rust/tests/ui/methods/method-call-err-msg.stderr

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error[E0061]: this method takes 0 arguments but 1 argument was supplied
--> $DIR/method-call-err-msg.rs:13:7
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|
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LL | x.zero(0)
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| ^^^^ -
| |
| unexpected argument of type `{integer}`
| help: remove the extra argument
|
note: method defined here
--> $DIR/method-call-err-msg.rs:5:8
|
LL | fn zero(self) -> Foo { self }
| ^^^^
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error[E0061]: this method takes 1 argument but 0 arguments were supplied
--> $DIR/method-call-err-msg.rs:14:7
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|
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LL | .one()
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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| ^^^-- an argument of type `isize` is missing
|
note: method defined here
--> $DIR/method-call-err-msg.rs:6:8
|
LL | fn one(self, _: isize) -> Foo { self }
| ^^^ --------
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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help: provide the argument
|
LL | .one(/* isize */)
| ~~~~~~~~~~~~~
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error[E0061]: this method takes 2 arguments but 1 argument was supplied
--> $DIR/method-call-err-msg.rs:15:7
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|
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LL | .two(0);
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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| ^^^--- an argument of type `isize` is missing
|
note: method defined here
--> $DIR/method-call-err-msg.rs:7:8
|
LL | fn two(self, _: isize, _: isize) -> Foo { self }
| ^^^ -------- --------
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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help: provide the argument
|
LL | .two(0, /* isize */);
| ~~~~~~~~~~~~~~~~
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error[E0599]: `Foo` is not an iterator
--> $DIR/method-call-err-msg.rs:19:7
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|
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LL | pub struct Foo;
| -------------- method `take` not found for this struct because it doesn't satisfy `Foo: Iterator`
...
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LL | / y.zero()
LL | | .take()
| | -^^^^ `Foo` is not an iterator
| |______|
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|
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|
= note: the following trait bounds were not satisfied:
`Foo: Iterator`
which is required by `&mut Foo: Iterator`
note: the trait `Iterator` must be implemented
--> $SRC_DIR/core/src/iter/traits/iterator.rs:LL:COL
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= help: items from traits can only be used if the trait is implemented and in scope
Account for non-overlapping unmet trait bounds in suggestion When a method not found on a type parameter could have been provided by any of multiple traits, suggest each trait individually, instead of a single suggestion to restrict the type parameter with *all* of them. Before: ``` error[E0599]: the method `cmp` exists for reference `&T`, but its trait bounds were not satisfied --> $DIR/method-on-unbounded-type-param.rs:5:10 | LL | (&a).cmp(&b) | ^^^ method cannot be called on `&T` due to unsatisfied trait bounds | = note: the following trait bounds were not satisfied: `T: Ord` which is required by `&T: Ord` `&T: Iterator` which is required by `&mut &T: Iterator` `T: Iterator` which is required by `&mut T: Iterator` help: consider restricting the type parameters to satisfy the trait bounds | LL | fn g<T>(a: T, b: T) -> std::cmp::Ordering where T: Iterator, T: Ord { | +++++++++++++++++++++++++ ``` After: ``` error[E0599]: the method `cmp` exists for reference `&T`, but its trait bounds were not satisfied --> $DIR/method-on-unbounded-type-param.rs:5:10 | LL | (&a).cmp(&b) | ^^^ method cannot be called on `&T` due to unsatisfied trait bounds | = note: the following trait bounds were not satisfied: `T: Ord` which is required by `&T: Ord` `&T: Iterator` which is required by `&mut &T: Iterator` `T: Iterator` which is required by `&mut T: Iterator` = help: items from traits can only be used if the type parameter is bounded by the trait help: the following traits define an item `cmp`, perhaps you need to restrict type parameter `T` with one of them: | LL | fn g<T: Ord>(a: T, b: T) -> std::cmp::Ordering { | +++++ LL | fn g<T: Iterator>(a: T, b: T) -> std::cmp::Ordering { | ++++++++++ ``` Fix #108428.
2024-01-30 18:10:12 +00:00
= note: the following traits define an item `take`, perhaps you need to implement one of them:
candidate #1: `Iterator`
candidate #2: `std::io::Read`
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error[E0061]: this method takes 3 arguments but 0 arguments were supplied
--> $DIR/method-call-err-msg.rs:21:7
|
LL | y.three::<usize>();
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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| ^^^^^^^^^^^^^^-- three arguments of type `usize`, `usize`, and `usize` are missing
|
note: method defined here
--> $DIR/method-call-err-msg.rs:8:8
|
LL | fn three<T>(self, _: T, _: T, _: T) -> Foo { self }
| ^^^^^ ---- ---- ----
Implementation for 65853 This attempts to bring better error messages to invalid method calls, by applying some heuristics to identify common mistakes. The algorithm is inspired by Levenshtein distance and longest common sub-sequence. In essence, we treat the types of the function, and the types of the arguments you provided as two "words" and compute the edits to get from one to the other. We then modify that algorithm to detect 4 cases: - A function input is missing - An extra argument was provided - The type of an argument is straight up invalid - Two arguments have been swapped - A subset of the arguments have been shuffled (We detect the last two as separate cases so that we can detect two swaps, instead of 4 parameters permuted.) It helps to understand this argument by paying special attention to terminology: "inputs" refers to the inputs being *expected* by the function, and "arguments" refers to what has been provided at the call site. The basic sketch of the algorithm is as follows: - Construct a boolean grid, with a row for each argument, and a column for each input. The cell [i, j] is true if the i'th argument could satisfy the j'th input. - If we find an argument that could satisfy no inputs, provided for an input that can't be satisfied by any other argument, we consider this an "invalid type". - Extra arguments are those that can't satisfy any input, provided for an input that *could* be satisfied by another argument. - Missing inputs are inputs that can't be satisfied by any argument, where the provided argument could satisfy another input - Swapped / Permuted arguments are identified with a cycle detection algorithm. As each issue is found, we remove the relevant inputs / arguments and check for more issues. If we find no issues, we match up any "valid" arguments, and start again. Note that there's a lot of extra complexity: - We try to stay efficient on the happy path, only computing the diagonal until we find a problem, and then filling in the rest of the matrix. - Closure arguments are wrapped in a tuple and need to be unwrapped - We need to resolve closure types after the rest, to allow the most specific type constraints - We need to handle imported C functions that might be variadic in their inputs. I tried to document a lot of this in comments in the code and keep the naming clear.
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help: provide the arguments
|
LL | y.three::<usize>(/* usize */, /* usize */, /* usize */);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
error: aborting due to 5 previous errors
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Some errors have detailed explanations: E0061, E0599.
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For more information about an error, try `rustc --explain E0061`.