Packages
Python client library for the Opsgenie REST API, enabling programmatic alert and incident management, heartbeat monitoring, and account operations.
However, the package has been dormant since August 2021 (1838 days); before adopting it, verify that your Opsgenie API version and feature set align with what the…
Optimizes the contraction order of einsum expressions to dramatically reduce computation time, working transparently with multiple array libraries.
Optimizes PyTorch einsum operations and functions containing them by applying opt_einsum strategies through PyTorch FX compute graphs.
Optax provides composable building blocks for gradient processing and optimization in JAX, including implementations of popular optimizers and loss functions that can be combined into custom solutions.
Install it if you are building machine learning systems with JAX and need flexible, composable optimizer and loss components.
OptBinning discretizes numeric variables into bins optimally for binary, continuous, and multiclass targets using mathematical programming, with support for constraints.
However, verify that its mathematical programming approach and dependency footprint fit your performance and deployment constraints before committing to production use.
Optimistix provides nonlinear solvers for root finding, minimization, fixed-point problems, and least-squares fitting, built on JAX with support for autodiff, GPU/TPU acceleration, and PyTree-based state.
Provides A/B testing, feature flagging, and feature management capabilities for Python applications, allowing you to run experiments and control feature rollouts without code deployment.
Install it if you need A/B testing or feature flag management in a Python application and are already using or planning to use the Optimizely platform.
Optimum provides optimization tools to export and run Transformers, Diffusers, and other HuggingFace models efficiently on specialized hardware accelerators like ONNX Runtime, OpenVINO, AWS Trainium, and Intel Gaudi.
Optimum Intel bridges Hugging Face Transformers and Diffusers models to OpenVINO, enabling model export, quantization, and accelerated inference on Intel CPUs, GPUs, and specialized accelerators.
Install it if you need to optimize and accelerate Transformers or Diffusers models on Intel CPUs, GPUs, or accelerators; skip it if you have no Intel hardware target…
Exports Hugging Face transformer models to ONNX format and runs them via ONNX Runtime for optimized inference.
A PyTorch quantization backend that reduces model size and memory by converting weights and activations to lower-precision integer or float8 formats while maintaining inference accuracy.
A dict subclass that automatically omits None values when storing or serializing, and is both picklable and JSON-serializable.
Optlang formulates and solves linear, mixed-integer, and quadratic optimization problems using symbolic expressions from sympy, with pluggable solver backends including GLPK, CPLEX, and Gurobi.
Install it if you're doing operations research, scientific computing, or constraint-based modeling in Python.
OpTree provides optimized utilities for flattening, unflattening, and mapping over nested Python container structures (PyTrees) like dicts, lists, tuples, and custom types.
Optuna is a hyperparameter optimization framework that automates the search for optimal hyperparameter values in machine learning models using a define-by-run API and state-of-the-art sampling algorithms.
Provides a real-time web dashboard for visualizing and monitoring Optuna hyperparameter optimization studies stored in a database backend.
Provides integration modules connecting Optuna hyperparameter optimization with third-party ML frameworks like PyTorch, scikit-learn, TensorFlow, XGBoost, LightGBM, and others.
optype provides single-method protocols and typed operators for precise type hints, letting you express exact types that reject sneaky subtypes and work cooperatively with type checkers like mypy and pyright.
Install it if you write code that needs to accept objects based on what operations they support rather than their concrete type.
Provides Python bindings to libopus, the IETF low-delay audio codec, allowing Python code to encode and decode Opus-compressed audio streams.
Provides Python bindings to libopus, the IETF low-delay audio codec, enabling encoding and decoding of Opus-compressed audio streams in Python applications.
OQpy generates OpenQASM 3 and OpenPulse programs in Python, providing a high-level interface to build quantum circuits with pulse-level control and calibration definitions.
Install it if you need to generate OpenQASM 3 programs with pulse calibrations from Python; skip it if you only work with high-level quantum circuit abstractions.
A Python driver for connecting to Oracle Database directly, conforming to the Python Database API 2.0 specification with support for both thin mode (direct connection) and thick mode (with optional Oracle Client libraries).
Passive parser for Oral-B toothbrush Bluetooth Low Energy advertisements that decodes manufacturer data broadcast by the device without establishing a connection.
ORAS Python is an SDK that lets you push OCI Artifacts to OCI Conformant registries, treating them as storage from Python applications.
A Python client library for the Orb billing REST API, providing typed request and response objects with both synchronous and asynchronous interfaces.
Install it if you are building a Python application that integrates with Orb's billing platform and want type-safe, well-documented API access.
Orbax Checkpoint provides asynchronous checkpointing for JAX machine learning workflows, supporting multiple storage formats and customizable serialization to save and restore model state during training.
Install it if you're running JAX training jobs that need reliable state persistence.
Orbax Export serializes JAX models to TensorFlow SavedModel format, enabling JAX-trained models to be deployed and used in TensorFlow environments.
A lightweight SDK for self-hosted tasks to send status updates, logs, and outputs back to Orchestra via HTTP, with decorator support for automatic lifecycle management.
However, the aging maintenance status (261 days since last release) suggests you should verify that the SDK remains compatible with your Orchestra version and that…
Adds comparison operators to Python enums so they can be sorted and compared using standard ordering syntax, with two strategies: ordering by definition sequence or by member values.
OrderedSet is a mutable collection that combines set semantics with list-like ordering and index-based access, supporting set operations while remembering insertion order.
Not recommended if you require active maintenance or expect frequent updates to track Python evolution.
Provides an OrderedDict implementation for Python 2.4–2.6, preserving insertion order in a dictionary-like object with O(1) amortized insertion, deletion, and lookup performance.
orderedmultidict provides a dictionary that stores multiple values per key while preserving insertion order, with an API compatible with Python's built-in dict.
Provides an Ordering enumeration and Compare protocol to unify comparison logic into a single method, letting you implement all ordering operations (`==`, `!=`, `<`, `>`, `<=`, `>=`) from one compare function.
Provides multiple ordered set implementations (OrderedSet, StableSet, OrderlySet, SortedSet) that maintain insertion order while supporting set operations like union, intersection, and difference.
A Python client for pushing ML feature data from offline sources to Orion Feature Store and retrieving feature metadata via protobuf serialization and Kafka integration.
However, the aging maintenance status (343 days since last release) means you should verify that it remains compatible with your Spark, Kafka, and Orion versions…
orjson is a fast JSON serialization and deserialization library that replaces Python's standard json module with native support for dataclasses, datetime, numpy arrays, and UUID objects.
Install it if you need faster JSON performance or native serialization of dataclasses, datetime, or numpy objects.
An async ORM for Python that unifies database models with pydantic validation, designed to work directly with async web frameworks like FastAPI without maintaining separate ORM and validation schemas.
Provides Rust-accelerated implementations of performance-critical utility functions for the ormar async ORM, automatically used by ormar when installed.
ormsgpack is a fast MessagePack serialization library for Python that encodes and decodes objects to and from the MessagePack binary format, with native support for dataclasses, datetimes, and numpy arrays.
Install it if you need fast, type-aware MessagePack serialization for dataclasses, datetimes, or numpy arrays.
A type-safe Python SDK for the orq.ai API, providing synchronous and asynchronous access to agent management, alerts, evaluations, and related operations.
However, verify the license terms before use, as the license status is currently unclear in the package metadata.