0.5.dev0+git.20260409.dbbf22f - April 09, 2026 03:39 UTC
APIs Reference#
This is the class and function reference of scikit-plots. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full guidelines on their uses. For reference on concepts repeated across the APIs, see scikit-plots Glossary.
Object |
Description |
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str(object=’’) -> str |
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str(object=’’) -> str |
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Open the online documentation search page in the default web browser. |
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Context manager for global scikit-plots configuration. |
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Retrieve current values for configuration set by |
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Set global scikit-plots configuration. |
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Show libraries and system information on which SciPy was built |
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Print or return debugging information about the system, Python, dependencies, and hardware. |
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Return SP (scikitplot) logger instance. |
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Annoy Approximate Nearest Neighbors Index.
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Compiled with GCC/Clang. Using 512-bit AVX instructions. |
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Compiled with GCC/Clang. Using 512-bit AVX instructions. |
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High-level ANNoy index composed from mixins. |
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Compression used for |
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Mixin adding explicit Annoy-native persistence helpers. |
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Mixin that exports and restores index metadata. |
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NumPy / SciPy / pandas interoperability for Annoy-like indexes. |
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Mixin adding pickle support. |
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Persistence strategy used by |
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Mixin that adds convenient plotting methods to high-level Annoy wrappers. |
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User-facing neighbor queries for Annoy-like backends. |
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Plots the 2-dimensional projection of PCA on a given dataset. |
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Plots PCA components’ explained variance ratios. (new in v0.2.2) |
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Generate a plot of a sklearn model’s feature importances. |
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Generates a plot of the train and test learning curves for a classifier. |
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Plot the elbow curve for different values of K in KMeans clustering. |
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Plot residuals and fit various distributions to assess their goodness of fit. |
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Generates various evaluation plots for a classifier, including confusion matrix, |
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Generates a confusion matrix plot from predictions and true labels. |
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Generates the Precision-Recall AUC Curves from labels and predicted scores/probabilities. |
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Generates the ROC AUC curves from labels and predicted scores/probabilities. |
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Plot calibration curves for a set of classifier probability estimates. |
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Plots silhouette analysis of clusters provided. |
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Validates the labels passed into arguments such as
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Generate the data points necessary to plot the Cumulative Gain curve for binary classification tasks.
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Generate the data points necessary to plot the Kolmogorov-Smirnov (KS)
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Validate the provided axes and figure or create new ones if needed.
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Compute the sigmoid (expit) of a scalar input. |
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Compute the natural logarithm of the sigmoid (expit) of a scalar input. |
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Compute the logit (inverse sigmoid) of a scalar input. |
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py_print(message: str = ‘Hello, from Pybind11 C++!’) -> None |
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Compute the sigmoid function for the input array |
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Compute the softmax function. |
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Compute the log of the sum of exponentials of input elements. |
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Compute the logarithm of the softmax function. |
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High-level Python interface for the C++ ANNoy backend. |
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Compiled with GCC/Clang(Using 512-bit AVX instructions). |
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Compiled with GCC/Clang. Using 512-bit AVX instructions. |
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Compiled with GCC/Clang. Using 512-bit AVX instructions. |
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Astropy is a package intended to contain core functionality and some |
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This subpackage contains statistical tools provided for or used by Astropy. |
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Fortran to Python Interface Generator. |
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Return the directory that contains the |
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str(object=’’) -> str |
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str(object=’’) -> str |
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Abstract base class for all text chunkers. |
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Standard noise filter ported and improved from remarx’s |
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Abstract base class for all format-specific document readers. |
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A no-op reader that validates source existence and accessibility. |
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Abstract base class for corpus document filters. |
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Wrap any document stream with resilience, deduplication, and checkpointing. |
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Chains multiple |
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Return |
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Adapter that wraps a new-style chunker as a |
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Bridge for |
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Bridge for |
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Bridge for |
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Bridge for |
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Wrap chunker in a bridge if it is a new-style chunker. |
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Produce fixed-size sliding-window chunks over a document. |
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Configuration for |
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Unit of measurement for window size and step. |
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Split a document into paragraph-level |
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Configuration for |
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Supported sentence-splitting backends. |
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Split a document into sentence-level |
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Configuration for |
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Lemmatization backend. |
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Stemming algorithm. |
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Stopword list source. |
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Word tokenisation backend. |
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Process a document at word level, producing normalised token chunks. |
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Configuration for |
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Result of a corpus build operation. |
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Configuration for |
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Unified corpus builder — end-to-end pipeline orchestrator. |
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Component factory callables for |
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Wrap any callable as a |
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Custom backend callables for |
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Wrap any callable as a |
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Wrap any callable as a |
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Lifecycle callbacks for |
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Path subclass for non-Windows systems. |
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str(object=’’) -> str |
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Multi-backend sentence embedding engine with SHA-256 file caching. |
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str(object=’’) -> str |
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str(object=’’) -> str |
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str(object=’’) -> str |
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Export a corpus with embeddings to LLM training formats. |
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Unified embedding engine for any |
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frozenset() -> empty frozenset object |
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Configuration for |
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Pipeline component that populates NLP enrichment fields on |
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Export a list of documents to |
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Load |
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Remove exact duplicate lines while preserving first-occurrence order. |
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Remove HTML and XML tags from the document text. |
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Detect document language and set |
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Convert the document text to lowercase. |
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Apply a sequence of normalisers in order. |
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Abstract base class for all text normalisers. |
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Apply Unicode normalisation (NFC, NFD, NFKC, or NFKD). |
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Collapse runs of whitespace and optionally strip leading/trailing space. |
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Configuration for |
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Pipeline component that populates |
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Normalise text according to config. |
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Orchestrates the full corpus ingestion pipeline. |
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Immutable summary of a single pipeline run. |
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Create and export a corpus from a single source file. |
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ALTO XML reader for scanned document archives. |
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Text extraction from audio files via companion transcript/lyrics parsing, |
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Fully user-customizable reader for any file extension and resource type. |
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OCR-based text extraction from raster image files. |
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Markdown document reader. |
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PDF document reader with pdfminer.six → pypdf cascade. |
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reStructuredText document reader. |
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TEI/XML document reader with dramatic structure extraction. |
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Plain-text document reader. |
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Text extraction from video files via subtitle parsing and/or |
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Fetch a web page and extract structured text via BeautifulSoup. |
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Generic XML document reader with configurable XPath. |
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Extract the transcript of a YouTube video using |
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Generic ZIP archive reader — dispatches each member to its natural reader. |
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Configuration for similarity search. |
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A single search result. |
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Multi-mode similarity index over |
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Declarative descriptor for one or more document sources. |
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A single resolved source entry yielded by |
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Discriminant for the kind of source an entry represents. |
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Compile and import an extension module (module-only convenience wrapper). |
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Compile and import an extension module, with deterministic caching. |
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Compile a package of multiple extension modules from in-memory code strings. |
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Compile a package of multiple extension modules from existing |
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A compiled module cache entry. |
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A compiled package cache entry (multi-module build). |
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Find module cache entries matching an exact module name. |
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Find a single module cache entry by key. |
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Find a single package cache entry by key. |
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Return True if |
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Return all cache entry directories whose name is a valid cache key. |
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List module cache entries found under the cache directory. |
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List package cache entries found under the cache directory. |
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Create a deterministic cache key from a JSON-serializable mapping. |
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Resolve the cache directory path without creating it. |
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Read |
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Register an existing compiled extension artifact into the cache registry. |
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Resolve and create the cache directory. |
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Compute a runtime fingerprint for caching correctness. |
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SHA-256 digest of source bytes. |
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Write |
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Structural protocol for custom compiler callables. |
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Thread-unsafe module-level registry of custom compiler callables. |
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Register a custom compiler in the module-level registry. |
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Retrieve a registered custom compiler by name. |
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Return sorted list of registered custom compiler names. |
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Check prerequisites pure Python, setuptools only. |
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Check prerequisites compile C++ via Cython. |
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Check prerequisites full stack setuptools, Cython, pybind11, and NumPy. |
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Check prerequisites pybind11 only. |
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Check prerequisites own custom C-API. |
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Return the pybind11 include directory, or |
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Return the NumPy C-API include directory, or |
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Collect C/C++ source files from one or more files, directories, or globs. |
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Collect unique directories that contain C/C++ header files. |
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Built-in custom compiler: pybind11-only projects. |
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Built-in custom compiler: NumPy C-API projects. |
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Compute cache statistics. |
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Deterministically garbage-collect cached build entries. |
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Import an extension module from an explicit artifact path. |
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Import an extension module from raw artifact bytes. |
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Import an extension module from a filesystem path. |
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Acquire an exclusive build lock via atomic directory creation. |
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List the current alias→key mappings. |
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Pin a cache key under a human-friendly alias. |
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Resolve an alias to a cache key. |
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Remove an alias pin. |
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Normalized defaults produced by applying a profile. |
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Apply a profile with strict precedence rules. |
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Return True if running on Windows. |
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Resolve a profile name to deterministic defaults. |
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Build and import a multi-module extension package and return loaded modules. |
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Build and import a multi-module extension package from code strings. |
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Build and import a multi-module extension package and return loaded modules. |
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Build and import a multi-module extension package from |
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Check whether build prerequisites are importable. |
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Compile and import a Cython extension module and return the loaded module. |
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Compile and import a Cython extension module from source text. |
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Compile/import a Cython module from a |
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Compile and import all |
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Compile/import a Cython module from a |
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Export a cache entry directory to a destination folder. |
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Resolve (and create) the cache root directory. |
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Import a compiled extension artifact from raw bytes. |
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Import a compiled extension artifact from a path. |
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Import a cached module entry and return the loaded module. |
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Import the newest cached module entry matching |
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Import a cached package and return the loaded modules. |
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Import a cached package entry by cache key. |
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Import a cached module entry by cache key. |
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Import a pinned alias and return the loaded module(s). |
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Import a pinned alias. |
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List cached module entries. |
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List cached package entries. |
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Delete the entire cache directory. |
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Register a compiled extension artifact from bytes and import it. |
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Register an existing compiled extension artifact on disk, then import it. |
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Result of compiling/importing a single Cython extension module. |
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Result of a cache garbage-collection operation. |
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Cache statistics for the compiled-artifact cache root. |
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Result of compiling/importing a package of extension modules. |
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Immutable security policy applied to build inputs before compilation. |
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Immutable security policy applied to build inputs before compilation. |
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Raised when a build input violates the active |
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Immutable security policy applied to build inputs before compilation. |
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Return |
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Return |
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Return |
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Validate build inputs against a |
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Structured metadata for a template. |
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Build and import a multi-module package example and return loaded modules. |
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Build and import a multi-module package example and return a structured result. |
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Compile and import a Cython template and return the loaded module. |
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Compile and import a Cython template and return a structured result. |
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Copy a workflow template folder to a destination directory. |
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Generate Sphinx |
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Resolve a package example name to its on-disk folder path. |
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Resolve a template ID to an on-disk path. |
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Resolve a workflow name to its on-disk folder path. |
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List available multi-module package examples. |
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List available templates. |
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List available workflow template folders. |
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Load package example metadata from |
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Load template metadata from an adjacent |
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Read template source text. |
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Read metadata for a template and return a |
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Return the on-disk template root directory. |
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Return the workflow CLI template path. |
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Convert an arbitrary string into a valid Python module name. |
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Return a path to the cache directory for example datasets. |
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Report available example datasets, useful for reporting issues. |
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Load an example dataset from the online repository (requires internet). |
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Display a legend for the abbreviations of decile table column names. |
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Generate the Decile Table from labels and probabilities. |
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Generate the Decile-wise Lift Plot from labels and probabilities. |
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Generate the Decile based cumulative Lift Plot from labels and probabilities. |
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Generate the Decile-wise Lift Plot from labels and probabilities. |
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Generate the KS Statistic Plot from labels and probabilities. |
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Generate a decile table and four plots. |
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ModelPlotPy decile analysis. |
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Decile/ntile analysis for sklearn classifiers. |
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Plot response curve. |
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Plot cumulative response curve. |
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Plot cumulative lift curve. |
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Plot cumulative gains curve. |
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Plot response, cumulative response, cumulative lift, and cumulative gains as a 2x2 panel. |
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Plot costs and revenues curves. |
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Plot profit curve. |
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Plot ROI (return on investment) curve. |
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Module deprecation warning. |
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Generic exception thrown to surface failure information about external-facing operations. |
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Visible deprecation warning. |
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Enables ANNImputer |
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pipeline.py. |
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Mapping of envelope types to amplitude-modulation functions. |
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Generate a concatenated waveform from a musical composition input. |
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Play audio from a NumPy array using either IPython (for Jupyter) or sounddevice. |
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Plot the waveform of mono or multi-channel audio data. |
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Save waveform to an audio file using specified or auto-selected backend. |
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Save waveform as an MP3 file using pydub and ffmpeg, with support for mono or stereo. |
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Convert input sheet (str/list/dict) to a list of (note, octave, duration). |
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Display parsed notes or note frequencies from a musical sheet. |
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Serialize sheet notes to JSON or YAML string. |
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Enable serialization of compositions or note sheets. |
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NumPy Array API compatibility library |
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Extra array functions built on top of the array API standard. |
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A probability scale for matplotlib Axes. |
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Probability, percentile, and quantile plots. |
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Compute the plotting positions for a dataset. Heavily borrows from |
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Fits a line to x-y data in various forms (linear, log, prob scales). |
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sphinxext. |
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Add a |
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A role and directive to display mathtext in Sphinx. |
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A directive for including a Matplotlib plot in a Sphinx document. |
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Custom roles for the Matplotlib documentation. |
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Sphinx compatibility shim for docutils |
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Tweedie Distribution Module. |
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An instance of |
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A Tweedie continuous random variable inherited |
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Approximate K-nearest-neighbours (KNN) imputer with pluggable ANN backends. |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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int([x]) -> integer |
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A custom logging handler inherited from |
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A custom logging formatter inherited from |
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Return the effective level for the scikit-plots logger. |
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Return SP (scikitplot) logger instance. |
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Return the current verbosity level. |
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Set the logger’s level. |
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Set the verbosity level. |
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Log a message at the specified log level. |
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Log once per n calls from the same call site. |
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Log only for the first n calls from the same call site. |
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Log only if a condition is True. |
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Log a message at the specified log level. |
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Log a message at the DEBUG log level. |
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Log a message at the INFO log level. |
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Log a message at the WARNING log level. |
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Log a message at the WARN -> WARNING log level. |
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Log a message at the ERROR log level. |
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Log an error-like message at a specified level. |
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Log a message with severity ‘ERROR’ on the root logger. |
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Compatibility wrapper for legacy call sites. |
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Log a message at the CRITICAL log level. |
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Log a message at the FATAL -> CRITICAL log level. |
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Memory-mapped region with automatic resource management. |
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mmap_region(int size: int, int prot: int = 0x3, int flags: int = 0x22, int fd: int = -1, int offset: int = 0) -> MemoryMap |
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frozenset() -> empty frozenset object |
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Parsed capability set for |
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Validate that all long-form CLI flags in |
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Get supported |
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Import MLflow lazily with a user-friendly error. |
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Resolve a canonical artifact download function across MLflow versions. |
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Configuration that maps directly to |
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Session-level configuration for |
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Detect whether the current process is running in a Docker container. |
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A customizable provider for MLflow-like libraries. |
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Retrieve the currently active MLflow provider. |
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Set the active MLflow provider globally. |
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Temporarily set the MLflow provider for a context block. |
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Full snapshot of process environment for strict restoration. |
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Apply |
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Parse a minimal |
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Raised when a requested |
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Base exception for scikitplot.mlflow errors. |
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Raised when MLflow is required but not installed. |
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Raised when the managed MLflow server fails to start or exits prematurely. |
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Raised when an operation is rejected by the active |
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Artifact helper facade bound to a specific MLflow client/URI. |
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Model helper facade bound to a session-bound MLflow client. |
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Built-in immutable sequence. |
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Project-level configuration for MLflow usage across multiple scripts. |
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Write a ProjectConfig to a YAML file. |
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Ensure local backend/artifact directories exist. |
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Find a project root directory deterministically. |
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Resolve project markers deterministically. |
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Load project MLflow config from TOML or YAML based on file extension. |
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Load project MLflow config from a TOML file. |
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Load project MLflow config from a YAML file. |
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Normalize local store values for consistent multi-script usage. |
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Temporarily override module default markers for a block. |
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Set the module default markers. |
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Wait until the MLflow tracking REST API responds. |
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Declarative security policy for |
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Declarative security policy for |
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Declarative security policy for |
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Return the currently active |
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Temporarily activate a |
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Set the active |
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Spawned MLflow server process state. |
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Build the CLI args for |
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Build a deterministic |
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Spawn an MLflow server subprocess. |
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A handle that proxies the upstream |
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Create a strict, context-managed MLflow session. |
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Create an MLflow session using a shared project config file (TOML or YAML). |
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Create an MLflow session using a shared project TOML config. |
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Parsed MLflow version. |
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Check whether MLflow is installed in the current Python environment. |
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Retrieve the installed MLflow version (if available). |
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Standardized project config paths used by the workflow. |
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Return the path to the built-in demo config shipped with the package. |
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Compute standard config file paths for a project. |
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Export the built-in demo config into the current project. |
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Patch |
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Run a beginner-friendly end-to-end demo workflow. |
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Run the built-in end-to-end MLflow workflow demo. |
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Return the absolute path to the NumCpp C++ headers include directory. |
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dot(a: numpy.ndarray, b: numpy.ndarray) -> numpy.ndarray |
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Encode categorical features into dummy/indicator 0/1 variables. |
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Multi-column multi-label string column one-hot encoder [Rbcee2ffc57f9-1]. |
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32-bit KISS RNG with complete serialization support. |
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Low-level 64-bit KISS RNG with context manager support. |
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Factory function for auto-detecting 32-bit vs 64-bit RNG. |
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Seed sequence compatible with numpy.random.SeedSequence. |
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NumPy-compatible BitGenerator using KISS algorithm with complete serialization. |
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High-level random number generator using KISS algorithm. |
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NumPy RandomState-compatible interface with complete serialization. |
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Create default KISS random number generator. |
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Context manager for temporary RNG. |
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Random sample from array. |
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Random integers in [low, high) or [low, high]. |
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Normal distribution (Box-Muller transform). |
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Randomly permute sequence or return permuted range. |
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Random floats in [0, 1). |
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Shuffle array in-place (Fisher-Yates algorithm). |
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Uniform distribution in [low, high). |
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Plot PR or ROC curves with a seaborn-like API. |
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Visualization of the Confusion Matrix [Ra7e29df24177-1] alongside a text report showing key classification metrics. |
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Given binary labels y_true (0/1) and probabilities y_score 1d array, compute/plot a decile [Rd1ed195c7ca1-2] table. |
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Pretty-print the legend of decile table column names. |
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Bayesian blocks fitness for binned or unbinned events. |
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Base class for bayesian blocks fitness functions. |
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Bayesian blocks fitness for point measures. |
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Bayesian blocks fitness for regular events. |
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Compute optimal segmentation of data with Scargle’s Bayesian Blocks. |
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Binomial proportion and confidence interval in bins of a continuous |
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Binomial proportion confidence interval given k successes, |
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Performs bootstrap resampling on numpy arrays. |
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Construct a callable piecewise-linear CDF from a pair of arrays. |
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Fold the weighted intervals to the interval (0,1). |
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Convert a string or number to a floating point number, if possible. |
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Convert a string or number to a floating point number, if possible. |
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Histogram of a piecewise-constant weight function. |
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Compute the length of overlap of two intervals. |
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Compute the Kuiper statistic. |
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Compute the false positive probability for the Kuiper statistic. |
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Compute the Kuiper statistic to compare two samples. |
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Calculate a robust standard deviation using the median absolute deviation (MAD). |
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Calculate the median absolute deviation (MAD). |
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Poisson parameter confidence interval given observed counts. |
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Computes the signal to noise ratio for source being observed in the |
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Calculate histogram bin edges like |
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Return the optimal histogram bin width using the Freedman-Diaconis rule. |
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Enhanced histogram function, providing adaptive binnings. |
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Return the optimal histogram bin width using Knuth’s rule. |
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Return the optimal histogram bin width using Scott’s rule. |
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Computes the Akaike Information Criterion (AIC). |
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Computes the Akaike Information Criterion assuming that the observations |
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Computes the Bayesian Information Criterion (BIC) given the log of the |
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Computes the Bayesian Information Criterion (BIC) assuming that the |
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A Tweedie continuous random variable inherited |
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An instance of |
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Lightweight ⏱ timing context manager with |
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Generate portable, collision-resistant filenames and paths. |
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Make Convenience wrapper to build a unique path (callable with zero args). |
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Generates an architectural visualization for a given linear Keras |
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Generates an architectural visualization for a given linear Keras |
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A factory class for dynamically generating a dummy Keras layer with custom spacing. |
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Scikit-plots Factory API module. |
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Generates the ROC curves from labels and predicted scores/probabilities |
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Generates the Precision Recall Curve from labels and probabilities |