that dramatically reduces the time required to build MLOps pipelines. The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock... -
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Granite TSFM
Foundation Models for Time Series
granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted... -
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Agent Payments Protocol (AP2)
Building a Secure and Interoperable Future for AI-Driven Payments
AP2 is a project released by Google’s “Agentic Commerce” initiative, focusing on a protocol and reference implementation for agent-driven or AI-mediated payments. In effect, AP2 aims to define a secure, interoperable protocol that allows software agents to act on behalf of users—making payments or shopping decisions autonomously—while preserving necessary security, auditability, and trust. The repository contains sample scenarios (in Python, Android, etc.) that illustrate how agents,... -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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smartclicker-open
Lightweight open-source AutoClicker for Windows with modern GUI, hotke
SmartClicker Open — lightweight and modern AutoClicker for Windows 10 / 11. Built with Python & CustomTkinter, it provides a clean interface and fast performance. ✅ Features: • F5 to Start, F6 to Hold • Single / Double / Triple / Hold click modes • Adjustable click interval (down to 0.01s) • No installation required — portable EXE • Works on all modern Windows versions • 100% open-source under MIT License 🧩 Technical: - Language: Python 3.10+ - Framework: CustomTkinter - Build: PyInstaller portable executable - License: MIT 💡 Project goal: Provide a safe, open-source, ad-free AutoClicker alternative with a clean UI and transparent codebase. ... -
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HydraDragonAntivirus
Dynamic and static analysis with Sandboxie for Windows, including EDR
Dynamic and static analysis with Sandboxie for Windows, including EDR, ClamAV, YARA-X, custom machine learning AI, behavioral analysis, NLP-based detection, website signatures, Ghidra, Suricata, Sigma, and much more than you can imagine -
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CSM (Conversational Speech Model)
A Conversational Speech Generation Model
The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution. -
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Filt8- v3.6 alerts for WSJT-X FT8
Alert and filter QSO for WSJT-X FT8 FT4
Filt8 - v3.6 release - Requires Python 3.x (3.10 or higher on Mac) Scrollable maps for small screens State data as of Feb 25, 2024. Map saves settings. Map features: filter by band, click to Lookup. Offline Maps to show station grid locations as you decode them in real-time (Check out js8mapper project on https://sourceforge.net/projects/js8map/ for this same option for JS8Call) Map feature allows filtering by band, listings by callsigns or grids, and callsign lookups via QRZ or HamCall (this requires Internet). ... -
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langchain-prefect
Tools for using Langchain with Prefect
Large Language Models (LLMs) are interesting and useful - building apps that use them responsibly feels like a no-brainer. Tools like Langchain make it easier to build apps using LLMs. We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole... -
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RedtDec
RetDec is a retargetable machine-code decompiler based on LLVM
The decompiler is not limited to any particular target architecture, operating system, or executable file format. ELF, PE, Mach-O, COFF, AR (archive), Intel HEX, and raw machine code supported. 32-bit: Intel x86, ARM, MIPS, PIC32, and PowerPC 64-bit: x86-64 supported. Demangling of symbols from C++ binaries (GCC, MSVC, Borland). Reconstruction of functions, types, and high-level constructs. -
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LaserBlast
A Laser Cannon Strategy Game
Why did I write this program, and why in Python? Well there were really two reasons. First I wanted to quickly test various game rules and strategies. Python and pygames made prototyping quick and easy. This is actually about the twentieth version of the game. Second I wanted to try the new match/case statements that were added in Python 3.10. I found lots of uses for match/case and I really like it. -
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gr-message_to_serial
GNURADIO OOT block
Block that receives a " message" and send string values over serial connection, to control hardware devices ( switch ), for example, via Arduino based controller ( see https://sourceforge.net/projects/ardu-switch/ ) Prerequisite: pyserial Build as usual for a Gnuradio block: - download and unpack - cd gr-message_to serial - mkdir build && cd build - cmake .. && make - sudo make install && ldconfig If successful this block is into OOT section... Enjoy ;-)
