Julia has two mechanisms for loading code:
- Code inclusion: e.g.
include("source.jl"). Inclusion allows you to split a single program across multiple source files. The expression
include("source.jl")causes the contents of the file
source.jlto be evaluated in the global scope of the module where the
includecall occurs. If
include("source.jl")is called multiple times,
source.jlis evaluated multiple times. The included path,
source.jl, is interpreted relative to the file where the
includecall occurs. This makes it simple to relocate a subtree of source files. In the REPL, included paths are interpreted relative to the current working directory,
- Package loading: e.g.
using X. The import mechanism allows you to load a package—i.e. an independent, reusable collection of Julia code, wrapped in a module—and makes the resulting module available by the name
Xinside of the importing module. If the same
Xpackage is imported multiple times in the same Julia session, it is only loaded the first time—on subsequent imports, the importing module gets a reference to the same module. Note though, that
import Xcan load different packages in different contexts:
Xcan refer to one package named
Xin the main project but potentially to different packages also named
Xin each dependency. More on this below.
Code inclusion is quite straightforward and simple: it evaluates the given source file in the context of the caller. Package loading is built on top of code inclusion and serves a different purpose. The rest of this chapter focuses on the behavior and mechanics of package loading.
A package is a source tree with a standard layout providing functionality that can be reused by other Julia projects. A package is loaded by
import X or
using X statements. These statements also make the module named
X—which results from loading the package code—available within the module where the import statement occurs. The meaning of
import X is context-dependent: which
X package is loaded depends on what code the statement occurs in. Thus, handling of
import X happens in two stages: first, it determines what package is defined to be
X in this context; second, it determines where that particular
X package is found.
These questions are answered by searching through the project environments listed in
LOAD_PATH for project files (
JuliaProject.toml), manifest files (
JuliaManifest.toml), or folders of source files.
Most of the time, a package is uniquely identifiable simply from its name. However, sometimes a project might encounter a situation where it needs to use two different packages that share the same name. While you might be able fix this by renaming one of the packages, being forced to do so can be highly disruptive in a large, shared code base. Instead, Julia's code loading mechanism allows the same package name to refer to different packages in different components of an application.
Julia supports federated package management, which means that multiple independent parties can maintain both public and private packages and registries of packages, and that projects can depend on a mix of public and private packages from different registries. Packages from various registries are installed and managed using a common set of tools and workflows. The
Pkg package manager that ships with Julia lets you install and manage your projects' dependencies. It assists in creating and manipulating project files (which describe what other projects that your project depends on), and manifest files (which snapshot exact versions of your project's complete dependency graph).
One consequence of federation is that there cannot be a central authority for package naming. Different entities may use the same name to refer to unrelated packages. This possibility is unavoidable since these entities do not coordinate and may not even know about each other. Because of the lack of a central naming authority, a single project may end up depending on different packages that have the same name. Julia's package loading mechanism does not require package names to be globally unique, even within the dependency graph of a single project. Instead, packages are identified by universally unique identifiers (UUIDs), which get assigned when each package is created. Usually you won't have to work directly with these somewhat cumbersome 128-bit identifiers since
Pkg will take care of generating and tracking them for you. However, these UUIDs provide the definitive answer to the question of "what package does
X refer to?"
Since the decentralized naming problem is somewhat abstract, it may help to walk through a concrete scenario to understand the issue. Suppose you're developing an application called
App, which uses two packages:
Priv is a private package that you created, whereas
Pub is a public package that you use but don't control. When you created
Priv, there was no public package by the name
Priv. Subsequently, however, an unrelated package also named
Priv has been published and become popular. In fact, the
Pub package has started to use it. Therefore, when you next upgrade
Pub to get the latest bug fixes and features,
App will end up depending on two different packages named
Priv—through no action of yours other than upgrading.
App has a direct dependency on your private
Priv package, and an indirect dependency, through
Pub, on the new public
Priv package. Since these two
Priv packages are different but are both required for
App to continue working correctly, the expression
import Priv must refer to different
Priv packages depending on whether it occurs in
App's code or in
Pub's code. To handle this, Julia's package loading mechanism distinguishes the two
Priv packages by their UUID and picks the correct one based on its context (the module that called
import). How this distinction works is determined by environments, as explained in the following sections.
An environment determines what
import X and
using X mean in various code contexts and what files these statements cause to be loaded. Julia understands two kinds of environments:
- A project environment is a directory with a project file and an optional manifest file, and forms an explicit environment. The project file determines what the names and identities of the direct dependencies of a project are. The manifest file, if present, gives a complete dependency graph, including all direct and indirect dependencies, exact versions of each dependency, and sufficient information to locate and load the correct version.
- A package directory is a directory containing the source trees of a set of packages as subdirectories, and forms an implicit environment. If
Xis a subdirectory of a package directory and
X/src/X.jlexists, then the package
Xis available in the package directory environment and
X/src/X.jlis the source file by which it is loaded.
These can be intermixed to create a stacked environment: an ordered set of project environments and package directories, overlaid to make a single composite environment. The precedence and visibility rules then combine to determine which packages are available and where they get loaded from. Julia's load path forms a stacked environment, for example.
These environment each serve a different purpose:
- Project environments provide reproducibility. By checking a project environment into version control—e.g. a git repository—along with the rest of the project's source code, you can reproduce the exact state of the project and all of its dependencies. The manifest file, in particular, captures the exact version of every dependency, identified by a cryptographic hash of its source tree, which makes it possible for
Pkgto retrieve the correct versions and be sure that you are running the exact code that was recorded for all dependencies.
- Package directories provide convenience when a full carefully-tracked project environment is unnecessary. They are useful when you want to put a set of packages somewhere and be able to directly use them, without needing to create a project environment for them.
- Stacked environments allow for adding tools to the primary environment. You can push an environment of development tools onto the end of the stack to make them available from the REPL and scripts, but not from inside packages.
At a high-level, each environment conceptually defines three maps: roots, graph and paths. When resolving the meaning of
import X, the roots and graph maps are used to determine the identity of
X, while the paths map is used to locate the source code of
X. The specific roles of the three maps are:
An environment's roots map assigns package names to UUIDs for all the top-level dependencies that the environment makes available to the main project (i.e. the ones that can be loaded in
Main). When Julia encounters
import Xin the main project, it looks up the identity of
An environment's graph is a multilevel map which assigns, for each
contextUUID, a map from names to UUIDs, similar to the roots map but specific to that
context. When Julia sees
import Xin the code of the package whose UUID is
context, it looks up the identity of
graph[context][:X]. In particular, this means that
import Xcan refer to different packages depending on
The paths map assigns to each package UUID-name pair, the location of that package's entry-point source file. After the identity of
import Xhas been resolved to a UUID via roots or graph (depending on whether it is loaded from the main project or a dependency), Julia determines what file to load to acquire
Xby looking up
paths[uuid,:X]in the environment. Including this file should define a module named
X. Once this package is loaded, any subsequent import resolving to the same
uuidwill create a new binding to the already-loaded package module.
Each kind of environment defines these three maps differently, as detailed in the following sections.
For ease of understanding, the examples throughout this chapter show full data structures for roots, graph and paths. However, Julia's package loading code does not explicitly create these. Instead, it lazily computes only as much of each structure as it needs to load a given package.
A project environment is determined by a directory containing a project file called
Project.toml, and optionally a manifest file called
Manifest.toml. These files may also be called
JuliaManifest.toml, in which case
Manifest.toml are ignored. This allows for coexistence with other tools that might consider files called
Manifest.toml significant. For pure Julia projects, however, the names
Manifest.toml are preferred.
The roots, graph and paths maps of a project environment are defined as follows:
The roots map of the environment is determined by the contents of the project file, specifically, its top-level
uuid entries and its
[deps] section (all optional). Consider the following example project file for the hypothetical application,
App, as described earlier:
name = "App" uuid = "8f986787-14fe-4607-ba5d-fbff2944afa9" [deps] Priv = "ba13f791-ae1d-465a-978b-69c3ad90f72b" Pub = "c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1"
This project file implies the following roots map, if it was represented by a Julia dictionary:
roots = Dict( :App => UUID("8f986787-14fe-4607-ba5d-fbff2944afa9"), :Priv => UUID("ba13f791-ae1d-465a-978b-69c3ad90f72b"), :Pub => UUID("c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1"), )
Given this roots map, in
App's code the statement
import Priv will cause Julia to look up
roots[:Priv], which yields
ba13f791-ae1d-465a-978b-69c3ad90f72b, the UUID of the
Priv package that is to be loaded in that context. This UUID identifies which
Priv package to load and use when the main application evaluates
The dependency graph of a project environment is determined by the contents of the manifest file, if present. If there is no manifest file, graph is empty. A manifest file contains a stanza for each of a project's direct or indirect dependencies. For each dependency, the file lists the package's UUID and a source tree hash or an explicit path to the source code. Consider the following example manifest file for
[[Priv]] # the private one deps = ["Pub", "Zebra"] uuid = "ba13f791-ae1d-465a-978b-69c3ad90f72b" path = "deps/Priv" [[Priv]] # the public one uuid = "2d15fe94-a1f7-436c-a4d8-07a9a496e01c" git-tree-sha1 = "1bf63d3be994fe83456a03b874b409cfd59a6373" version = "0.1.5" [[Pub]] uuid = "c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1" git-tree-sha1 = "9ebd50e2b0dd1e110e842df3b433cb5869b0dd38" version = "2.1.4" [Pub.deps] Priv = "2d15fe94-a1f7-436c-a4d8-07a9a496e01c" Zebra = "f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62" [[Zebra]] uuid = "f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62" git-tree-sha1 = "e808e36a5d7173974b90a15a353b564f3494092f" version = "3.4.2"
This manifest file describes a possible complete dependency graph for the
- There are two different packages named
Privthat the application uses. It uses a private package, which is a root dependency, and a public one, which is an indirect dependency through
Pub. These are differentiated by their distinct UUIDs, and they have different deps:
- The private
Privdepends on the
- The public
Privhas no dependencies.
- The private
- The application also depends on the
Pubpackage, which in turn depends on the public
Privand the same
Zebrapackage that the private
Privpackage depends on.
This dependency graph represented as a dictionary, looks like this:
graph = Dict( # Priv – the private one: UUID("ba13f791-ae1d-465a-978b-69c3ad90f72b") => Dict( :Pub => UUID("c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1"), :Zebra => UUID("f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62"), ), # Priv – the public one: UUID("2d15fe94-a1f7-436c-a4d8-07a9a496e01c") => Dict(), # Pub: UUID("c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1") => Dict( :Priv => UUID("2d15fe94-a1f7-436c-a4d8-07a9a496e01c"), :Zebra => UUID("f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62"), ), # Zebra: UUID("f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62") => Dict(), )
Given this dependency
graph, when Julia sees
import Priv in the
Pub package—which has UUID
c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1—it looks up:
2d15fe94-a1f7-436c-a4d8-07a9a496e01c, which indicates that in the context of the
import Priv refers to the public
Priv package, rather than the private one which the app depends on directly. This is how the name
Priv can refer to different packages in the main project than it does in one of its package's dependencies, which allows for duplicate names in the package ecosystem.
What happens if
import Zebra is evaluated in the main
App code base? Since
Zebra does not appear in the project file, the import will fail even though
Zebra does appear in the manifest file. Moreover, if
import Zebra occurs in the public
Priv package—the one with UUID
2d15fe94-a1f7-436c-a4d8-07a9a496e01c—then that would also fail since that
Priv package has no declared dependencies in the manifest file and therefore cannot load any packages. The
Zebra package can only be loaded by packages for which it appear as an explicit dependency in the manifest file: the
Pub package and one of the
The paths map of a project environment is extracted from the manifest file. The path of a package
X is determined by these rules (in order):
- If the project file in the directory matches
X, then either:
- It has a toplevel
uuidwill be mapped to that path, interpreted relative to the directory containing the project file.
uuidis mapped to
src/X.jlrelative to the directory containing the project file.
- It has a toplevel
- If the above is not the case and the project file has a corresponding manifest file and the manifest contains a stanza matching
- If it has a
pathentry, use that path (relative to the directory containing the manifest file).
- If it has a
git-tree-sha1entry, compute a deterministic hash function of
slug—and look for a directory named
packages/X/$slugin each directory in the Julia
DEPOT_PATHglobal array. Use the first such directory that exists.
- If it has a
If any of these result in success, the path to the source code entry point will be either that result, the relative path from that result plus
src/X.jl; otherwise, there is no path mapping for
uuid. When loading
X, if no source code path is found, the lookup will fail, and the user may be prompted to install the appropriate package version or to take other corrective action (e.g. declaring
X as a dependency).
In the example manifest file above, to find the path of the first
Priv package—the one with UUID
ba13f791-ae1d-465a-978b-69c3ad90f72b—Julia looks for its stanza in the manifest file, sees that it has a
path entry, looks at
deps/Priv relative to the
App project directory—let's suppose the
App code lives in
/home/me/projects/App/deps/Priv exists and therefore loads
Priv from there.
If, on the other hand, Julia was loading the other
Priv package—the one with UUID
2d15fe94-a1f7-436c-a4d8-07a9a496e01c—it finds its stanza in the manifest, see that it does not have a
path entry, but that it does have a
git-tree-sha1 entry. It then computes the
slug for this UUID/SHA-1 pair, which is
HDkrT (the exact details of this computation aren't important, but it is consistent and deterministic). This means that the path to this
Priv package will be
packages/Priv/HDkrT/src/Priv.jl in one of the package depots. Suppose the contents of
["/home/me/.julia", "/usr/local/julia"], then Julia will look at the following paths to see if they exist:
Julia uses the first of these that exists to try to load the public
Priv package from the file
packages/Priv/HDKrT/src/Priv.jl in the depot where it was found.
Here is a representation of a possible paths map for our example
App project environment, as provided in the Manifest given above for the dependency graph, after searching the local file system:
paths = Dict( # Priv – the private one: (UUID("ba13f791-ae1d-465a-978b-69c3ad90f72b"), :Priv) => # relative entry-point inside `App` repo: "/home/me/projects/App/deps/Priv/src/Priv.jl", # Priv – the public one: (UUID("2d15fe94-a1f7-436c-a4d8-07a9a496e01c"), :Priv) => # package installed in the system depot: "/usr/local/julia/packages/Priv/HDkr/src/Priv.jl", # Pub: (UUID("c07ecb7d-0dc9-4db7-8803-fadaaeaf08e1"), :Pub) => # package installed in the user depot: "/home/me/.julia/packages/Pub/oKpw/src/Pub.jl", # Zebra: (UUID("f7a24cb4-21fc-4002-ac70-f0e3a0dd3f62"), :Zebra) => # package installed in the system depot: "/usr/local/julia/packages/Zebra/me9k/src/Zebra.jl", )
This example map includes three different kinds of package locations (the first and third are part of the default load path):
- The private
Privpackage is "vendored" inside the
- The public
Zebrapackages are in the system depot, where packages installed and managed by the system administrator live. These are available to all users on the system.
Pubpackage is in the user depot, where packages installed by the user live. These are only available to the user who installed them.
Package directories provide a simpler kind of environment without the ability to handle name collisions. In a package directory, the set of top-level packages is the set of subdirectories that "look like" packages. A package
X exists in a package directory if the directory contains one of the following "entry point" files:
Which dependencies a package in a package directory can import depends on whether the package contains a project file:
- If it has a project file, it can only import those packages which are identified in the
[deps]section of the project file.
- If it does not have a project file, it can import any top-level package—i.e. the same packages that can be loaded in
Mainor the REPL.
The roots map is determined by examining the contents of the package directory to generate a list of all packages that exist. Additionally, a UUID will be assigned to each entry as follows: For a given package found inside the folder
X/Project.tomlexists and has a
uuidis that value.
X/Project.tomlexists and but does not have a top-level UUID entry,
uuidis a dummy UUID generated by hashing the canonical (real) path to
- Otherwise (if
Project.tomldoes not exist), then
uuidis the all-zero nil UUID.
The dependency graph of a project directory is determined by the presence and contents of project files in the subdirectory of each package. The rules are:
- If a package subdirectory has no project file, then it is omitted from graph and import statements in its code are treated as top-level, the same as the main project and REPL.
- If a package subdirectory has a project file, then the graph entry for its UUID is the
[deps]map of the project file, which is considered to be empty if the section is absent.
As an example, suppose a package directory has the following structure and content:
Aardvark/ src/Aardvark.jl: import Bobcat import Cobra Bobcat/ Project.toml: [deps] Cobra = "4725e24d-f727-424b-bca0-c4307a3456fa" Dingo = "7a7925be-828c-4418-bbeb-bac8dfc843bc" src/Bobcat.jl: import Cobra import Dingo Cobra/ Project.toml: uuid = "4725e24d-f727-424b-bca0-c4307a3456fa" [deps] Dingo = "7a7925be-828c-4418-bbeb-bac8dfc843bc" src/Cobra.jl: import Dingo Dingo/ Project.toml: uuid = "7a7925be-828c-4418-bbeb-bac8dfc843bc" src/Dingo.jl: # no imports
Here is a corresponding roots structure, represented as a dictionary:
roots = Dict( :Aardvark => UUID("00000000-0000-0000-0000-000000000000"), # no project file, nil UUID :Bobcat => UUID("85ad11c7-31f6-5d08-84db-0a4914d4cadf"), # dummy UUID based on path :Cobra => UUID("4725e24d-f727-424b-bca0-c4307a3456fa"), # UUID from project file :Dingo => UUID("7a7925be-828c-4418-bbeb-bac8dfc843bc"), # UUID from project file )
Here is the corresponding graph structure, represented as a dictionary:
graph = Dict( # Bobcat: UUID("85ad11c7-31f6-5d08-84db-0a4914d4cadf") => Dict( :Cobra => UUID("4725e24d-f727-424b-bca0-c4307a3456fa"), :Dingo => UUID("7a7925be-828c-4418-bbeb-bac8dfc843bc"), ), # Cobra: UUID("4725e24d-f727-424b-bca0-c4307a3456fa") => Dict( :Dingo => UUID("7a7925be-828c-4418-bbeb-bac8dfc843bc"), ), # Dingo: UUID("7a7925be-828c-4418-bbeb-bac8dfc843bc") => Dict(), )
A few general rules to note:
- A package without a project file can depend on any top-level dependency, and since every package in a package directory is available at the top-level, it can import all packages in the environment.
- A package with a project file cannot depend on one without a project file since packages with project files can only load packages in
graphand packages without project files do not appear in
- A package with a project file but no explicit UUID can only be depended on by packages without project files since dummy UUIDs assigned to these packages are strictly internal.
Observe the following specific instances of these rules in our example:
Aardvarkcan import on any of
Dingo; it does import
Bobcatcan and does import both
Dingo, which both have project files with UUIDs and are declared as dependencies in
Bobcatcannot depend on
Aardvarkdoes not have a project file.
Cobracan and does import
Dingo, which has a project file and UUID, and is declared as a dependency in
Cobracannot depend on
Bobcatsince neither have real UUIDs.
Dingocannot import anything because it has a project file without a
The paths map in a package directory is simple: it maps subdirectory names to their corresponding entry-point paths. In other words, if the path to our example project directory is
/home/me/animals then the
paths map could be represented by this dictionary:
paths = Dict( (UUID("00000000-0000-0000-0000-000000000000"), :Aardvark) => "/home/me/AnimalPackages/Aardvark/src/Aardvark.jl", (UUID("85ad11c7-31f6-5d08-84db-0a4914d4cadf"), :Bobcat) => "/home/me/AnimalPackages/Bobcat/src/Bobcat.jl", (UUID("4725e24d-f727-424b-bca0-c4307a3456fa"), :Cobra) => "/home/me/AnimalPackages/Cobra/src/Cobra.jl", (UUID("7a7925be-828c-4418-bbeb-bac8dfc843bc"), :Dingo) => "/home/me/AnimalPackages/Dingo/src/Dingo.jl", )
Since all packages in a package directory environment are, by definition, subdirectories with the expected entry-point files, their
paths map entries always have this form.
The third and final kind of environment is one that combines other environments by overlaying several of them, making the packages in each available in a single composite environment. These composite environments are called environment stacks. The Julia
LOAD_PATH global defines an environment stack—the environment in which the Julia process operates. If you want your Julia process to have access only to the packages in one project or package directory, make it the only entry in
LOAD_PATH. It is often quite useful, however, to have access to some of your favorite tools—standard libraries, profilers, debuggers, personal utilities, etc.—even if they are not dependencies of the project you're working on. By adding an environment containing these tools to the load path, you immediately have access to them in top-level code without needing to add them to your project.
The mechanism for combining the roots, graph and paths data structures of the components of an environment stack is simple: they are merged as dictionaries, favoring earlier entries over later ones in the case of key collisions. In other words, if we have
stack = [env₁, env₂, …] then we have:
roots = reduce(merge, reverse([roots₁, roots₂, …])) graph = reduce(merge, reverse([graph₁, graph₂, …])) paths = reduce(merge, reverse([paths₁, paths₂, …]))
pathsᵢ variables correspond to the subscripted environments,
envᵢ, contained in
reverse is present because
merge favors the last argument rather than first when there are collisions between keys in its argument dictionaries. There are a couple of noteworthy features of this design:
- The primary environment—i.e. the first environment in a stack—is faithfully embedded in a stacked environment. The full dependency graph of the first environment in a stack is guaranteed to be included intact in the stacked environment including the same versions of all dependencies.
- Packages in non-primary environments can end up using incompatible versions of their dependencies even if their own environments are entirely compatible. This can happen when one of their dependencies is shadowed by a version in an earlier environment in the stack (either by graph or path, or both).
Since the primary environment is typically the environment of a project you're working on, while environments later in the stack contain additional tools, this is the right trade-off: it's better to break your development tools but keep the project working. When such incompatibilities occur, you'll typically want to upgrade your dev tools to versions that are compatible with the main project.
Preferences are dictionaries of metadata that influence package behavior within an environment. The preferences system supports reading preferences at compile-time, which means that at code-loading time, we must ensure that a particular
.ji file was built with the same preferences as the current environment before loading it. The public API for modifying Preferences is contained within the Preferences.jl package. Preferences are stored as TOML dictionaries within a
(Julia)LocalPreferences.toml file next to the currently-active project. If a preference is "exported", it is instead stored within the
(Julia)Project.toml instead. The intention is to allow shared projects to contain shared preferences, while allowing for users themselves to override those preferences with their own settings in the LocalPreferences.toml file, which should be .gitignored as the name implies.
Preferences that are accessed during compilation are automatically marked as compile-time preferences, and any change recorded to these preferences will cause the Julia compiler to recompile any cached precompilation
.ji files for that module. This is done by serializing the hash of all compile-time preferences during compilation, then checking that hash against the current environment when searching for the proper
.ji file to load.
Preferences can be set with depot-wide defaults; if package Foo is installed within your global environment and it has preferences set, these preferences will apply as long as your global environment is part of your
LOAD_PATH. Preferences in environments higher up in the environment stack get overridden by the more proximal entries in the load path, ending with the currently active project. This allows depot-wide preference defaults to exist, with active projects able to merge or even completely overwrite these inherited preferences. See the docstring for
Preferences.set_preferences!() for the full details of how to set preferences to allow or disallow merging.
Federated package management and precise software reproducibility are difficult but worthy goals in a package system. In combination, these goals lead to a more complex package loading mechanism than most dynamic languages have, but it also yields scalability and reproducibility that is more commonly associated with static languages. Typically, Julia users should be able to use the built-in package manager to manage their projects without needing a precise understanding of these interactions. A call to
Pkg.add("X") will add to the appropriate project and manifest files, selected via
Pkg.activate("Y"), so that a future call to
import X will load
X without further thought.