automatic import of python-edc-randomization

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diff --git a/.gitignore b/.gitignore
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+/edc-randomization-0.3.45.tar.gz
diff --git a/python-edc-randomization.spec b/python-edc-randomization.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-edc-randomization
+Version:	0.3.45
+Release:	1
+Summary:	Randomization classes for clinicedc/edc
+License:	GPL license, see LICENSE
+URL:		https://github.com/clinicedc/edc-randomization
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b1/6e/c958aaac83febe90c0943511540a31d9cf18787bcc866dd9add9b9ff4b5d/edc-randomization-0.3.45.tar.gz
+BuildArch:	noarch
+
+
+%description
+Randomization objects for clinicedc projects
+Overview
+++++++++
+The ``Randomizer`` class emulates the randomization of a clincial trial participant in
+realtime. This module doesn't actually `randomize` in realtime. Instead, a CSV file is
+prepared in advance by the statistician. This CSV file lists the order in which subjects
+are to be randomized. The ``Randomizer`` class initially imports the entire list in order
+into a ``model``. When a subject is to be randomized, the ``Randomizer`` class selects
+the next available row from the model.
+A very basic ``randomization_list.csv`` prepared in advance might look like this::
+    site_name,sid,assignment
+    temeke,1000,active
+    temeke,1001,active
+    temeke,1002,placebo
+    temeke,1003,active
+    temeke,1004,placebo
+    temeke,1005,placebo
+For large multisite trials this may be thousands of lines ordered using some type of block
+randomization.
+This module will import (only once) all rows from the CSV file into a model. The ``Randomizer``
+class selects and allocates in order by site_name one row per participant from the model.
+    randomizer_cls = site_randomizers.get("default")
+    randomizer_cls.randomize(subject_identifier=subject_identifier, ...)
+    # or just:
+    site_randomizers.randomize("default", subject_identifier=subject_identifier, ...)
+Usually, the ``Randomizer`` class is instantiated in a ``signal`` once the subject's
+eligibility is confirmed and the subject's informed consent is submitted. A
+`signal` attached to the subject's informed consent is a good place to do this assuming the sequence
+of events are 1) pass eligibility criteria, 2) complete informed consent, 3) `randomize` and
+issue study identifier 4) start baseline visit.
+    @receiver(
+        post_save,
+        weak=False,
+        sender=SubjectConsent,
+        dispatch_uid="subject_consent_on_post_save",
+    )
+    def subject_consent_on_post_save(sender, instance, raw, created, **kwargs):
+        if not raw:
+            if created:
+                # randomize
+                site_randomizers.randomize(
+                    "default",
+                    subject_identifier=instance.subject_identifier,
+                    report_datetime=instance.consent_datetime,
+                    site=instance.site,
+                    user=instance.user_created,
+                )
+Registering a randomizer
+++++++++++++++++++++++++
+The default ``Randomizer`` class is ``edc_randomization.randomizer.Randomizer``. Unless you
+indicate otherwise, it will be automatically registered with the site controller,
+``site_randomizers`` with the name ``default``. It is recommended you access the ``Randomizer``
+class through ``site_randomizers`` instead of directly importing.
+    randomizer_cls = site_randomizers.get("default")
+Customizing the default randomizer
+++++++++++++++++++++++++++++++++++
+Some attributes of the default ``Randomizer`` class can be customized using ``settings`` attributes:
+    EDC_RANDOMIZATION_LIST_PATH = 'path/to/csv_file'
+    EDC_RANDOMIZATION_ASSIGNMENT_MAP = {
+        "intervention": 1,
+        "control": 2,
+        }
+    EDC_RANDOMIZATION_ASSIGNMENT_DESCRIPTION_MAP = {
+        "intervention": "Fluconazole plus flucytosine",
+        "control": "Fluconazole"
+        }
+Creating a custom randomizer
+++++++++++++++++++++++++++++
+If you need to customize further, create a custom ``Randomizer`` class.
+In the example below, ``gender`` is added for a trial stratified by ``gender``.
+Custom ``Randomizer`` classes live in ``randomizers.py`` in the root of your app. The
+``site_randomizers`` controller will ``autodiscover`` them.
+    # my_app/randomizers.py
+    @register()
+    class MyRandomizer(Randomizer):
+        name = "my_randomizer"
+        model = "edc_randomization.myrandomizationlist"
+        randomization_list_path = tmpdir
+        assignment_map = {"Intervention": 1, "Control": 0}
+        assignment_description_map = {"Intervention": "Fluconazole plus flucytosine", "Control": "Fluconazole"}
+        extra_csv_fieldnames = ["gender"]
+        def __init__(self, gender=None, **kwargs):
+            self.gender = gender
+            super().__init__(**kwargs)
+        @property
+        def extra_required_instance_attrs(self):
+            return dict(gender=self.gender)
+        @property
+        def extra_model_obj_options(self):
+            return dict(gender=self.gender)
+        @classmethod
+        def get_extra_list_display(cls):
+            return [(4, "gender")]
+The ``register()`` decorator registers the custom class with ``site_randomizers``.
+With a custom randomizer, the default ``Randomizer`` class is no longer needed,
+update settings to prevent the default class from registering.
+Use the settings attribute:
+    EDC_RANDOMIZATION_REGISTER_DEFAULT_RANDOMIZER = False
+Confirm this by checking the ``site_randomizers``:
+    >>> randomizer_cls = site_randomizers.get("default")
+    NotRegistered: A Randomizer class by this name ...
+    >>> randomizer_cls = site_randomizers.get("my_randomizer")
+    >>> randomizer_cls.name
+    "my_randomizer"
+Manually Importing from CSV
++++++++++++++++++++++++++++
+A ``Randomizer`` class will call ``import_list`` when it is instantiated
+for the first time. If you want to load the CSV file manually,
+import the ``Randomizer`` class and call ``import_list()``.
+   >>> randomizer_cls = site_randomizers.get("my_randomizer")
+   >>> randomizer_cls.import_list()
+   Import CSV data
+     Randomizer:
+       -  Name: my_randomizer
+       -  Assignments: {'active': 1, 'placebo': 2}
+       -  Model: edc_randomization.myrandomizationlist
+       -  Path: /home/me/.etc/randomization_list.csv
+       -  Imported 5 SIDs for randomizer `my_randomizer` into model `edc_randomization.myrandomizationlist`
+          from /home/me/.etc/randomization_list.csv.
+       -  Verified OK.
+Manually Export to CSV
+++++++++++++++++++++++
+    >>> from edc_randomization.utils import export_randomization_list
+    >>> export_randomization_list(randomizer_name="default",path="~/", username="erikvw")
+If the user does not have permissions to view the randomizationlist table, a ``RandomizationListExporterError`` will be raised:
+    RandomizationListExporterError: User `erikvw` does not have permission to view 'edc_randomization.randomizationlist'
+
+%package -n python3-edc-randomization
+Summary:	Randomization classes for clinicedc/edc
+Provides:	python-edc-randomization
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-edc-randomization
+Randomization objects for clinicedc projects
+Overview
+++++++++
+The ``Randomizer`` class emulates the randomization of a clincial trial participant in
+realtime. This module doesn't actually `randomize` in realtime. Instead, a CSV file is
+prepared in advance by the statistician. This CSV file lists the order in which subjects
+are to be randomized. The ``Randomizer`` class initially imports the entire list in order
+into a ``model``. When a subject is to be randomized, the ``Randomizer`` class selects
+the next available row from the model.
+A very basic ``randomization_list.csv`` prepared in advance might look like this::
+    site_name,sid,assignment
+    temeke,1000,active
+    temeke,1001,active
+    temeke,1002,placebo
+    temeke,1003,active
+    temeke,1004,placebo
+    temeke,1005,placebo
+For large multisite trials this may be thousands of lines ordered using some type of block
+randomization.
+This module will import (only once) all rows from the CSV file into a model. The ``Randomizer``
+class selects and allocates in order by site_name one row per participant from the model.
+    randomizer_cls = site_randomizers.get("default")
+    randomizer_cls.randomize(subject_identifier=subject_identifier, ...)
+    # or just:
+    site_randomizers.randomize("default", subject_identifier=subject_identifier, ...)
+Usually, the ``Randomizer`` class is instantiated in a ``signal`` once the subject's
+eligibility is confirmed and the subject's informed consent is submitted. A
+`signal` attached to the subject's informed consent is a good place to do this assuming the sequence
+of events are 1) pass eligibility criteria, 2) complete informed consent, 3) `randomize` and
+issue study identifier 4) start baseline visit.
+    @receiver(
+        post_save,
+        weak=False,
+        sender=SubjectConsent,
+        dispatch_uid="subject_consent_on_post_save",
+    )
+    def subject_consent_on_post_save(sender, instance, raw, created, **kwargs):
+        if not raw:
+            if created:
+                # randomize
+                site_randomizers.randomize(
+                    "default",
+                    subject_identifier=instance.subject_identifier,
+                    report_datetime=instance.consent_datetime,
+                    site=instance.site,
+                    user=instance.user_created,
+                )
+Registering a randomizer
+++++++++++++++++++++++++
+The default ``Randomizer`` class is ``edc_randomization.randomizer.Randomizer``. Unless you
+indicate otherwise, it will be automatically registered with the site controller,
+``site_randomizers`` with the name ``default``. It is recommended you access the ``Randomizer``
+class through ``site_randomizers`` instead of directly importing.
+    randomizer_cls = site_randomizers.get("default")
+Customizing the default randomizer
+++++++++++++++++++++++++++++++++++
+Some attributes of the default ``Randomizer`` class can be customized using ``settings`` attributes:
+    EDC_RANDOMIZATION_LIST_PATH = 'path/to/csv_file'
+    EDC_RANDOMIZATION_ASSIGNMENT_MAP = {
+        "intervention": 1,
+        "control": 2,
+        }
+    EDC_RANDOMIZATION_ASSIGNMENT_DESCRIPTION_MAP = {
+        "intervention": "Fluconazole plus flucytosine",
+        "control": "Fluconazole"
+        }
+Creating a custom randomizer
+++++++++++++++++++++++++++++
+If you need to customize further, create a custom ``Randomizer`` class.
+In the example below, ``gender`` is added for a trial stratified by ``gender``.
+Custom ``Randomizer`` classes live in ``randomizers.py`` in the root of your app. The
+``site_randomizers`` controller will ``autodiscover`` them.
+    # my_app/randomizers.py
+    @register()
+    class MyRandomizer(Randomizer):
+        name = "my_randomizer"
+        model = "edc_randomization.myrandomizationlist"
+        randomization_list_path = tmpdir
+        assignment_map = {"Intervention": 1, "Control": 0}
+        assignment_description_map = {"Intervention": "Fluconazole plus flucytosine", "Control": "Fluconazole"}
+        extra_csv_fieldnames = ["gender"]
+        def __init__(self, gender=None, **kwargs):
+            self.gender = gender
+            super().__init__(**kwargs)
+        @property
+        def extra_required_instance_attrs(self):
+            return dict(gender=self.gender)
+        @property
+        def extra_model_obj_options(self):
+            return dict(gender=self.gender)
+        @classmethod
+        def get_extra_list_display(cls):
+            return [(4, "gender")]
+The ``register()`` decorator registers the custom class with ``site_randomizers``.
+With a custom randomizer, the default ``Randomizer`` class is no longer needed,
+update settings to prevent the default class from registering.
+Use the settings attribute:
+    EDC_RANDOMIZATION_REGISTER_DEFAULT_RANDOMIZER = False
+Confirm this by checking the ``site_randomizers``:
+    >>> randomizer_cls = site_randomizers.get("default")
+    NotRegistered: A Randomizer class by this name ...
+    >>> randomizer_cls = site_randomizers.get("my_randomizer")
+    >>> randomizer_cls.name
+    "my_randomizer"
+Manually Importing from CSV
++++++++++++++++++++++++++++
+A ``Randomizer`` class will call ``import_list`` when it is instantiated
+for the first time. If you want to load the CSV file manually,
+import the ``Randomizer`` class and call ``import_list()``.
+   >>> randomizer_cls = site_randomizers.get("my_randomizer")
+   >>> randomizer_cls.import_list()
+   Import CSV data
+     Randomizer:
+       -  Name: my_randomizer
+       -  Assignments: {'active': 1, 'placebo': 2}
+       -  Model: edc_randomization.myrandomizationlist
+       -  Path: /home/me/.etc/randomization_list.csv
+       -  Imported 5 SIDs for randomizer `my_randomizer` into model `edc_randomization.myrandomizationlist`
+          from /home/me/.etc/randomization_list.csv.
+       -  Verified OK.
+Manually Export to CSV
+++++++++++++++++++++++
+    >>> from edc_randomization.utils import export_randomization_list
+    >>> export_randomization_list(randomizer_name="default",path="~/", username="erikvw")
+If the user does not have permissions to view the randomizationlist table, a ``RandomizationListExporterError`` will be raised:
+    RandomizationListExporterError: User `erikvw` does not have permission to view 'edc_randomization.randomizationlist'
+
+%package help
+Summary:	Development documents and examples for edc-randomization
+Provides:	python3-edc-randomization-doc
+%description help
+Randomization objects for clinicedc projects
+Overview
+++++++++
+The ``Randomizer`` class emulates the randomization of a clincial trial participant in
+realtime. This module doesn't actually `randomize` in realtime. Instead, a CSV file is
+prepared in advance by the statistician. This CSV file lists the order in which subjects
+are to be randomized. The ``Randomizer`` class initially imports the entire list in order
+into a ``model``. When a subject is to be randomized, the ``Randomizer`` class selects
+the next available row from the model.
+A very basic ``randomization_list.csv`` prepared in advance might look like this::
+    site_name,sid,assignment
+    temeke,1000,active
+    temeke,1001,active
+    temeke,1002,placebo
+    temeke,1003,active
+    temeke,1004,placebo
+    temeke,1005,placebo
+For large multisite trials this may be thousands of lines ordered using some type of block
+randomization.
+This module will import (only once) all rows from the CSV file into a model. The ``Randomizer``
+class selects and allocates in order by site_name one row per participant from the model.
+    randomizer_cls = site_randomizers.get("default")
+    randomizer_cls.randomize(subject_identifier=subject_identifier, ...)
+    # or just:
+    site_randomizers.randomize("default", subject_identifier=subject_identifier, ...)
+Usually, the ``Randomizer`` class is instantiated in a ``signal`` once the subject's
+eligibility is confirmed and the subject's informed consent is submitted. A
+`signal` attached to the subject's informed consent is a good place to do this assuming the sequence
+of events are 1) pass eligibility criteria, 2) complete informed consent, 3) `randomize` and
+issue study identifier 4) start baseline visit.
+    @receiver(
+        post_save,
+        weak=False,
+        sender=SubjectConsent,
+        dispatch_uid="subject_consent_on_post_save",
+    )
+    def subject_consent_on_post_save(sender, instance, raw, created, **kwargs):
+        if not raw:
+            if created:
+                # randomize
+                site_randomizers.randomize(
+                    "default",
+                    subject_identifier=instance.subject_identifier,
+                    report_datetime=instance.consent_datetime,
+                    site=instance.site,
+                    user=instance.user_created,
+                )
+Registering a randomizer
+++++++++++++++++++++++++
+The default ``Randomizer`` class is ``edc_randomization.randomizer.Randomizer``. Unless you
+indicate otherwise, it will be automatically registered with the site controller,
+``site_randomizers`` with the name ``default``. It is recommended you access the ``Randomizer``
+class through ``site_randomizers`` instead of directly importing.
+    randomizer_cls = site_randomizers.get("default")
+Customizing the default randomizer
+++++++++++++++++++++++++++++++++++
+Some attributes of the default ``Randomizer`` class can be customized using ``settings`` attributes:
+    EDC_RANDOMIZATION_LIST_PATH = 'path/to/csv_file'
+    EDC_RANDOMIZATION_ASSIGNMENT_MAP = {
+        "intervention": 1,
+        "control": 2,
+        }
+    EDC_RANDOMIZATION_ASSIGNMENT_DESCRIPTION_MAP = {
+        "intervention": "Fluconazole plus flucytosine",
+        "control": "Fluconazole"
+        }
+Creating a custom randomizer
+++++++++++++++++++++++++++++
+If you need to customize further, create a custom ``Randomizer`` class.
+In the example below, ``gender`` is added for a trial stratified by ``gender``.
+Custom ``Randomizer`` classes live in ``randomizers.py`` in the root of your app. The
+``site_randomizers`` controller will ``autodiscover`` them.
+    # my_app/randomizers.py
+    @register()
+    class MyRandomizer(Randomizer):
+        name = "my_randomizer"
+        model = "edc_randomization.myrandomizationlist"
+        randomization_list_path = tmpdir
+        assignment_map = {"Intervention": 1, "Control": 0}
+        assignment_description_map = {"Intervention": "Fluconazole plus flucytosine", "Control": "Fluconazole"}
+        extra_csv_fieldnames = ["gender"]
+        def __init__(self, gender=None, **kwargs):
+            self.gender = gender
+            super().__init__(**kwargs)
+        @property
+        def extra_required_instance_attrs(self):
+            return dict(gender=self.gender)
+        @property
+        def extra_model_obj_options(self):
+            return dict(gender=self.gender)
+        @classmethod
+        def get_extra_list_display(cls):
+            return [(4, "gender")]
+The ``register()`` decorator registers the custom class with ``site_randomizers``.
+With a custom randomizer, the default ``Randomizer`` class is no longer needed,
+update settings to prevent the default class from registering.
+Use the settings attribute:
+    EDC_RANDOMIZATION_REGISTER_DEFAULT_RANDOMIZER = False
+Confirm this by checking the ``site_randomizers``:
+    >>> randomizer_cls = site_randomizers.get("default")
+    NotRegistered: A Randomizer class by this name ...
+    >>> randomizer_cls = site_randomizers.get("my_randomizer")
+    >>> randomizer_cls.name
+    "my_randomizer"
+Manually Importing from CSV
++++++++++++++++++++++++++++
+A ``Randomizer`` class will call ``import_list`` when it is instantiated
+for the first time. If you want to load the CSV file manually,
+import the ``Randomizer`` class and call ``import_list()``.
+   >>> randomizer_cls = site_randomizers.get("my_randomizer")
+   >>> randomizer_cls.import_list()
+   Import CSV data
+     Randomizer:
+       -  Name: my_randomizer
+       -  Assignments: {'active': 1, 'placebo': 2}
+       -  Model: edc_randomization.myrandomizationlist
+       -  Path: /home/me/.etc/randomization_list.csv
+       -  Imported 5 SIDs for randomizer `my_randomizer` into model `edc_randomization.myrandomizationlist`
+          from /home/me/.etc/randomization_list.csv.
+       -  Verified OK.
+Manually Export to CSV
+++++++++++++++++++++++
+    >>> from edc_randomization.utils import export_randomization_list
+    >>> export_randomization_list(randomizer_name="default",path="~/", username="erikvw")
+If the user does not have permissions to view the randomizationlist table, a ``RandomizationListExporterError`` will be raised:
+    RandomizationListExporterError: User `erikvw` does not have permission to view 'edc_randomization.randomizationlist'
+
+%prep
+%autosetup -n edc-randomization-0.3.45
+
+%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-edc-randomization -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.45-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..74a2fdc
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+2449b132140685c3a42a9725c30af65a  edc-randomization-0.3.45.tar.gz