Search Results for "source code tracking" - Page 19
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Showing 950 open source projects for "source code tracking"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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ATX
Smart phone automation tool. Support iOS, Android, WebApp and game
ATX (AutomatorX) is an open source automated testing tool that supports testing native applications, games, and Web applications on iOS and Android platforms. Use Python to write test cases, and use image recognition and control positioning technology to complete the automation of the game. Attach a dedicated IDE to complete scripting quickly. The libraries for Android and iOS native application testing have been separated and can be used alone (it is strongly recommended to use it alone, firstly, it has less dependencies and high stability, and secondly, it can be automatically completed when writing code) -
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coNCePTuaL
DSL for writing communication benchmarks
coNCePTuaL is a toolset for rapidly generating portable, readable, and reproducible network-performance tests. coNCePTuaL can perform the equivalent of many pages of C code with just a few mouse clicks or lines of code in a domain-specific language. -
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Examples.Python
Shows how to use tkinter only by programming code (Python).
Examples Python shows how to use tkinter only by programming code (Python). * Github repository : https://github.com/gammasoft71/Examples.Python * Homepage : https://gammasoft71.wixsite.com/gammasoft/python -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). "autologging.traced" decorates a class to provide automatic CALL/RETURN tracing for all class,... -
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Jupyter Themes
Custom Jupyter Notebook Themes
jupyter-themes brings theme management to classic Jupyter Notebooks with a command-line tool that can restyle the interface, code cells, and UI chrome in seconds. It ships a catalog of popular dark and light themes and lets you customize fonts, font sizes, cell widths, and toolbar visibility so the notebook matches your preferred reading and coding ergonomics. The theming system adjusts CodeMirror syntax highlighting to keep code legible against chosen backgrounds and provides options to... -
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ECS:Python
Light-weight C++ library for embedding Python into C++
ECS:Python (Embedded C++ Scripting with Python) is a simple Python wrapper library designed specifically for C++ developers who wish to add Python scripting to their new / existing C++ projects. ECS:Python allows you to expose objects from a C++ application to an embedded Python interpreter for interactive scripting. ECS:Python is light-weight and easy to use. To get started all you need to do from your project is #include "EcsPython.h", and link to the EcsPython library. Included with... -
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Django JET
Modern responsive template for the Django admin interface
Django JET has two kinds of licenses: open-source (AGPLv3) and commercial. Please note that using AGPLv3 code in your programs makes them AGPL compatible too. So if you don't want to comply with that we can provide you a commercial license (visit the Home page). The commercial license is designed for using Django JET in commercial products and applications without the provisions of the AGPLv3. -
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Sploit
SploitFrameWork *BETA*
WELCOME TO THE SPLOITFRAMEWORK SPLOIT COMES WITH A PAYLOAD OF THINGS FOR ALL YOUR HACKING NEEDS, SUCH AS 1. Email Phishing 2. Spear Phishing 3. Spoofing 4. Credential Harvester 5. Kayloggers 6. Tabnabbing And More . . . -
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Skater
Python library for model interpretation/explanations
...Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. The library has embraced object-oriented and functional programming paradigms as deemed necessary to provide scalability and concurrency while keeping code brevity in mind. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Spooky Coder
Auto code generation for many languages.
Quickly define your ORM with the simple Brainstorm format, then instantly create your SQL, Java, PHP, Python, Perl, even C++, etc. code to manage all your object relationships. -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda management system. ... -
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PyEdit Editor
Configurable Editor in Python
PyEdit is a fully featured fast text editor written in Python. It can be used in any platform that has GTK. Because it is written in Python, it is easily configurable. Features code spell check and macro recording. Tested in Win/Lin/Mac --- Update: Using the editor full time V23 is mature enough for production --- Update: Had to downgrade to PyGTK 2.22.xx as 2,24,x had a double click message bug. (uploaded 22.2 to this project) --- Update: V33 is working as a champ. New... -
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Nick's Python Toolchest
A heterogeneous bunch of useful Python stuff
Nxpy is a Python library that combines general purpose features with a set of tools more geared towards build automation and source code management. It provides convenient ways to invoke and control interactive and non-interactive commands, context aware backup for files you need to modify, convenience stubs for file like objects, and more. It also contains wrappers for ClearCase, Maven and Subversion, as well as tools to manipulate Maven and Visual Studio configuration files. -
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Python Basics
Some usefull modules and APIs for Python
Often used project independent code for Python. See Code (https://sourceforge.net/p/pythonbasics/code/) for the files. -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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JavaScript Lint is a development tool that validates JavaScript code for best coding practices, finding common mistakes without actually running the script or opening the web page.
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pyhanlp
Chinese participle
pyhanlp is a Python interface for HanLP (Han Language Processing) that lets you use a mature Java-based NLP toolkit from Python workflows without rebuilding the underlying algorithms. It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into... -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Image classification models for Keras
Keras code and weights files for popular deep learning models
All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'... -
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Pyrlang
Erlang node implemented in Python 3.5+ (Asyncio-based)
This is a drop-in Erlang node implementation in Python 3, implementing a network Erlang node protocol. It was designed to allow interoperation between existing Python projects and BEAM languages: Erlang, Elixir, Gleam, Luaerl, LFE, Clojerl, and such. With just a few lines of startup code your Python program becomes an Erlang network node, participating in the Erlang cluster. -
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Intel neon
Intel® Nervana™ reference deep learning framework
neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu... -
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Tangent
Source-to-source debuggable derivatives in pure Python
Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. ...
