Search Results for "structure" - Page 4
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Showing 119 open source projects for "structure"
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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Pipelines
An experimental programming language for data flow
...Unlike other languages for defining data flow, the Pipeline language requires the implementation of components to be defined separately in the Python scripting language. This allows the details of implementations to be separated from the structure of the pipeline while providing access to thousands of active libraries for machine learning, data analysis, and processing. -
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django-dynamic-scraper
Creating Scrapy scrapers via the Django admin interface
...Since it simplifies things DDS is not usable for all kinds of scrapers, but it is well suited for the relatively common case of regularly scraping a website with a list of updated items (e.g. news, events, etc.) and then dig into the detail page to scrape some more infos for each item. Django Dynamic Scraper tries to keep its data structure in the database as separated as possible from the models in your app, so it comes with its own Django model classes for defining scrapers, runtime information related to your scraper runs and classes. -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and... -
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Data Algorithm/leetcode/lintcode
Data Structure and Algorithm notes
...Part I is a brief introduction of basic data structures and algorithms, such as, linked lists, stack, queues, trees, sorting and etc. This book notes about learning data structure and algorithms. It was written in Simplified Chinese but other languages such as English and Traditional Chinese are also working in progress. -
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ECS:Python
Light-weight C++ library for embedding Python into C++
...ECS:Python requires a Python distribution to be installed on your system. Python can be downloaded from: www.python.org/download What's new in v3.0: * Fixed x64 pointer types. * Added CI and unit tests. * Cleaned up project structure and code formatting. * Switch to C++11 std::mutex. -
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fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and... -
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TensorFlow-ZH
Chinese version of the official document of TensorFlow
...It was initiated shortly after TensorFlow’s open-sourcing, with translation and proofreading contributions from a community of volunteers who aimed to bridge the language barrier for learners in China and other Mandarin communities. The repo mirrors the structure of the original English docs: chapters, sections, code examples, API references, and supplementary content like configuration and build guides. It includes additional files like a PDF version (compiled LaTeX/TeX sources), table of contents mappings, and translation metadata to track contributions. Over time, the repo has evolved to stay in sync with upstream changes, providing versioned snapshots of the translated content. -
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Flasky
Companion code to my O'Reilly book "Flask Web Development"
Flasky is a comprehensive example web application built with the Flask microframework that demonstrates best practices for developing real-world Python web applications, covering everything from project structure and configuration to database models, authentication, and deployment. It serves as both a tutorial and sample codebase that walks developers through building a full-featured web application, including user registration and login, role-based permissions, user profiles, and content creation. The project shows how to organize a Flask application into reusable blueprints, configure environment-specific settings, integrate SQL databases via SQLAlchemy, and manage migrations. ... -
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SAWS
A supercharged AWS command line interface (CLI)
...SAWS aims to supercharge the AWS CLI with features focusing on improving ease-of-use, and increasing productivity. Under the hood, SAWS is powered by the AWS CLI and supports the same commands and command structure. In addition to the default commands, subcommands, and options the AWS CLI provides, SAWS supports auto-completion of your AWS resources. Currently, bucket names, instance ids, and instance tags are included, with additional support for more resources under development. Sometimes you're not quite sure what specific command/subcommand/option combination you need to use. ... -
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asyncoro
Python framework for asynchronous, concurrent, distributed programming
...Asynchronous completions implemented in asyncoro are sockets (non-blocking sockets), database cursors, sleep timers and locking primitives. Programs developed with asyncoro have same logic and structure as Python programs with threads, except for a few syntactic changes. asyncoro supports socket I/O notification mechanisms epoll, kqueue, /dev/poll (and poll and select, where necessary), and Windows I/O Completion Ports (IOCP) for high performance and scalability, and SSL for security -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. ... -
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Algorithms in Python
Data Structures and Algorithms in Python
Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational understanding of algorithmic patterns. ... -
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Parse C++ header files using ply.lex to generate navigable class tree representing the class structure. CppHeaderParser.py has the advantage of being a pure python C++ header parser. Grap a copy of ply at http://www.dabeaz.com/ply/
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mergepbx
script for merging XCode project files in git
...Simply adding files can lead to merge conflicts that have to be solved manually, although it would be possible to resolve the conflict automatically if the merge algorithm would be aware of the structure of Xcode's project file. After long and annoying merge sessions in one of my projects, I came to the conclusion, that writing a merge driver for git which understands the structure of the project file would be a worthwhile endeavour, as it would save me from solving the merge conflicts for my co-workers. Unfortunately, that script was finished only after the project ended. ... -
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inFolder
A personal wiki created by your directory structure
A graphical text editor used to maintain a collection of pages, whose content is created by the user, but whose hierarchical structure is dictated by the directory structure. -
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PangView
Text Viewer that displays text similar to pango
...The parser reads pango tags similar to html. The utility was written, so formatted text can be displayed quickly. NEW! The parser now is updated to use a faster method of internal data structure. -
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Aqualid
General purpose build system
...Key features: Flexible and scalable for large projects Dynamic dependency graph Batch build support Distributed build scripts (no fixed project structure) Support any build target types (files, strings, URLs, remote resources etc.) Conditional options Scons like build scripts (but don't compatible) -
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SVNStartCommitHelper
Useful form to support SVN Commits as an SVN Start-Commit Hook Script
...The edited content is transformed and forwarded to the SVN commit dialog then. You still have full control on the commit message then. While using the helper you focus on message quality now instead struggling with message structure. -
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Importer library to import assets from different common 3D file formats such as Collada, Blend, Obj, X, 3DS, LWO, MD5, MD2, MD3, MDL, MS3D and a lot of other formats. The data is stored in an own in-memory data-format, which can be easily processed. www.open3mod.com/ is a 3D model viewer and exporter based on Assimp that is also Open Source.
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SPADE
A toolkit for developing and deploying protein structure algorithms.
The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE. -
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. -
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nacho
Python micro web-framework and asynchronous networking library
...Developers can customise templates used for generation or plug custom patterns, which makes the tool suitable across small utilities or large service fleets. Because it encourages consistency among services, teams can spin up new microservices with a shared structure and skip repetitive setup. Though the repository may be less active than some major frameworks, it serves as a valuable jump-start for projects where speed and uniformity matter. -
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Construct is a python module for bit-level, symmetrical parsing and building of data structures. Complex constructs are formed by a hierarchy of less-complex constructs, as well as user-defined constructs.
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