Packages
Wraps Apache Spark Connect to let Python applications connect to remote Dataproc Spark sessions via the Spark Connect protocol without extra setup steps.
Extracts and classifies properties from individual data values and matrices—type, alignment, width, digit counts, and formatting metadata for integers, floats, strings, booleans, datetimes, and special values like NaN and infinity.
DataRecorder provides buffered writing tools for saving data to files (CSV, XLSX, JSON, TXT, SQLite) with support for multithreaded access and automatic crash recovery.
A Python client library for programmatically interacting with the DataRobot platform API, enabling model building, deployment, and management workflows.
DRUM is a command-line tool for developing, testing, and deploying custom machine learning models written in Python, R, or Java before uploading them to DataRobot's platform.
A toolkit for building and deploying AI agents on DataRobot, providing unified LLM routing, agentic tools, multi-framework support (LangGraph, LlamaIndex, CrewAI, NIM), and orchestration through a low-code workflow interface.
Enforces content moderation on LLM prompts and responses using configurable guard rules, blocking or modifying text according to a YAML-defined policy before and after LLM inference.
However, the proprietary license and unclear license treatment require legal review before use outside DataRobot deployments.
Provides a unified Python interface for making predictions using DataRobot's prediction methods, abstracting away implementation details to simplify model inference.
However, the aging maintenance status means you should verify that the library supports your specific prediction methods and be prepared for slower issue resolution…
dataset simplifies reading and writing data to databases by wrapping SQLAlchemy with a JSON-like interface, letting you treat database tables as Python dictionaries.
Install it if you want to trade some ORM features for simplicity and speed of development—it's well-suited for scripts, prototypes, and lightweight data applications.
Loads and preprocesses datasets from the Hugging Face Hub or local files in many formats (CSV, JSON, Parquet, Arrow, audio, image, video, PDF, NIfTI), with built-in support for streaming, caching, and conversion to NumPy, Pandas, PyTorch, TensorFlow, and other frameworks.
Install it if you work with datasets for machine learning, data exploration, or preprocessing—it will save time and reduce boilerplate.
Downloads and loads curated time-series forecasting datasets (Favorita, M3, M4, M5, Hierarchical, Longhorizon, PHM2008) into pandas DataFrames, fetching from remote storage on first use.
Datasette is a web server and CLI tool that transforms SQLite databases into interactive, queryable websites with a REST API, designed for exploring and publishing data without writing custom code.
Datashader converts large datasets into accurate visual representations by rasterizing data through projection, aggregation, and transformation stages, enabling scalable visualization of millions of records.
DataSieve extends scikit-learn's Pipeline to handle row and feature transformations while propagating changes across X, y, and sample_weight arrays—enabling outlier removal, feature selection, and dimensionality reduction in a coordinated pipeline.
However, the aging maintenance status (460 days since last release) means you should verify compatibility with your specific pandas and scikit-learn versions before…
Provides probabilistic data structures (MinHash, HyperLogLog, and related indexes) for fast similarity estimation and cardinality counting on large datasets with minimal memory overhead.
Provides streaming algorithms (sketches) for approximate answers to big-data queries like cardinality estimation, quantiles, and frequent items with proven error bounds and orders-of-magnitude speed gains.
Datastar-py provides a Python SDK for building server-sent event (SSE) responses that allow backends to push real-time updates to browsers, with built-in helpers for multiple web frameworks.
Datazets provides a simple interface to download and import well-known example datasets for machine learning, data science, and educational purposes without manual data collection.
Install it if you regularly prototype with example data or teach data science; skip it if you work exclusively with proprietary or custom datasets.
Extracts publication dates from web pages by analyzing URL patterns and HTML content, returning both the extracted date and a confidence measure of its accuracy.
Adds a spaCy pipeline component that identifies date entities in text using regex and converts them to structured datetime objects via dateparser, storing results in a custom token extension.
However, it is abandoned (last updated 2023-08-24) with no ongoing maintenance, so install only if the fixed functionality is sufficient and you do not expect bug…
datedelta extends Python's datetime module with calendar-aware date arithmetic for years, months, weeks, and days, handling leap years and variable month lengths correctly.
Datefinder extracts date and time expressions from unstructured text and converts them into datetime objects or typed match objects with confidence and span information.
Parses strings into datetime objects and formats datetime objects into strings using explicit, human-readable format specifications instead of strftime codes.
Parses dates from text in multiple languages and formats, handling both absolute dates and relative expressions like "3 days ago" or "next month".
Install it if you need to parse dates from unstructured text or HTML; skip it if you only work with standardized, single-format date strings.
Provides a DateTime data type for working with date and time values, primarily designed for Zope integration but usable standalone with support for timezone conversion and flexible date/time string parsing.
Adds quarter-based date handling to Python's datetime module, letting you create, compare, and iterate over fiscal or calendar quarters as first-class objects.
However, the abandoned status means no future bug fixes or Python version support—evaluate whether you can maintain a fork or accept the risk of eventual…
DateTimeRange creates and manipulates time range objects, supporting operations like containment checks, intersections, unions, truncation, and iteration over intervals.
Install it if your code frequently reasons about time intervals, overlaps, or iteration across date ranges.
DateType provides type-checking-time wrapper types for Python's standard `datetime` module that enforce stricter type distinctions: preventing `datetime` from type-checking as `date`, and separating naive and aware datetimes into mutually-incompatible types.
Provides date and time arithmetic operations, including range generation and business day calculations, built on top of python-dateutil's relativedelta.
However, verify compatibility with your Python version and dependency stack, and consider whether you can rely on python-dateutil directly if maintenance becomes a…
Implements the Discord Audio & Video End-to-End Encryption (DAVE) Protocol using OpenMLS, enabling encrypted communication for Discord audio and video streams.
Reads DAWG (Directed Acyclic Word Graph) files created by the dawgdic C++ library or DAWG Python package, providing pure-Python access without compiled extensions.
Read-only access to DAWG (directed acyclic word graph) files created by the dawgdic C++ library or DAWG Python package, without requiring compiled extensions.
Install it if you have pre-built DAWG data and want to query it without compiled extensions or C dependencies.
Daytona is a Python SDK for managing and interacting with sandboxed computing environments—isolated, on-demand virtual computers that can execute code, run processes, and perform file and Git operations securely.
Install it if you need to programmatically manage sandboxed code execution environments and are comfortable with an alpha-stage SDK.
Generated Python API client for the Daytona Analytics API, providing programmatic access to Daytona's sandbox and code execution services.
However, verify the license status first—the package metadata does not confirm the Apache-2.0 license claimed in the repository.
Async Python client for the Daytona Analytics API, generated from OpenAPI specs, enabling programmatic interaction with Daytona sandbox environments and code execution.
However, verify the license terms first—the metadata does not clearly state the license, and you should confirm it aligns with your use case before committing to a…
Generated Python API client for Daytona, a cloud development environment platform, providing programmatic access to create and manage sandboxes and execute code remotely.
Install it if you need to automate sandbox management or integrate Daytona into a Python application; skip it if you do not use Daytona.
Async Python client for the Daytona API, enabling programmatic interaction with Daytona sandboxes and code execution services.
Install only if you are already using or planning to use Daytona's services; it is a specialized client, not a general-purpose library.
A deprecated alias package that ships identical code to its successor; maintained only for backward compatibility during a transition period.
Auto-generated Python client for the Daytona Toolbox API, providing programmatic access to file operations, process execution, git operations, LSP, and computer use automation (mouse, keyboard, screenshots).
An async Python client for the Daytona Toolbox API, generated from OpenAPI specs, enabling programmatic interaction with Daytona sandbox and code execution services.