Search Results for "bingo python code" - Page 14
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Showing 2581 open source projects for "bingo python code"
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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Mage.ai
Build, run, and manage data pipelines for integrating data
... is a standalone file containing modular code that’s reusable and testable with data validations. No more DAGs with spaghetti code. Start developing locally with a single command or launch a dev environment in your cloud using Terraform. Write code in Python, SQL, or R in the same data pipeline for ultimate flexibility. -
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Pyre
Performant type-checking for python
Built from the ground up to support gradual typing and deliver responsive incremental checks. Performant on large codebases with millions of lines of Python. Designed to help improve code quality and development speed by flagging type errors interactively in your terminal or live in your favorite editor. Follows the typing standards introduced in PEPs 484, 526, 612, and is being actively developed and constantly improved. Pyre ships with Pysa, a security focused static analysis tool we've built... -
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Hy
A dialect of Lisp that's embedded in Python
... thing a Python programmer will notice about Hy is that it has Lisp’s traditional parenthesis-heavy prefix syntax in place of Python’s C-like infix syntax. As in other Lisps, the value of a simplistic syntax is that it facilitates Lisp’s signature feature, metaprogramming through macros, which are functions that manipulate code objects at compile-time to produce new code objects, which are then executed as if they had been part of the original code. -
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isort
A Python utility / library to sort imports
isort is a Python utility/library to sort imports alphabetically, and automatically separated into sections and by type. It provides a command-line utility, Python library and plugins for various editors to quickly sort all your imports. It requires Python 3.6+ to run but supports formatting Python 2 code too. Several plugins have been written that enable to use isort from within a variety of text-editors. You can find a full list of them on the isort wiki. Additionally, I will enthusiastically... -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily... -
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django-pgtrigger
Write Postgres triggers for your Django models
django-pgtrigger is a Django library for defining and managing PostgreSQL triggers directly in Python code. It allows developers to create database-level logic like automatic field updates, auditing, or validation without writing raw SQL. It’s ideal for teams that want stronger data integrity while keeping logic version-controlled. -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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grafanalib
Python library for building Grafana dashboards
Grafanalib is a Python library for building Grafana dashboards programmatically, allowing users to automate dashboard creation and configuration. -
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Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together... -
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gopy
gopy generates a CPython extension module from a go package
... extensively on reproducing complex Go code in large libraries -- most stuff "just works". For example, the GoGi GUI library is fully usable from python now (do make; make install in the python directory there, and try the examples/widgets/widgets.py demo). Callback methods from Go into Python now work: you can pass a python function to a Go function that has a function argument, and it will call the python function appropriately. -
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arxiv_latex_cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper
This tool allows you to easily clean the LaTeX code of your paper to submit to arXiv. From a folder containing all your code, e.g. /path/to/latex/, it creates a new folder /path/to/latex_arXiv/, that is ready to ZIP and upload to arXiv. -
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MegaLinter
Mega-Linter analyzes 50 languages, 22 formats, 21 tooling formats etc.
Verify your code consistency with an open-source tool. MegaLinter is an Open-Source tool for CI/CD workflows that analyzes the consistency of your code, IAC, configuration, and scripts in your repository sources, to ensure all your projects sources are clean and formatted whatever IDE/toolbox is used by their developers, powered by OX Security. Supporting 54 languages, 24 formats, 22 tooling formats and ready to use out of the box, as a GitHub action or any CI system highly configurable... -
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Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees... -
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Super-Linter
Combination of multiple linters to install as a GitHub Action
This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. The design of the Super-Linter is currently to allow linting to occur in GitHub Actions as a part of continuous integration... -
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py-spy
Sampling profiler for Python programs
py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spending time on without restarting the program or modifying the code in any way. py-spy is extremely low overhead: it is written in Rust for speed and doesn't run in the same process as the profiled Python program. This means py-spy is safe to use against production Python code. py-spy works from the command line and takes either the PID of the program you want to sample from or the command... -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
.... As shown below, it results in readable code that can always be visualized. Hamilton loads that definition and automatically builds the DAG for you. Hamilton brings modularity and structure to any Python application moving data: ETL pipelines, ML workflows, LLM applications, RAG systems, BI dashboards, and the Hamilton UI allows you to automatically visualize, catalog, and monitor execution. -
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Fantomas
FSharp source code formatter
F# source code formatter, inspired by scalariform for Scala, ocp-indent for OCaml and PythonTidy for Python. This project aims at formatting F# source files based on a given configuration. Fantomas will ensure correct indentation and consistent spacing between elements in the source files. We assume that the source files are parsable by F# compiler before feeding into the tool. Fantomas follows two F# style guides: the F# code formatting guidelines from Microsoft by default and the G-Research F... -
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Spirit
Spirit is a modern Python based forum built on top of Django framework
... comment you want with a "like." Spirit is mobile-first, it's meant to work in the same way in any given device. The code has been written on python employing django's framework and it can be easily integrated to pre-existing projects. Spirit is part of the open source initiative, and it's a project released under the terms of the MIT license. -
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Jinja
Ultra fast and expressive template engine
Jinja is a fast, full-featured and expressive template engine for Python. It offers full unicode support, a sandboxed environment for safe executions, and so much more. Jinja is among the most widely used template engines for Python, and for good reason. It is both beautiful and powerful, and makes a template designer’s job a lot easier. Jinja is inspired by Django's templating system, but steps it up with an expressive language that results in more powerful tools, plus an automatic HTML... -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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Foolbox
Python toolbox to create adversarial examples
Foolbox: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. Foolbox 3 is built on top of EagerPy and runs natively in PyTorch, TensorFlow, and JAX. Foolbox provides a large collection of state-of-the-art gradient-based and decision-based adversarial attacks. Catch bugs before running your code thanks to extensive type annotations in Foolbox. Foolbox is a Python library that lets you easily run adversarial attacks against machine... -
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Chainlit
Build Python LLM apps in minutes
Chainlit is an open-source Python package that makes it incredibly fast to build and share LLM apps. Integrate the Chainlit API in your existing code to spawn a ChatGPT-like interface in minutes! Integrate seamlessly with an existing code base or start from scratch in minutes. Understand the intermediary steps that produced an output at a glance. Deep dive into prompts in the Prompt Playground to understand where things went wrong and iterate. Invite your teammates, create annotated datasets... -
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Typer
Typer, build great CLIs, based on Python type hints
Typer is a library for building CLI applications that users will love using and developers will love creating. Based on Python 3.6+ type hints. Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. It's easy to use for the final users. Automatic help, and automatic completion for all shells. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. The simplest example adds only 2 lines...
