- Implements various statistics on Vector
# Important Notes
Some minor codebase improvements:
- Some tweaks to Any/Nothing to improve performance
- Fixed bug in ObjectComparator
- Added if_nothing
- Removed Group_By_Key
This PR replaces hard-coded `@Builtin_Method` and `@Builtin_Type` nodes in Builtins with an automated solution
that a) collects metadata from such annotations b) generates `BuiltinTypes` c) registers builtin methods with corresponding
constructors.
The main differences are:
1) The owner of the builtin method does not necessarily have to be a builtin type
2) You can now mix regular methods and builtin ones in stdlib
3) No need to keep track of builtin methods and types in various places and register them by hand (a source of many typos or omissions as it found during the process of this PR)
Related to #181497846
Benchmarks also execute within the margin of error.
### Important Notes
The PR got a bit large over time as I was moving various builtin types and finding various corner cases.
Most of the changes however are rather simple c&p from Builtins.enso to the corresponding stdlib module.
Here is the list of the most crucial updates:
- `engine/runtime/src/main/java/org/enso/interpreter/runtime/builtin/Builtins.java` - the core of the changes. We no longer register individual builtin constructors and their methods by hand. Instead, the information about those is read from 2 metadata files generated by annotation processors. When the builtin method is encountered in stdlib, we do not ignore the method. Instead we lookup it up in the list of registered functions (see `getBuiltinFunction` and `IrToTruffle`)
- `engine/runtime/src/main/java/org/enso/interpreter/runtime/callable/atom/AtomConstructor.java` has now information whether it corresponds to the builtin type or not.
- `engine/runtime/src/main/scala/org/enso/compiler/codegen/RuntimeStubsGenerator.scala` - when runtime stubs generator encounters a builtin type, based on the @Builtin_Type annotation, it looks up an existing constructor for it and registers it in the provided scope, rather than creating a new one. The scope of the constructor is also changed to the one coming from stdlib, while ensuring that synthetic methods (for fields) also get assigned correctly
- `engine/runtime/src/main/scala/org/enso/compiler/codegen/IrToTruffle.scala` - when a builtin method is encountered in stdlib we don't generate a new function node for it, instead we look it up in the list of registered builtin methods. Note that Integer and Number present a bit of a challenge because they list a whole bunch of methods that don't have a corresponding method (instead delegating to small/big integer implementations).
During the translation new atom constructors get initialized but we don't want to do it for builtins which have gone through the process earlier, hence the exception
- `lib/scala/interpreter-dsl/src/main/java/org/enso/interpreter/dsl/MethodProcessor.java` - @Builtin_Method processor not only generates the actual code fpr nodes but also collects and writes the info about them (name, class, params) to a metadata file that is read during builtins initialization
- `lib/scala/interpreter-dsl/src/main/java/org/enso/interpreter/dsl/MethodProcessor.java` - @Builtin_Method processor no longer generates only (root) nodes but also collects and writes the info about them (name, class, params) to a metadata file that is read during builtins initialization
- `lib/scala/interpreter-dsl/src/main/java/org/enso/interpreter/dsl/TypeProcessor.java` - Similar to MethodProcessor but handles @Builtin_Type annotations. It doesn't, **yet**, generate any builtin objects. It also collects the names, as present in stdlib, if any, so that we can generate the names automatically (see generated `types/ConstantsGen.java`)
- `engine/runtime/src/main/java/org/enso/interpreter/node/expression/builtin` - various classes annotated with @BuiltinType to ensure that the atom constructor is always properly registered for the builitn. Note that in order to support types fields in those, annotation takes optional `params` parameter (comma separated).
- `engine/runtime/src/bench/scala/org/enso/interpreter/bench/fixtures/semantic/AtomFixtures.scala` - drop manual creation of test list which seemed to be a relict of the old design
- Added Encoding type
- Added `Text.bytes`, `Text.from_bytes` with Encoding support
- Renamed `File.read` to `File.read_text`
- Renamed `File.write` to `File.write_text`
- Added Encoding support to `File.read_text` and `File.write_text`
- Added warnings to invalid encodings
- Added Minimum, Maximum, Longest. Shortest, Mode, Percentile
- Added first and last to Map
- Restructured Faker type more inline with FakerJS
- Created 2,500 row data set
- Tests for group_by
- Performance tests for group_by
Following the Slice and Array.Copy experiment, took just the Array.Copy parts out and built into the Vector class.
This gives big performance wins in common operations:
| Test | Ref | New |
| --- | --- | --- |
| New Vector | 41.5 | 41.4 |
| Append Single | 26.6 | 4.2 |
| Append Large | 26.6 | 4.2 |
| Sum | 230.1 | 99.1 |
| Drop First 20 and Sum | 343.5 | 96.9 |
| Drop Last 20 and Sum | 311.7 | 96.9 |
| Filter | 240.2 | 92.5 |
| Filter With Index | 364.9 | 237.2 |
| Partition | 772.6 | 280.4 |
| Partition With Index | 912.3 | 427.9 |
| Each | 110.2 | 113.3 |
*Benchmarks run on an AWS EC2 r5a.xlarge with 1,000,000 item count, 100 iteration size run 10 times.*
# Important Notes
Have generally tried to push the `@Tail_Call` down from the Vector class and move to calling functions on the range class.
- Expanded benchmarks on Vector
- Added `take` method to Vector
- Added `each_with_index` method to Vector
- Added `filter_with_index` method to Vector
* Add matching mode definitions
* Add stub for new method API and an initial test suite
* Fix tests, implement exact matching
* Implement Regex matching
* changelog
* Add benchmarks
* Wokraround for case insensitive regex locale support
* minor tweaks
* Unify Case_Insensitive
* Update edge cases
* Fix other affected places
* minor style change
* Add a problematic test
* Add a regex test for a similar situation
* Migrate to StringSearch:wq
* Add test cases for scharfes S edge case
* Add problematic Regex Unicode normalization test
* Document the regex accents peculiarity
* Do not apply the normalization in ASCII only mode
* cr
* Integer parse via Longs
* Integer parse via Longs
* Benchmark for Number Parse
* CHANGELOG.md and Natural Order
* Expanded test set
* Number base tests
* Few more negative tests
