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Developer tooling for Julia namespace management: detecting implicit imports, improper explicit imports, and improper qualified accesses

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ExplicitImports

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Summary

ExplicitImports.jl helps detect implicit imports and mitigate issues with the alternatives (explicit imports and qualified accesses).

Problem Example Interactive detection Programmatic detection Regression-testing check
Implicit imports using LinearAlgebra print_explicit_imports implicit_imports check_no_implicit_imports
Non-owning import using LinearAlgebra: map print_explicit_imports improper_explicit_imports check_all_explicit_imports_via_owners
Non-public import using LinearAlgebra: _svd! print_explicit_imports with report_non_public=true improper_explicit_imports check_all_explicit_imports_are_public
Stale import using LinearAlgebra: svd # unused print_explicit_imports improper_explicit_imports check_no_stale_explicit_imports
Non-owning access LinearAlgebra.map print_explicit_imports improper_qualified_accesses check_all_qualified_accesses_via_owners
Non-public access LinearAlgebra._svd! print_explicit_imports with report_non_public=true improper_qualified_accesses check_all_qualified_accesses_are_public
Self-qualified access Foo.bar within the module Foo print_explicit_imports improper_qualified_accesses check_no_self_qualified_accesses

To understand these examples, note that:

  • svd is an API function of LinearAlgebra
  • map is an API function of Base, which happens to be present in the LinearAlgebra namespace
  • _svd! is a private function of LinearAlgebra

Goals

  • Figure out what implicit imports a Julia module is relying on, in order to make them explicit.
  • Provide tools to help make explicit imports and (more recently) qualified accesses more ergonomic

Terminology

  • implicit import: a name x available in a module due to using XYZ for some package or module XYZ. This name has not been explicitly imported; rather, it is simply available since it is exported by XYZ.
  • explicit import: a name x available in a module due to using XYZ: x or import XYZ: x for some package or module XYZ.
  • qualified access: a name x accessed via XYZ.x

Why

Relying on implicit imports can be problematic, as Base or another package can start exporting that name as well, resulting in a clash. This is a tricky situation because adding a new feature to Base (or a package) and exporting it is not considered a breaking change to its API, but it can cause working code to stop working due to these clashes.

If you've even seen a warning like:

WARNING: both X and Y export "foo"; uses of it in module MyPackage must be qualified

Then this is the kind of clash at issue. When this occurs, the name foo won't point to either package's name, since it is ambiguous which one it should be. However, if the package code is relying on the name foo existing, then there's trouble.

One fix, as the warning suggests, is to qualify the use foo by writing e.g. X.foo or Y.foo. Another option is to explicitly import it, by writing using X: foo instead of just using X.

There are various takes on how problematic this issue is, to what extent this occurs in practice, and to what extent it is worth mitigating. See julia#42080 for some discussion on this.

Personally, I don't think this is always a huge issue, and that it's basically fine for packages to use implicit imports if that is their preferred style and they understand the risk. But I do think this issue is somewhat a "hole" in the semver system as it applies to Julia packages, and I wanted to create some tooling to make it easier to mitigate the issue for package authors who would prefer to not rely on implicit imports.

Example

julia> using ExplicitImports

julia> print_explicit_imports(ExplicitImports)
WARNING: both JuliaSyntax and Base export "parse"; uses of it in module ExplicitImports must be qualified
  Module ExplicitImports is relying on implicit imports for 7 names. These could be explicitly imported as follows:

  using AbstractTrees: AbstractTrees, Leaves, TreeCursor, children, nodevalue
  using JuliaSyntax: JuliaSyntax, @K_str

  Additionally, module ExplicitImports has 1 self-qualified access:

    •  parent was accessed as ExplicitImports.parent inside ExplicitImports at /Users/eph/ExplicitImports/src/deprecated.jl:79:21

  Additionally, module ExplicitImports accesses 1 name from non-owner modules:

    •  parent has owner AbstractTrees but it was accessed from ExplicitImports at
       /Users/eph/ExplicitImports/src/deprecated.jl:79:21

Note: the WARNING is more or less harmless; the way this package is written, it will happen any time there is a clash, even if that clash is not realized in your code. I cannot figure out how to suppress it.

You can also pass show_locations=true for more details:

  Module ExplicitImports is relying on implicit imports for 7 names. These could be explicitly imported as follows:

  using AbstractTrees: AbstractTrees # used at /Users/eph/ExplicitImports/src/parse_utilities.jl:51:10
  using AbstractTrees: Leaves # used at /Users/eph/ExplicitImports/src/get_names_used.jl:453:17
  using AbstractTrees: TreeCursor # used at /Users/eph/ExplicitImports/src/parse_utilities.jl:129:18
  using AbstractTrees: children # used at /Users/eph/ExplicitImports/src/get_names_used.jl:380:26
  using AbstractTrees: nodevalue # used at /Users/eph/ExplicitImports/src/get_names_used.jl:359:16
  using JuliaSyntax: JuliaSyntax # used at /Users/eph/ExplicitImports/src/get_names_used.jl:439:53
  using JuliaSyntax: @K_str # used at /Users/eph/ExplicitImports/src/get_names_used.jl:299:33

  Additionally, module ExplicitImports has 1 self-qualified access:

    •  parent was accessed as ExplicitImports.parent inside ExplicitImports at /Users/eph/ExplicitImports/src/deprecated.jl:79:21

  Additionally, module ExplicitImports accesses 1 name from non-owner modules:

    •  parent has owner AbstractTrees but it was accessed from ExplicitImports at
       /Users/eph/ExplicitImports/src/deprecated.jl:79:21

Note the paths of course will differ depending on the location of the code on your system.

This can be handy for debugging; if you find that in fact ExplicitImports thinks a local variable is a global from another module, please file an issue and include the code snippet!

Limitations

Some tricky scoping situations are not handled correctly

These can likely all be fixed by improving the code in src/get_names_used.jl, so they aren't inherent limitations of this approach, but since we are re-implementing Julia's scoping rules on top of the parse tree, for fully accurate results we need to handle each situation correctly, which takes a lot of work.

Known issues:

  • global and local keywords are currently ignored
  • baremodule is currently not handled
  • arguments in macro definitions are not handled (may be treated incorrectly as globals)
  • arguments to let blocks are not handled (may be treated incorrectly as globals)
  • multi-argument include calls are ignored
  • In Julia, include adds the included code at top-level in the module in which it is called. Here, when include is called within a local scope, all of the code being included is treated as being within that local scope.
  • quoted code (e.g. when building Julia expressions programmatically) may be analyzed incorrectly
  • default values in function definitions can be incorrectly treated as local variables (#62)

The consequence of these issues is that ExplicitImports may misunderstand whether or not a particular name refers to a local variable or a global one, and thus whether or not some particular implicitly-available name (exported by some module) is in fact being used. This could cause it to suggest an unnecessary explicit import, fail to suggest an explicit import, or to falsely claim that an explicit import is stale.

Hopefully these situations are somewhat rare, because even if ExplicitExports misunderstands the scoping for one usage of a name, it may correctly parse the scoping of it in another usage in the same module, and could end up drawing the correct conclusion anyway.

Additionally, the testing-oriented functions check_no_implicit_imports and check_no_stale_explicit_imports have the ability to filter out problematic names or modules, to allow manual intervention in cases in which ExplicitImports gets it wrong.

Cannot recurse through dynamic include statements

These are include in which the argument is not a string literal. For example, the package MathOptInterface.jl currently includes the following code in it's Test module:

for file in readdir(@__DIR__)
    if startswith(file, "test_") && endswith(file, ".jl")
        include(file)
    end
end

This is problematic for ExplicitImports.jl; unless we really use a full-blown interpreter (which I do think could be a viable strategy1), we can't really execute this code to know what files are being included. Thus being unable to traverse dynamic includes is essentially an inherent limitation of the approach used in this package.

The consequence of missing files is that the any names used or imports made in those files are totally missed. Even if we did take a strategy like "scan the package src directory for Julia code, and analyze all those files", without understanding includes, we wouldn't understand which files belong to which modules, making this analysis useless.

However, we do at least detect this situation, so we can know which modules are affected by the missing information, and (by default) refuse to make claims about them. For example, running print_explicit_imports on this module gives:

julia> print_explicit_imports(MathOptInterface.Test, pkgdir(MathOptInterface))
  Module MathOptInterface.Test could not be accurately analyzed, likely due to dynamic include statements. You can pass strict=false to
  attempt to get (possibly inaccurate) results anyway.

  Module MathOptInterface.Test._BaseTest could not be accurately analyzed, likely due to dynamic include statements. You can pass
  strict=false to attempt to get (possibly inaccurate) results anyway.

Note here we need to pass pkgdir(MathOptInterface) as the second argument, as pathof(MathOptInterface.Test) === nothing and we would get a FileNotFoundException.

If we do pass strict=false, in this case we get

julia> print_explicit_imports(MathOptInterface.Test, pkgdir(MathOptInterface); strict=false)
  Module MathOptInterface.Test is not relying on any implicit imports.

  Module MathOptInterface.Test._BaseTest is not relying on any implicit imports.

However, we can't really be sure there isn't a reliance on implicit imports present in the files that we weren't able to scan (or perhaps some stale explicit imports made in those files, or perhaps usages of names explicitly imported in the files we could scan, which would prove those explicit imports are in fact not stale).

Need to load the package/module

This implementation relies on Base.which to introspect which module any given name comes from, and therefore we need to load the module, not just inspect its source code. We can't solely use the source code because implicit imports are implicit -- which is part of the criticism of them in the first place, that the source file alone does not tell you where the names come from.

In particular, this means it is hard to convert implicit imports to explicit as a formatting pass, for example.

Given a running language server, however, I think it should be possible to query that for the information needed.

Footnotes

  1. An alternate implementation using an AbstractInterpreter (like JET does) might solve this issue (at the cost of increased complexity), and possibly get some handling of tricky scoping situations "for free".

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Developer tooling for Julia namespace management: detecting implicit imports, improper explicit imports, and improper qualified accesses

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