automatic import of python-django-kck

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+/django-kck-0.0.56.tar.gz
diff --git a/python-django-kck.spec b/python-django-kck.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-django-kck
+Version:	0.0.56
+Release:	1
+Summary:	Data orchestration for Django
+License:	BSD
+URL:		https://gitlab.com/frameworklabs/django-kck
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/25/c4/9b22b22d197fe6fd4fa2936fdc9820559c2a578a2d4ace90187930ac59f7/django-kck-0.0.56.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-Django
+Requires:	python3-dateutil
+Requires:	python3-django-postgres-extensions
+Requires:	python3-psycopg2-binary
+Requires:	python3-django-picklefield
+
+%description
+# Django KCK
+Django KCK is data orchestration for Django.  It can be used for:
+* scheduled data imports from remote sources
+* ensuring each data product kept fresh, either by updating at a regular
+  interval or when there is a change in source data on upon which it
+  depends
+* preparing complex data products in advance of a likely request
+* simplifying and optimizing complex data flows
+
+The development pattern Django KCK encourages for data products
+emphasizes compartmentalization and simplification over complexity,
+cached data with configurable refresh routines over real-time
+computation, and common-sense optimizations over sprawling distributed
+parallelism.
+
+## History
+Django KCK is a simplified version of KCK that targets the Django
+environment exclusively.  It also uses PostgreSQL as the cache backend,
+instead of Cassandra.
+
+## Quick Install
+
+## Basic Usage
+
+```
+# myapp/primers.py
+
+from kck import Primer
+
+
+class TitleListPrimer(Primer):
+    key = 'title_list'
+    parameters = [
+        {"name": "id", "from_str": int}
+    ]
+
+    def compute(self, key):
+        param_dict = self.key_to_param_dict(key)
+        results = [{ 'title': lkp_title(id) } for id in param_dict['id_list']]
+        return results
+```
+
+```
+# myapp/views.py
+
+from kck import Cache
+from django.http import JsonResponse
+
+def first_data_product_view(request, author_id):
+    cache = Cache.get_instance()
+    title_list = cache.get(f'title_list/{author_id}')
+    return JsonResponse(title_list)
+
+```
+
+## Theory
+Essentially, Django KCK is a lazy-loading cache.  Instead of warming the
+cache in advance, Django KCK lets a developer tell the cache how to
+prime itself in the event of a cache miss.
+
+If we don't warm the cache in advance and we ask the cache for a data
+product that depends on a hundred other data products in the cache, each
+of which either gathers or computes data from other sources, then this
+design will only generate or request the data that is absolutely
+necessary for the computation.  In this way, Django KCK is able to do
+the last amount of work possible to accomplish the task.
+
+To further expedite the process or building derivative data products,
+Django KCK includes mechanisms that allow for periodic or triggered
+updates of data upon which a data product depends, such that it will be
+immediately available when a request is made.
+
+It also makes it possible to "augment" derivative data products with
+new information so that, for workloads that can take advantage of the
+optimization, a data product can be updated in place, without
+regenerating the product in its entirety.  Where it works, this approach
+can turn minutes of computation into milliseconds.
+
+
+
+
+%package -n python3-django-kck
+Summary:	Data orchestration for Django
+Provides:	python-django-kck
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-django-kck
+# Django KCK
+Django KCK is data orchestration for Django.  It can be used for:
+* scheduled data imports from remote sources
+* ensuring each data product kept fresh, either by updating at a regular
+  interval or when there is a change in source data on upon which it
+  depends
+* preparing complex data products in advance of a likely request
+* simplifying and optimizing complex data flows
+
+The development pattern Django KCK encourages for data products
+emphasizes compartmentalization and simplification over complexity,
+cached data with configurable refresh routines over real-time
+computation, and common-sense optimizations over sprawling distributed
+parallelism.
+
+## History
+Django KCK is a simplified version of KCK that targets the Django
+environment exclusively.  It also uses PostgreSQL as the cache backend,
+instead of Cassandra.
+
+## Quick Install
+
+## Basic Usage
+
+```
+# myapp/primers.py
+
+from kck import Primer
+
+
+class TitleListPrimer(Primer):
+    key = 'title_list'
+    parameters = [
+        {"name": "id", "from_str": int}
+    ]
+
+    def compute(self, key):
+        param_dict = self.key_to_param_dict(key)
+        results = [{ 'title': lkp_title(id) } for id in param_dict['id_list']]
+        return results
+```
+
+```
+# myapp/views.py
+
+from kck import Cache
+from django.http import JsonResponse
+
+def first_data_product_view(request, author_id):
+    cache = Cache.get_instance()
+    title_list = cache.get(f'title_list/{author_id}')
+    return JsonResponse(title_list)
+
+```
+
+## Theory
+Essentially, Django KCK is a lazy-loading cache.  Instead of warming the
+cache in advance, Django KCK lets a developer tell the cache how to
+prime itself in the event of a cache miss.
+
+If we don't warm the cache in advance and we ask the cache for a data
+product that depends on a hundred other data products in the cache, each
+of which either gathers or computes data from other sources, then this
+design will only generate or request the data that is absolutely
+necessary for the computation.  In this way, Django KCK is able to do
+the last amount of work possible to accomplish the task.
+
+To further expedite the process or building derivative data products,
+Django KCK includes mechanisms that allow for periodic or triggered
+updates of data upon which a data product depends, such that it will be
+immediately available when a request is made.
+
+It also makes it possible to "augment" derivative data products with
+new information so that, for workloads that can take advantage of the
+optimization, a data product can be updated in place, without
+regenerating the product in its entirety.  Where it works, this approach
+can turn minutes of computation into milliseconds.
+
+
+
+
+%package help
+Summary:	Development documents and examples for django-kck
+Provides:	python3-django-kck-doc
+%description help
+# Django KCK
+Django KCK is data orchestration for Django.  It can be used for:
+* scheduled data imports from remote sources
+* ensuring each data product kept fresh, either by updating at a regular
+  interval or when there is a change in source data on upon which it
+  depends
+* preparing complex data products in advance of a likely request
+* simplifying and optimizing complex data flows
+
+The development pattern Django KCK encourages for data products
+emphasizes compartmentalization and simplification over complexity,
+cached data with configurable refresh routines over real-time
+computation, and common-sense optimizations over sprawling distributed
+parallelism.
+
+## History
+Django KCK is a simplified version of KCK that targets the Django
+environment exclusively.  It also uses PostgreSQL as the cache backend,
+instead of Cassandra.
+
+## Quick Install
+
+## Basic Usage
+
+```
+# myapp/primers.py
+
+from kck import Primer
+
+
+class TitleListPrimer(Primer):
+    key = 'title_list'
+    parameters = [
+        {"name": "id", "from_str": int}
+    ]
+
+    def compute(self, key):
+        param_dict = self.key_to_param_dict(key)
+        results = [{ 'title': lkp_title(id) } for id in param_dict['id_list']]
+        return results
+```
+
+```
+# myapp/views.py
+
+from kck import Cache
+from django.http import JsonResponse
+
+def first_data_product_view(request, author_id):
+    cache = Cache.get_instance()
+    title_list = cache.get(f'title_list/{author_id}')
+    return JsonResponse(title_list)
+
+```
+
+## Theory
+Essentially, Django KCK is a lazy-loading cache.  Instead of warming the
+cache in advance, Django KCK lets a developer tell the cache how to
+prime itself in the event of a cache miss.
+
+If we don't warm the cache in advance and we ask the cache for a data
+product that depends on a hundred other data products in the cache, each
+of which either gathers or computes data from other sources, then this
+design will only generate or request the data that is absolutely
+necessary for the computation.  In this way, Django KCK is able to do
+the last amount of work possible to accomplish the task.
+
+To further expedite the process or building derivative data products,
+Django KCK includes mechanisms that allow for periodic or triggered
+updates of data upon which a data product depends, such that it will be
+immediately available when a request is made.
+
+It also makes it possible to "augment" derivative data products with
+new information so that, for workloads that can take advantage of the
+optimization, a data product can be updated in place, without
+regenerating the product in its entirety.  Where it works, this approach
+can turn minutes of computation into milliseconds.
+
+
+
+
+%prep
+%autosetup -n django-kck-0.0.56
+
+%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-django-kck -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.56-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..530f4c7
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+29aa1a3bbb313a3ff69f9d2c9d033eae  django-kck-0.0.56.tar.gz