Search Results for "python structural engineering" - Page 2
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Showing 77 open source projects for "python structural engineering"
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tacklelib
The C++11 library, msvc2015u3/gcc5.4 + cmake,python,bash,vbs modules
https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README.md https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.deps.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.linux_x86_64.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/changelog.txt -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
Prompt-eng-interactive-tutorial is a comprehensive, hands-on tutorial that teaches the craft of prompt engineering with Claude through guided, executable lessons. It starts with the anatomy of a good prompt and moves into techniques that deliver the “80/20” gains—separating instructions from data, specifying schemas, and setting evaluation criteria. The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts... -
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Design Patterns in Swift
Design Patterns implemented in Swift
Design-Patterns-In-Swift is a repository that translates classic software engineering design patterns (from sources like the Gang of Four) into Swift code examples, so you can see how those patterns look in a modern, strongly typed, object-/protocol-oriented language. It covers creational, structural, and behavioral patterns: singletons, factories, decorators, observers, strategy, command, mediator, and more. For each pattern, you’ll typically see one or more Swift implementations, commentary on where it makes sense in a Swift architecture, and caveats about when you might prefer pure protocol composition or using functional patterns instead. ... -
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Neural Network Intelligence
AutoML toolkit for automate machine learning lifecycle
Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'... -
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5
osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
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comby
A code rewrite tool for structural search and replace that supports
Comby is a tool for searching and changing code structure. Use lightweight templates to easily search and change code, HTML, or JSON. Comby is designed to work on any language or data format. Perform richer search and replace because Comby understands the syntax of code blocks, strings, and comments for your language. Comby is ideal for touching up pieces of code. Use it to translate code like this Python 2 to 3 fixer on the right to replace deprecated methods. Easily write one-off refactors... -
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GDAL wheels for linux
GDAL wheels for python and C/C++ projects (Linux only)
To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs... -
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libpostal
A C library for parsing/normalizing street addresses around the world
A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,... -
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Zipline
Zipline, a Pythonic algorithmic trading library
...Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python package. For a development installation (used to develop Zipline itself), create and activate a virtualenv, then run the etc/dev-install script. Please note that Zipline is not a community-led project. Zipline is maintained by the Quantopian engineering team, and we are quite small and often busy. -
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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ebfformat
An Efficient Binary data Format
EBF, which stands for Efficient Binary Format, is a binary file format for reading and writing binary data easily. Reading writing routines are currently available in C,C++,Fortran,Java, Python, IDL, MATLAB. A program called ebftkpy which has a set of utility functions to work with the .ebf files , e.g., viewing the contents and getting a summary, is also provided. The EBF specification is designed to be concise and easy to understand to make it easier for others to write their own code... -
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Python Crawler Tutorial Starts From Zero
Python crawler tutorial, taking you from zero to one
Python Crawler Tutorial Starts From Zero is a Chinese-language learning repository that teaches web crawling from introductory concepts through practical examples. Early lessons explain HTTP requests, request analysis, the Python Requests library, and common categories of extracted data. Separate chapters cover JSON processing and regular expressions for transforming responses into structured information. -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
13
MITIE
MITIE: library and tools for information extraction
...MITIE is built on top of dlib, a high-performance machine-learning library[1], MITIE makes use of several state-of-the-art techniques including the use of distributional word embeddings[2] and Structural Support Vector Machines[3]. MITIE offers several pre-trained models providing varying levels of support for both English, Spanish, and German trained using a variety of linguistic resources (e.g., CoNLL 2003, ACE, Wikipedia, Freebase, and Gigaword). The core MITIE software is written in C++, but bindings for several other software languages including Python, R, Java, C, and MATLAB allow a user to quickly integrate MITIE into his/her own applications. -
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CFD Python
Sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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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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chemfiles
Modern library for chemistry file reading and writing
Chemfiles is a modern and high-quality library for reading and writing trajectory files created by computational chemistry simulations program. These trajectories contains atomic positions, velocities, names, topology and sometimes more. Running simulations produce enormous amounts of data, which has to be post-processed to extract physical information about the simulated system. Chemfiles provides an interface to access this information which is - unified: the same code will work with... -
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pyCGNS
A Python package for CGNS
pyCGNS is now on github: https://pycgns.github.io/index.html https://github.com/pyCGNS/pyCGNS -
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That project aims at providing a clean API, and the corresponding C++ implementation, for the basis of Airline IT Business Object Model (BOM), ie, to be used by several other Open Source projects, such as RMOL, Air-Sched, Travel-CCM, OpenTREP, etc.
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interview
Everything you need to prepare for your technical interview
...Technology-specific sections cover Android, C#, Go, JavaScript, Node.js, PHP, Python, React, and additional subjects. The repository also includes resources for networking, operating systems, cryptography, mathematics, and system design, allowing candidates to build a broader preparation plan from many independent sources. -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. 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.... -
22
AirTSP
Simulated Airline Travel Solution Provider Library
AirTSP is also named AirTSP (TSP standing for Travel Service Provider). That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline Schedule Management System. It is intended to be used in simulated environments only: it is not designed to work in the real-world of Airline IT operations. AirTSP/AirTSP makes an extensive use of existing open-source libraries for increased functionality, speed and accuracy. In particular the Boost (C++... -
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BiBler
Tool to manage and manipulate BibTeX entries
BiBler is a software for managing references to scientific articles using BibTeX. BiBler runs with a windows GUI or can be used as a Python library -
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pyhard2, control hardware from python
An object-oriented framework for the development of instrument drivers
pyhard2 is an object-oriented framework to help in the development of instrument drivers. pyhard2 is proposed as an alternative to LabVIEW. Emphasis is given on serial drivers but the framework can be used with any socket. The source also contains the implementation of a PID controller and a setpoint ramp generator. The instrument drivers may further be incorporated in a GUI, using, e.g. PyQt or PySide. Threading is automatically taken care of. Furthermore, generic GUI (called... -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects.
