Search Results for "property"
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Showing 36 open source projects for "property"
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1
Chemprop
Message Passing Neural Networks for Molecule Property Prediction
Chemprop is a repository containing message-passing neural networks for molecular property prediction. -
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Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests. -
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Semantica
Graph-Native Infrastructure for Context and Accountable AI Systems
...Deterministic reasoning, ontology management, provenance tracking, and decision records help explain how conclusions were reached. The platform can complement existing LLMs, vector databases, and agent frameworks rather than replacing them. It supports RDF and labeled-property graphs along with standards-oriented interoperable storage. A browser-based Knowledge Explorer provides graph visualization, temporal inspection, and causal-chain tracing. Semantica is self-hostable and aimed especially at regulated or sensitive environments where decisions must remain traceable and defensible. -
4
itr-wala
File your Indian income tax return (ITR) from your terminal
...A separate tax engine handles slabs, rebates, cess, surcharges, special-rate income, interest, late fees, and old-versus-new regime comparisons. Strict validation cross-checks entered values and rejects malformed or sensitive identifiers. The repository includes golden tests, validator tests, and property-based fuzzing to verify calculation behavior. It can generate a filing pack that maps computed values to the government portal while leaving payment, submission, and e-verification to the user. It targets resident individual returns for AY 2026-27 and explicitly identifies unsupported cases. -
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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
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Woke
Woke is a Python-based development and testing framework for Solidity
Woke is a Python-based development and testing framework for Solidity. A testing framework for Solidity smart contracts with Python-native equivalents of Solidity types and blazing-fast execution. A property-based fuzzer for Solidity smart contracts that allows testers to write their fuzz tests in Python. See examples and documentation for more information. Fuzzer builds on top of the testing framework and allows efficient fuzz testing of Solidity smart contracts. Woke implements an LSP server for Solidity. The only currently supported communication channel is TCP. -
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Schemathesis
Guarantee flawless API functionality with test scenarios
...The application under test could be written in any language; the only thing you need is a valid API schema in a supported format. Simple to use and yet powerful to uncover hard-to-find errors thanks to the property-based testing approach backed by state-of-the-art Hypothesis library. Schemathesis uses your API's schema to generate both valid and invalid test scenarios, helping you verify API compliance and catch potential issues. It also verifies examples from the schema itself. -
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Brownie
A Python-based development and testing framework for smart contracts
Brownie is a Python-based development and testing framework for smart contracts targeting the Ethereum Virtual Machine. Powerful debugging tools, including python-style tracebacks and custom error strings. The recommended way to install Brownie is via pipx. pipx installs Brownie into a virtual environment and makes it available directly from the command-line. Once installed, you will never have to activate a virtual environment prior to using Brownie. Brownie documentation is hosted at Read... -
9
watermarks-remover
Strip multi-vendor AI provenance marks
Watermarks Remover is an agent skill and Python service for removing AI provenance marks from text and files that users own. It cleans invisible Unicode characters, exotic spaces, bidirectional controls, and other hidden text artifacts through deterministic processing. Statistical text watermarks can be addressed through agent rewriting and an optional rewrite hook. The service also strips provenance and metadata such as C2PA, EXIF, XMP, and document properties from many media and document... -
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django-rest-framework-gis
Geographic add-ons for Django REST Framework
...The primary key of the model (usually the "id" attribute) is automatically used as the id field of each GeoJSON Feature Object. The GeoJSON specification allows a feature to contain a boundingbox of a feature. GeoFeatureModelSerializer allows two different ways to fill this property. The first is using the geo_field to calculate the bounding box of a feature. -
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django-prometheus
Export Django monitoring metrics for Prometheus.io
...You can define custom buckets for latency, adding more buckets decreases performance but increases accuracy. SQLite, MySQL, and PostgreSQL databases can be monitored. Just replace the ENGINE property of your database, replacing django.db.backends with django_prometheus.db.backends. You may want to monitor the creation/deletion/update rate for your model. This can be done by adding a mixin to them. This is safe to do on existing models (it does not require a migration). Note that the exported metrics are counters of creations, modifications and deletions done in the current process. ... -
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redshift_connector
Amazon Redshift connector for Python
...Please open an issue with our project to request new integrations or get support for a redshift_connector issue seen in an existing integration. Following the DB-API specification, autocommit is off by default. It can be turned on by using the autocommit property of the connection. The paramstyle for a cursor can be modified via cursor.paramstyle. The default paramstyle used is format. Valid values for paramstyle include qmark, numeric, named, format, pyformat. redshift_connector uses logging for providing detailed error messages regarding IdP authentication. A do-nothing handler is enabled by default as to prevent logs from being output to sys.stderr. -
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A cross-platform, open-source, alternative to NIST REFPROP. Based on reference-accuracy equations of state and transport property correlations for refrigerants like Water, CO2, R134a, Nitrogen, Argon, Ammonia, Air, R404a, R410a, Propane and many others. A selection of secondary working fluid properties are also available. Can also make use of REFPROP when available. In addition, calculations for Humid Air Properties based on ASHRAE RP-1485 are provided.
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DWSIM - Open Source Process Simulator
Simulate chemical processes using advanced thermodynamic models
DWSIM is an open source, CAPE-OPEN compliant chemical process simulator for Windows, Linux and macOS systems. Written in VB.NET and C#, DWSIM features a comprehensive set of unit operations, advanced thermodynamic models, support for reacting systems, petroleum characterization tools and a fully-featured graphical interface. DWSIM Pro is a commercial sibling of DWSIM built on top of open-source software. It offers extended features, comes with private support, and is accessible in the... -
15
littleutils
Various small and useful command-line utilities
The littleutils include duplicate file finders (repeats, repeats.pl, repeats.py), image optimizers (opt-jpg, opt-png, opt-gif, recomp-jpg), file rename tools (lowercase, uppercase, pren), archive recompressors (to-gzip, to-bzip2, to-bzip3, to-7zip, to-lzma, to-lzip, to-xz), a tempfile utility (tempname), file property tools (filedate, filemode, filenode, fileown, filesize, and lrealpath), and others. See the README file for more details. -
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DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options. -
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Tartan Systems
Free Open Source Accounting and Club Systems
...The modules comprise the following: Asset's Register Book Clubs (Member and Book Register) Booking's Manager (Resorts and B&B's) Bowls Clubs (Lawn Bowls Tabs Draws and Competitions) Bowls Sectional Competitions (Lawn Bowls) Creditor's Ledger (Accounts Payable) Debtor's Ledger (Accounts Receivable) General Ledger (Nominal Ledger) Loans Ledger (Fixed and Variable Term Loans) Member's Ledger (Sports and Other Clubs) Rental's Ledger (Property and Collection) Salaries and Wages - ZA (Includes Staff Loans) Sales Invoicing (Includes Sales Orders, Quotations and Works Orders) Store's Ledger (Inventory) -
18
ChemCrow
Chemcrow
ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development. -
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Automated Interpretability
Code for Language models can explain neurons in language models paper
...It includes a “neuron explainer” component that, given a target neuron or latent feature, proposes natural language explanations or heuristics (e.g. “this neuron activates when the input has property X”) and then simulates activation behavior across example inputs to test whether the explanation holds. The project also contains a “neuron viewer” web component for browsing neurons, explanations, and activation patterns, making it more interactive and exploratory. -
20
Sezioni
Python tool for section property evaluation and stress calculation
This software is a basic tool for section property evaluation and stress calculation, written in python. The section can be imported or input by points and then can be modified moved, rotated etc.. Area and section inertia can be exported. Loads can be applied (multiple load cases can be imported) and the related stresses are calculated by mean of De Saint Venant formulas. Results are plot with selectable color maps. -
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Open source steam property routines in C. Implements the IAPWS-IF97 steam tables from the International Association for the Properties of Water and Steam. Includes two-way property solvers and test suite. Can be used from C/C++, Fortran, Python, LabVIEW, Octave and ASCEND.
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Open Drug Discovery Toolkit (ODDT)
Modular and comprehensive toolkit for use in cheminformatics
...These extensions allow to use of toolkits at all its grace and some features may be backported from others to introduce missing functionalities. Most important and handy property of Molecule in ODDT are Numpy dictionaries containing most properties of supplied molecule. Some of them are straightforward, other require some calculation, ie. atom features. Dictionaries are provided for major entities of molecules. -
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LGButton
A fully customisable subclass of the native UIControl
A fully customizable subclass of the native UIControl which allows you to create beautiful buttons without writing any line of code. A fully customizable subclass of the native UIControl which allows you to create beautiful buttons without writing any line of code. You can add images/icons to your button, icons are taken from different ready-to-use font icons collections, images can be imported directly from your project assets folder. Icons are managed by SwiftIconFont integration, so you... -
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Aglyph
Aglyph is a Dependency Injection framework for Python.
Aglyph is a Dependency Injection framework for Python, supporting type 2 (setter) and type 3 (constructor) injection. Aglyph runs on CPython (http://www.python.org/) 2.7 and 3.4+, and on recent versions of the PyPy (http://pypy.org/>),Jython (http://www.jython.org/), IronPython (http://ironpython.net/), and Stackless Python (http://www.stackless.com/) variants. Aglyph can assemble "prototype" components (a new instance is created every time), "singleton" components (the same instance... -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and a whole whack load of hyperparameters we don’t have to worry about. ...