This repository implements the scratch spaces API for package-specific mutable containers of data. These spaces can contain datasets, text, binaries, or any other kind of data that would be convenient to store in a location specific to your package. As compared to Artifacts, these containers of data are mutable. Because the scratch space location on disk is not very user-friendly, scratch spaces should, in general, not be used for a storing files that the user must interact with through a file browser.

DeepDiffs.jl provides the deepdiff function, which finds and displays differences (diffs) between Julia data structures. It supports Vectors, Dicts, and Strings. When diffing dictionaries where values associated with a particular key may change, deepdiff will recurse into value to provide a more detailed diff.

This package provides an implementation of an associative container mapping (K,V) pairs via the type IntervalTreeK, V. The type K may be any ordered type.

Tracker.jl previously provided Flux.jl with automatic differentiation for its machine learning platform.

This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.

This package provides a Julia interface defining a collection of types (without instances) for implementing conventions about the scientific interpretation of data. This package makes a distinction between the machine type and the scientific type of a Julia object. A machine type refers to the Julia type being used to represent the object, for instance Float64. The scientific type refers to how the object should be interpreted, for instance Continuous or Multiclass3.

The SortingAlgorithms package provides three sorting algorithms that can be used with Julia's standard sorting API: heapsort, timsort and radixsort.

This package provides manually managed memory buffers backed by NTuples in Julia.

This package defines functionality to calculate volume element changes for functions that perform a change of variables (like coordinate transformations).

This package provides support for decoding and encoding texts between multiple character encodings. It is currently based on the iconv interface, and supports all major platforms using GNU libiconv.

This package supports SI units and also many other unit system.

This package provides a set of tools for working with tabular data in Julia. Its design and functionality are similar to those of Pandas from Python or data.frame, data.table and dplyr from R, making it a great general purpose data science tool, especially for those coming to Julia from R or Python.

This package provides generic methods and modules used in many of the other BioJulia packages. This package defines IO, exceptions, and other types or methods used by other BioJulia packages.

FileIO aims to provide a common framework for detecting file formats and dispatching to appropriate readers/writers. The two core functions in this package are called load and save, and offer high-level support for formatted files (in contrast with Julia's low-level read and write).

This package provides Julia implementation of C-style interface to CFITSIO functions with following features:

• Function names closely mirror the C interface (e.g., fits_open_file()).

• Functions operate on FITSFile, a thin wrapper for fitsfile C struct (FITSFile has concept of "current HDU", as in CFITSIO).

• Wrapper functions do check the return status from CFITSIO and throw an error with the appropriate message.

This package provides a minimal String type for Julia that allows for efficient string representation and transfer

This package provides several functions to manipulate strings with ANSI escape sequences.

This package provides the IOCapture.capture(f) function, which captures the standard output and standard error, and returns it as a string together with the return value.

This package provides the StructTypes.StructType trait for Julia types to declare the kind of "struct" they are, providing serialization/deserialization packages patterns and strategies to automatically construct objects.

MsgPack.jl is a MessagePack implementation in pure Julia, with type-driven, overloadable packing/unpacking functionality.

The VersionParsing package implements flexible parsing of version-number strings into Julia's built-in VersionNumber type, via the vparse(string) function. Unlike the VersionNumber(string) constructor, vparse(string) can handle version-number strings in a much wider range of formats than are encompassed by the semver standard. This is useful in order to support VersionNumber comparisons applied to "foreign" version numbers from external packages.

This package provides a simple and flexible IR format, expressive enough to work with both lowered and typed Julia code, as well as external IRs. It can be used with Julia metaprogramming tools such as Cassette.

StatsBase.jl is a Julia package that provides basic support for statistics. Particularly, it implements a variety of statistics-related functions, such as scalar statistics, high-order moment computation, counting, ranking, covariances, sampling, and empirical density estimation.

This package enables the Julia compiler to generate efficient code when running test cases. Test cases are typically run with flags that prevent efficient code generation. This package detects those flags and instead spawns a separate Julia process without the flags in which to run the test cases.