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%global _empty_manifest_terminate_build 0
Name: python-instruct
Version: 0.7.2
Release: 1
Summary: please add a summary manually as the author left a blank one
License: BSD
URL: https://github.com/autumnjolitz/instruct
Source0: https://mirrors.aliyun.com/pypi/web/packages/05/d8/8799e697052ca9ea2657ce14cc7127f2790d953a4dd2bb0422e851e26854/instruct-0.7.2.tar.gz
BuildArch: noarch
Requires: python3-Jinja2
Requires: python3-inflection
Requires: python3-typing-extensions
Requires: python3-twine
Requires: python3-pytest
Requires: python3-pytest-mock
Requires: python3-pytest
Requires: python3-pytest-mock
%description
A compact, fast object system that can serve as the basis for a DAO model.
To that end, instruct uses ``__slots__`` to prevent new attribute addition, properties to control types, event listeners and historical changes, and a Jinja2-driven codegen to keep a pure-Python implementation as fast and as light as possible.
I want to basically have a form of strictly typed objects that behave like C structs but can handle automatically coercing incoming values correctly, have primitive events and have fast ``__iter__``, ``__eq__`` while also allowing for one to override it in the final class (and even call super!)
This girl asks for a lot but I like taking metaclassing as far as it can go without diving into using macropy. 😉
Current Capabilities:
- Support multiple inheritance, chained fields and ``__slots__`` [Done]
- Support type coercions (via ``_coerce__``) [Done]
- Strictly-typed ability to define fixed data objects [Done]
- Ability to drop all of the above type checks [Done]
- Track changes made to the object as well as reset [Done]
- Fast ``__iter__`` [Done]
- Native support of pickle [Done]/json [Done]
- Support List[type] declarations and initializations [Done]
- optionally data class annotation-like behavior [Done]
- ``_asdict``, ``_astuple``, ``_aslist`` functions like in a NamedTuple [Done]
- ``get``, ``keys``, ``values``, ``item`` functions available in the module and in a mixin named ``mapping=True``
+ This effectively allows access like other packages e.g. ``attrs.keys(item_instance)``
- ``bytes``/``bytearray`` are urlsafe base64 encoded by default, can override per field via a class level ``BINARY_JSON_ENCODERS = {key: encoding_function}`` [Done]
- Allow ``__coerce__`` to have a tuple of field names to avoid repetition on ``__coerce__`` definitions [Done]
- Allow use of ``Literal`` in the type (exact match of a value to a vector of values) [Done]
- Allow subtraction of properties like ``(F - {"a", "b"}).keys() == F_without_a_b.keys()`` [Done]
+ This will allow one to slim down a class to a restricted subtype, like for use in a DAO system to load/hold less data.
- Allow subtraction of properties like ``(F - {"a": {"b"}).keys() == F_a_without_b.keys()`` [Done]
+ This allows for one to remove fields that are unused prior to class initialization.
- Allow subtraction of properties via an inclusive list like ``(F & {"a", "b"}).keys() == F_with_only_a_and_b.keys()`` [Done]
- Allow subtraction to propagate to embedded Instruct classes like ``(F - {"a.b", "a.c"}).a.keys() == (F_a.keys() - {"b", "c"))`` [Done]
+ This would really allow for complex trees of properties to be rendered down to thin SQL column selects, thus reducing data load.
- Replace references to an embedded class in a ``__coerce__`` function with the subtracted form in case of embedded property subtractions [Done]
- Allow use of Annotated i.e. ``field: Annotated[int, NoJSON, NoPickle]`` and have ``to_json`` and ``pickle.dumps(...)`` skip "field" [Done]
+ Would grant a more powerful interface to controlling code-gen'ed areas via ``cls._annotated_metadata`` (maps field -> what's inside the ``Annotation``)
Next Goals:
- Allow Generics i.e. ``class F(instruct.Base, T): ...`` -> ``F[str](...)``
+ Would be able to allow specialized subtypes
- ``CStruct``-Base class that operates on an ``_cvalue`` cffi struct.
- Cython compatibility
%package -n python3-instruct
Summary: please add a summary manually as the author left a blank one
Provides: python-instruct
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-instruct
A compact, fast object system that can serve as the basis for a DAO model.
To that end, instruct uses ``__slots__`` to prevent new attribute addition, properties to control types, event listeners and historical changes, and a Jinja2-driven codegen to keep a pure-Python implementation as fast and as light as possible.
I want to basically have a form of strictly typed objects that behave like C structs but can handle automatically coercing incoming values correctly, have primitive events and have fast ``__iter__``, ``__eq__`` while also allowing for one to override it in the final class (and even call super!)
This girl asks for a lot but I like taking metaclassing as far as it can go without diving into using macropy. 😉
Current Capabilities:
- Support multiple inheritance, chained fields and ``__slots__`` [Done]
- Support type coercions (via ``_coerce__``) [Done]
- Strictly-typed ability to define fixed data objects [Done]
- Ability to drop all of the above type checks [Done]
- Track changes made to the object as well as reset [Done]
- Fast ``__iter__`` [Done]
- Native support of pickle [Done]/json [Done]
- Support List[type] declarations and initializations [Done]
- optionally data class annotation-like behavior [Done]
- ``_asdict``, ``_astuple``, ``_aslist`` functions like in a NamedTuple [Done]
- ``get``, ``keys``, ``values``, ``item`` functions available in the module and in a mixin named ``mapping=True``
+ This effectively allows access like other packages e.g. ``attrs.keys(item_instance)``
- ``bytes``/``bytearray`` are urlsafe base64 encoded by default, can override per field via a class level ``BINARY_JSON_ENCODERS = {key: encoding_function}`` [Done]
- Allow ``__coerce__`` to have a tuple of field names to avoid repetition on ``__coerce__`` definitions [Done]
- Allow use of ``Literal`` in the type (exact match of a value to a vector of values) [Done]
- Allow subtraction of properties like ``(F - {"a", "b"}).keys() == F_without_a_b.keys()`` [Done]
+ This will allow one to slim down a class to a restricted subtype, like for use in a DAO system to load/hold less data.
- Allow subtraction of properties like ``(F - {"a": {"b"}).keys() == F_a_without_b.keys()`` [Done]
+ This allows for one to remove fields that are unused prior to class initialization.
- Allow subtraction of properties via an inclusive list like ``(F & {"a", "b"}).keys() == F_with_only_a_and_b.keys()`` [Done]
- Allow subtraction to propagate to embedded Instruct classes like ``(F - {"a.b", "a.c"}).a.keys() == (F_a.keys() - {"b", "c"))`` [Done]
+ This would really allow for complex trees of properties to be rendered down to thin SQL column selects, thus reducing data load.
- Replace references to an embedded class in a ``__coerce__`` function with the subtracted form in case of embedded property subtractions [Done]
- Allow use of Annotated i.e. ``field: Annotated[int, NoJSON, NoPickle]`` and have ``to_json`` and ``pickle.dumps(...)`` skip "field" [Done]
+ Would grant a more powerful interface to controlling code-gen'ed areas via ``cls._annotated_metadata`` (maps field -> what's inside the ``Annotation``)
Next Goals:
- Allow Generics i.e. ``class F(instruct.Base, T): ...`` -> ``F[str](...)``
+ Would be able to allow specialized subtypes
- ``CStruct``-Base class that operates on an ``_cvalue`` cffi struct.
- Cython compatibility
%package help
Summary: Development documents and examples for instruct
Provides: python3-instruct-doc
%description help
A compact, fast object system that can serve as the basis for a DAO model.
To that end, instruct uses ``__slots__`` to prevent new attribute addition, properties to control types, event listeners and historical changes, and a Jinja2-driven codegen to keep a pure-Python implementation as fast and as light as possible.
I want to basically have a form of strictly typed objects that behave like C structs but can handle automatically coercing incoming values correctly, have primitive events and have fast ``__iter__``, ``__eq__`` while also allowing for one to override it in the final class (and even call super!)
This girl asks for a lot but I like taking metaclassing as far as it can go without diving into using macropy. 😉
Current Capabilities:
- Support multiple inheritance, chained fields and ``__slots__`` [Done]
- Support type coercions (via ``_coerce__``) [Done]
- Strictly-typed ability to define fixed data objects [Done]
- Ability to drop all of the above type checks [Done]
- Track changes made to the object as well as reset [Done]
- Fast ``__iter__`` [Done]
- Native support of pickle [Done]/json [Done]
- Support List[type] declarations and initializations [Done]
- optionally data class annotation-like behavior [Done]
- ``_asdict``, ``_astuple``, ``_aslist`` functions like in a NamedTuple [Done]
- ``get``, ``keys``, ``values``, ``item`` functions available in the module and in a mixin named ``mapping=True``
+ This effectively allows access like other packages e.g. ``attrs.keys(item_instance)``
- ``bytes``/``bytearray`` are urlsafe base64 encoded by default, can override per field via a class level ``BINARY_JSON_ENCODERS = {key: encoding_function}`` [Done]
- Allow ``__coerce__`` to have a tuple of field names to avoid repetition on ``__coerce__`` definitions [Done]
- Allow use of ``Literal`` in the type (exact match of a value to a vector of values) [Done]
- Allow subtraction of properties like ``(F - {"a", "b"}).keys() == F_without_a_b.keys()`` [Done]
+ This will allow one to slim down a class to a restricted subtype, like for use in a DAO system to load/hold less data.
- Allow subtraction of properties like ``(F - {"a": {"b"}).keys() == F_a_without_b.keys()`` [Done]
+ This allows for one to remove fields that are unused prior to class initialization.
- Allow subtraction of properties via an inclusive list like ``(F & {"a", "b"}).keys() == F_with_only_a_and_b.keys()`` [Done]
- Allow subtraction to propagate to embedded Instruct classes like ``(F - {"a.b", "a.c"}).a.keys() == (F_a.keys() - {"b", "c"))`` [Done]
+ This would really allow for complex trees of properties to be rendered down to thin SQL column selects, thus reducing data load.
- Replace references to an embedded class in a ``__coerce__`` function with the subtracted form in case of embedded property subtractions [Done]
- Allow use of Annotated i.e. ``field: Annotated[int, NoJSON, NoPickle]`` and have ``to_json`` and ``pickle.dumps(...)`` skip "field" [Done]
+ Would grant a more powerful interface to controlling code-gen'ed areas via ``cls._annotated_metadata`` (maps field -> what's inside the ``Annotation``)
Next Goals:
- Allow Generics i.e. ``class F(instruct.Base, T): ...`` -> ``F[str](...)``
+ Would be able to allow specialized subtypes
- ``CStruct``-Base class that operates on an ``_cvalue`` cffi struct.
- Cython compatibility
%prep
%autosetup -n instruct-0.7.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-instruct -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.2-1
- Package Spec generated
|
