transformGateScan

Prompt:
Implement the Python class `GateTransform` described below.

Class description:
Implement the GateTransform class.

Method signatures and docstrings:
- def __init__(self, Vmatrix, sourcenames, targetnames): Class to describe a linear transformation between source and target gates.
- def transformGateScan(self, vals2D, nn=None): Get a list of parameter names and [c1 c2 c3 c4] 'corner' values to generate dictionary self.vals2D[name] = matrix of values. Args: vals2D (dict): keys are the gate names, values are matrices with the gate values. nn : TODO. Returns: dict: tranformed gate values.

Implement the Python class `GateTransform` described below.

Class description:
Implement the GateTransform class.

Method signatures and docstrings:
- def __init__(self, Vmatrix, sourcenames, targetnames): Class to describe a linear transformation between source and target gates.
- def transformGateScan(self, vals2D, nn=None): Get a list of parameter names and [c1 c2 c3 c4] 'corner' values to generate dictionary self.vals2D[name] = matrix of values. Args: vals2D (dict): keys are the gate names, values are matrices with the gate values. nn : TODO. Returns: dict: tranformed gate values.

<|skeleton|>
class GateTransform:

    def __init__(self, Vmatrix, sourcenames, targetnames):
        """Class to describe a linear transformation between source and target gates."""
        <|body_0|>

    def transformGateScan(self, vals2D, nn=None):
        """Get a list of parameter names and [c1 c2 c3 c4] 'corner' values to generate dictionary self.vals2D[name] = matrix of values. Args: vals2D (dict): keys are the gate names, values are matrices with the gate values. nn : TODO. Returns: dict: tranformed gate values."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.Vmatrix = np.array(Vmatrix).astype(float)
        self.sourcenames = sourcenames
        self.targetnames = targetnames
<|end_body_0|>

<|body_start_1|>
        vals2Dout = {}
        zz = np.zeros(nn if nn is not None else (), dtype=float)
        if isinstance(vals2D, dict):
            xx = [vals2D.get(s, zz) for s in self.sourcenames]
            xx = [x.flatten() for x in xx]
            gate_values = np.vstack(xx).astype(float)
        else:
            gate_values = np.array(vals2D).astype(float)
        gate_values_out = pgeometry.projectiveTransformation(self.Vmatrix, gate_values)
        for j, n in enumerate(self.targetnames):
            vals2Dout[n] = gate_values_out[j].reshape(nn).astype(float)
        return vals2Dout
<|end_body_1|>

Solution:
class GateTransform:
    def __init__(self, Vmatrix, sourcenames, targetnames):
        """Class to describe a linear transformation between source and target gates."""
        self.Vmatrix = np.array(Vmatrix).astype(float)
        self.sourcenames = sourcenames
        self.targetnames = targetnames

    def transformGateScan(self, vals2D, nn=None):
        """Get a list of parameter names and [c1 c2 c3 c4] 'corner' values to generate dictionary self.vals2D[name] = matrix of values. Args: vals2D (dict): keys are the gate names, values are matrices with the gate values. nn : TODO. Returns: dict: tranformed gate values."""
        vals2Dout = {}
        zz = np.zeros(nn if nn is not None else (), dtype=float)
        if isinstance(vals2D, dict):
            xx = [vals2D.get(s, zz) for s in self.sourcenames]
            xx = [x.flatten() for x in xx]
            gate_values = np.vstack(xx).astype(float)
        else:
            gate_values = np.array(vals2D).astype(float)
        gate_values_out = pgeometry.projectiveTransformation(self.Vmatrix, gate_values)
        for j, n in enumerate(self.targetnames):
            vals2Dout[n] = gate_values_out[j].reshape(nn).astype(float)
        return vals2Dout


Prompt:
Implement the Python class `ParserModule` described below.

Class description:
nmap xml output parser

Method signatures and docstrings:
- def parse_path(cls, path): parse data from path
- def _parse_data(cls, data, pidb): parse raw string data

Implement the Python class `ParserModule` described below.

Class description:
nmap xml output parser

Method signatures and docstrings:
- def parse_path(cls, path): parse data from path
- def _parse_data(cls, data, pidb): parse raw string data

<|skeleton|>
class ParserModule:
    """nmap xml output parser"""

    def parse_path(cls, path):
        """parse data from path"""
        <|body_0|>

    def _parse_data(cls, data, pidb):
        """parse raw string data"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        pidb = ParsedItemsDb()
        if is_zip(path):
            with ZipFile(path) as fzip:
                for fname in filter(lambda x: re.match(cls.ARCHIVE_PATHS, x), fzip.namelist()):
                    pidb = cls._parse_data(file_from_zip(path, fname).decode('utf-8'), pidb)
            return pidb
        return cls._parse_data(Path(path).read_text(encoding='utf-8'), pidb)
<|end_body_0|>

<|body_start_1|>
        report = libnmap.parser.NmapParser.parse_fromstring(data)
        for ihost in report.hosts:
            via_target = ihost.user_target_hostname or ihost.address
            import_time = datetime.fromtimestamp(int(ihost.starttime or time()))
            host_data = {}
            if ihost.hostnames:
                host_data['hostnames'] = list(set(ihost.hostnames))
                if not host_data.get('hostname'):
                    host_data['hostname'] = host_data['hostnames'][0]
            for osmatch in [item for item in ihost.os_match_probabilities() if item.accuracy == 100]:
                host_data['os'] = osmatch.name
                pidb.upsert_note(ihost.address, 'cpe', data=json.dumps(osmatch.get_cpe()))
            pidb.upsert_host(ihost.address, **host_data)
            for iscript in ihost.scripts_results:
                pidb.upsert_note(ihost.address, f"nmap.{iscript['id']}", via_target=via_target, data=json.dumps(iscript), import_time=import_time)
            for iservice in ihost.services:
                service_data = {'state': f'{iservice.state}:{iservice.reason}', 'import_time': import_time}
                if iservice.service:
                    service_data['name'] = iservice.service
                if iservice.banner:
                    service_data['info'] = iservice.banner
                pidb.upsert_service(ihost.address, iservice.protocol, iservice.port, **service_data)
                if iservice.cpelist:
                    pidb.upsert_note(ihost.address, 'cpe', iservice.protocol, iservice.port, via_target, data=json.dumps([x.cpestring for x in iservice.cpelist]), import_time=import_time)
                for iscript in iservice.scripts_results:
                    pidb.upsert_note(ihost.address, f"nmap.{iscript['id']}", iservice.protocol, iservice.port, via_target, data=json.dumps(iscript), import_time=import_time)
        return pidb
<|end_body_1|>

Solution:
class ParserModule:
    """nmap xml output parser"""

    def parse_path(cls, path):
        """parse data from path"""
        pidb = ParsedItemsDb()
        if is_zip(path):
            with ZipFile(path) as fzip:
                for fname in filter(lambda x: re.match(cls.ARCHIVE_PATHS, x), fzip.namelist()):
                    pidb = cls._parse_data(file_from_zip(path, fname).decode('utf-8'), pidb)
            return pidb
        return cls._parse_data(Path(path).read_text(encoding='utf-8'), pidb)

    def _parse_data(cls, data, pidb):
        """parse raw string data"""
        report = libnmap.parser.NmapParser.parse_fromstring(data)
        for ihost in report.hosts:
            via_target = ihost.user_target_hostname or ihost.address
            import_time = datetime.fromtimestamp(int(ihost.starttime or time()))
            host_data = {}
            if ihost.hostnames:
                host_data['hostnames'] = list(set(ihost.hostnames))
                if not host_data.get('hostname'):
                    host_data['hostname'] = host_data['hostnames'][0]
            for osmatch in [item for item in ihost.os_match_probabilities() if item.accuracy == 100]:
                host_data['os'] = osmatch.name
                pidb.upsert_note(ihost.address, 'cpe', data=json.dumps(osmatch.get_cpe()))
            pidb.upsert_host(ihost.address, **host_data)
            for iscript in ihost.scripts_results:
                pidb.upsert_note(ihost.address, f"nmap.{iscript['id']}", via_target=via_target, data=json.dumps(iscript), import_time=import_time)
            for iservice in ihost.services:
                service_data = {'state': f'{iservice.state}:{iservice.reason}', 'import_time': import_time}
                if iservice.service:
                    service_data['name'] = iservice.service
                if iservice.banner:
                    service_data['info'] = iservice.banner
                pidb.upsert_service(ihost.address, iservice.protocol, iservice.port, **service_data)
                if iservice.cpelist:
                    pidb.upsert_note(ihost.address, 'cpe', iservice.protocol, iservice.port, via_target, data=json.dumps([x.cpestring for x in iservice.cpelist]), import_time=import_time)
                for iscript in iservice.scripts_results:
                    pidb.upsert_note(ihost.address, f"nmap.{iscript['id']}", iservice.protocol, iservice.port, via_target, data=json.dumps(iscript), import_time=import_time)
        return pidb


Prompt:
Implement the Python class `VisualizationDemo` described below.

Class description:
Implement the VisualizationDemo class.

Method signatures and docstrings:
- def __init__(self, cfg, instance_mode=ColorMode.IMAGE): Args: cfg (CfgNode): instance_mode (ColorMode):
- def run_on_image(self, image_list, visualize=0): Args: image (np.ndarray): an image of shape (H, W, C) (in BGR order). This is the format used by OpenCV. Returns: predictions (dict): the output of the model. vis_output (VisImage): the visualized image output.

Implement the Python class `VisualizationDemo` described below.

Class description:
Implement the VisualizationDemo class.

Method signatures and docstrings:
- def __init__(self, cfg, instance_mode=ColorMode.IMAGE): Args: cfg (CfgNode): instance_mode (ColorMode):
- def run_on_image(self, image_list, visualize=0): Args: image (np.ndarray): an image of shape (H, W, C) (in BGR order). This is the format used by OpenCV. Returns: predictions (dict): the output of the model. vis_output (VisImage): the visualized image output.

<|skeleton|>
class VisualizationDemo:

    def __init__(self, cfg, instance_mode=ColorMode.IMAGE):
        """Args: cfg (CfgNode): instance_mode (ColorMode):"""
        <|body_0|>

    def run_on_image(self, image_list, visualize=0):
        """Args: image (np.ndarray): an image of shape (H, W, C) (in BGR order). This is the format used by OpenCV. Returns: predictions (dict): the output of the model. vis_output (VisImage): the visualized image output."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.metadata = MetadataCatalog.get(cfg.DATASETS.TEST[0] if len(cfg.DATASETS.TEST) else '__unused')
        self.cpu_device = torch.device('cpu')
        self.instance_mode = instance_mode
        self.predictor = BatchPredictor(cfg)
<|end_body_0|>

<|body_start_1|>
        vis_output = None
        all_predictions = self.predictor(image_list)
        if visualize:
            predictions = all_predictions[0]
            image = image_list[0]
            visualizer = Visualizer(image, self.metadata, instance_mode=self.instance_mode)
            if 'panoptic_seg' in predictions:
                panoptic_seg, segments_info = predictions['panoptic_seg']
                vis_output = visualizer.draw_panoptic_seg_predictions(panoptic_seg.to(self.cpu_device), segments_info)
            else:
                if 'sem_seg' in predictions:
                    vis_output = visualizer.draw_sem_seg(predictions['sem_seg'].argmax(dim=0).to(self.cpu_device))
                if 'instances' in predictions:
                    instances = predictions['instances'].to(self.cpu_device)
                    vis_output = visualizer.draw_instance_predictions(predictions=instances)
        return (all_predictions, vis_output)
<|end_body_1|>

Solution:
class VisualizationDemo:
    def __init__(self, cfg, instance_mode=ColorMode.IMAGE):
        """Args: cfg (CfgNode): instance_mode (ColorMode):"""
        self.metadata = MetadataCatalog.get(cfg.DATASETS.TEST[0] if len(cfg.DATASETS.TEST) else '__unused')
        self.cpu_device = torch.device('cpu')
        self.instance_mode = instance_mode
        self.predictor = BatchPredictor(cfg)

    def run_on_image(self, image_list, visualize=0):
        """Args: image (np.ndarray): an image of shape (H, W, C) (in BGR order). This is the format used by OpenCV. Returns: predictions (dict): the output of the model. vis_output (VisImage): the visualized image output."""
        vis_output = None
        all_predictions = self.predictor(image_list)
        if visualize:
            predictions = all_predictions[0]
            image = image_list[0]
            visualizer = Visualizer(image, self.metadata, instance_mode=self.instance_mode)
            if 'panoptic_seg' in predictions:
                panoptic_seg, segments_info = predictions['panoptic_seg']
                vis_output = visualizer.draw_panoptic_seg_predictions(panoptic_seg.to(self.cpu_device), segments_info)
            else:
                if 'sem_seg' in predictions:
                    vis_output = visualizer.draw_sem_seg(predictions['sem_seg'].argmax(dim=0).to(self.cpu_device))
                if 'instances' in predictions:
                    instances = predictions['instances'].to(self.cpu_device)
                    vis_output = visualizer.draw_instance_predictions(predictions=instances)
        return (all_predictions, vis_output)


drop

Prompt:
Implement the Python class `ChangesetColumn` described below.

Class description:
Changeset extensions to SQLAlchemy columns

Method signatures and docstrings:
- def alter(self, *p, **k): Alter a column's definition: ``ALTER TABLE ALTER COLUMN``. May supply a new column object, or a list of properties to change. For example; the following are equivalent: col.alter(Column('myint', Integer, nullable=False)) col.alter('myint', Integer, nullable=False) col.alter(name='myint', type=Integer, nullable=False) Column name, type, default, and nullable may be changed here. Note that for column defaults, only PassiveDefaults are managed by the database - changing others doesn't make sense.
- def create(self, table=None, *args, **kwargs): Create this column in the database. Assumes the given table exists. ``ALTER TABLE ADD COLUMN``, for most databases.
- def drop(self, table=None, *args, **kwargs): Drop this column from the database, leaving its table intact. ``ALTER TABLE DROP COLUMN``, for most databases.

Implement the Python class `ChangesetColumn` described below.

Class description:
Changeset extensions to SQLAlchemy columns

Method signatures and docstrings:
- def alter(self, *p, **k): Alter a column's definition: ``ALTER TABLE ALTER COLUMN``. May supply a new column object, or a list of properties to change. For example; the following are equivalent: col.alter(Column('myint', Integer, nullable=False)) col.alter('myint', Integer, nullable=False) col.alter(name='myint', type=Integer, nullable=False) Column name, type, default, and nullable may be changed here. Note that for column defaults, only PassiveDefaults are managed by the database - changing others doesn't make sense.
- def create(self, table=None, *args, **kwargs): Create this column in the database. Assumes the given table exists. ``ALTER TABLE ADD COLUMN``, for most databases.
- def drop(self, table=None, *args, **kwargs): Drop this column from the database, leaving its table intact. ``ALTER TABLE DROP COLUMN``, for most databases.

<|skeleton|>
class ChangesetColumn:
    """Changeset extensions to SQLAlchemy columns"""

    def alter(self, *p, **k):
        """Alter a column's definition: ``ALTER TABLE ALTER COLUMN``. May supply a new column object, or a list of properties to change. For example; the following are equivalent: col.alter(Column('myint', Integer, nullable=False)) col.alter('myint', Integer, nullable=False) col.alter(name='myint', type=Integer, nullable=False) Column name, type, default, and nullable may be changed here. Note that for column defaults, only PassiveDefaults are managed by the database - changing others doesn't make sense."""
        <|body_0|>

    def create(self, table=None, *args, **kwargs):
        """Create this column in the database. Assumes the given table exists. ``ALTER TABLE ADD COLUMN``, for most databases."""
        <|body_1|>

    def drop(self, table=None, *args, **kwargs):
        """Drop this column from the database, leaving its table intact. ``ALTER TABLE DROP COLUMN``, for most databases."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        if 'table' not in k:
            k['table'] = self.table
        if 'engine' not in k:
            k['engine'] = k['table'].bind
        return alter_column(self, *p, **k)
<|end_body_0|>

<|body_start_1|>
        table = _normalize_table(self, table)
        engine = table.bind
        visitorcallable = get_engine_visitor(engine, 'columngenerator')
        engine._run_visitor(visitorcallable, self, *args, **kwargs)
        if self.foreign_keys:
            for fk in self.foreign_keys:
                visitorcallable = get_engine_visitor(engine, 'columnfkgenerator')
                engine._run_visitor(visitorcallable, self, fk=fk)
        return self
<|end_body_1|>

<|body_start_2|>
        table = _normalize_table(self, table)
        engine = table.bind
        visitorcallable = get_engine_visitor(engine, 'columndropper')
        engine._run_visitor(lambda dialect, conn: visitorcallable(conn), self, *args, **kwargs)
        return self
<|end_body_2|>

Solution:
class ChangesetColumn:
    """Changeset extensions to SQLAlchemy columns"""

    def alter(self, *p, **k):
        """Alter a column's definition: ``ALTER TABLE ALTER COLUMN``. May supply a new column object, or a list of properties to change. For example; the following are equivalent: col.alter(Column('myint', Integer, nullable=False)) col.alter('myint', Integer, nullable=False) col.alter(name='myint', type=Integer, nullable=False) Column name, type, default, and nullable may be changed here. Note that for column defaults, only PassiveDefaults are managed by the database - changing others doesn't make sense."""
        if 'table' not in k:
            k['table'] = self.table
        if 'engine' not in k:
            k['engine'] = k['table'].bind
        return alter_column(self, *p, **k)

    def create(self, table=None, *args, **kwargs):
        """Create this column in the database. Assumes the given table exists. ``ALTER TABLE ADD COLUMN``, for most databases."""
        table = _normalize_table(self, table)
        engine = table.bind
        visitorcallable = get_engine_visitor(engine, 'columngenerator')
        engine._run_visitor(visitorcallable, self, *args, **kwargs)
        if self.foreign_keys:
            for fk in self.foreign_keys:
                visitorcallable = get_engine_visitor(engine, 'columnfkgenerator')
                engine._run_visitor(visitorcallable, self, fk=fk)
        return self

    def drop(self, table=None, *args, **kwargs):
        """Drop this column from the database, leaving its table intact. ``ALTER TABLE DROP COLUMN``, for most databases."""
        table = _normalize_table(self, table)
        engine = table.bind
        visitorcallable = get_engine_visitor(engine, 'columndropper')
        engine._run_visitor(lambda dialect, conn: visitorcallable(conn), self, *args, **kwargs)
        return self


testFailedDeps

Prompt:
Implement the Python class `BuildCommandTest` described below.

Class description:
Test class for our BuildCommand class.

Method signatures and docstrings:
- def testBrilloBuildOperationCalled(self): Test that BrilloBuildOperation is used when appropriate.
- def testBrilloBuildOperationNotCalled(self): Test that BrilloBuildOperation is not used when it shouldn't be.
- def testSuccess(self): Test that successful commands work.
- def testFailedDeps(self): Test that failures are detected correctly.

Implement the Python class `BuildCommandTest` described below.

Class description:
Test class for our BuildCommand class.

Method signatures and docstrings:
- def testBrilloBuildOperationCalled(self): Test that BrilloBuildOperation is used when appropriate.
- def testBrilloBuildOperationNotCalled(self): Test that BrilloBuildOperation is not used when it shouldn't be.
- def testSuccess(self): Test that successful commands work.
- def testFailedDeps(self): Test that failures are detected correctly.

<|skeleton|>
class BuildCommandTest:
    """Test class for our BuildCommand class."""

    def testBrilloBuildOperationCalled(self):
        """Test that BrilloBuildOperation is used when appropriate."""
        <|body_0|>

    def testBrilloBuildOperationNotCalled(self):
        """Test that BrilloBuildOperation is not used when it shouldn't be."""
        <|body_1|>

    def testSuccess(self):
        """Test that successful commands work."""
        <|body_2|>

    def testFailedDeps(self):
        """Test that failures are detected correctly."""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        cmd = ['--board=randonname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper')
        self.PatchObject(command, 'UseProgressBar', return_value=True)
        with MockBuildCommand(cmd) as build:
            operation_run = self.PatchObject(cros_build.BrilloBuildOperation, 'Run')
            build.inst.Run()
            self.assertTrue(operation_run.called)
<|end_body_0|>

<|body_start_1|>
        cmd = ['--board=randonname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper')
        self.PatchObject(command, 'UseProgressBar', return_value=False)
        with MockBuildCommand(cmd) as build:
            operation_run = self.PatchObject(cros_build.BrilloBuildOperation, 'Run')
            build.inst.Run()
            self.assertFalse(operation_run.called)
<|end_body_1|>

<|body_start_2|>
        cmds = [['--host', 'power_manager'], ['--board=randomname', 'power_manager'], ['--board=randomname', '--debug', 'power_manager'], ['--board=randomname', '--no-deps', 'power_manager'], ['--board=randomname', '--no-chroot-update', 'power_manager'], ['--board=randomname', '--no-enable-only-latest', 'power_manager']]
        for cmd in cmds:
            update_chroot = not ('--no-deps' in cmd or '--no-chroot-update' in cmd)
            enable_only_latest = '--no-enable-only-latest' not in cmd
            fake_workon_helper = FakeWorkonHelper()
            self.PatchObject(workon_helper, 'WorkonHelper', return_value=fake_workon_helper)
            with MockBuildCommand(cmd) as build:
                build.inst.Run()
                self.assertEquals(1 if update_chroot else 0, build.chroot_update_called)
                self.assertEquals(1 if enable_only_latest else 0, fake_workon_helper.start_called)
                self.assertEquals(True if enable_only_latest else None, fake_workon_helper.use_workon_only)
<|end_body_2|>

<|body_start_3|>
        args = ['--board=randomname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper', return_value=FakeWorkonHelper())
        with MockBuildCommand(args) as build:
            cmd = partial_mock.In('--backtrack=0')
            build.rc_mock.AddCmdResult(cmd=cmd, returncode=1, error='error\n')
            with self.OutputCapturer():
                try:
                    build.inst.Run()
                except Exception as e:
                    logging.error(e)
            self.AssertOutputContainsError(cros_build.BuildCommand._BAD_DEPEND_MSG, check_stderr=True)
<|end_body_3|>

Solution:
class BuildCommandTest:
    """Test class for our BuildCommand class."""

    def testBrilloBuildOperationCalled(self):
        """Test that BrilloBuildOperation is used when appropriate."""
        cmd = ['--board=randonname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper')
        self.PatchObject(command, 'UseProgressBar', return_value=True)
        with MockBuildCommand(cmd) as build:
            operation_run = self.PatchObject(cros_build.BrilloBuildOperation, 'Run')
            build.inst.Run()
            self.assertTrue(operation_run.called)

    def testBrilloBuildOperationNotCalled(self):
        """Test that BrilloBuildOperation is not used when it shouldn't be."""
        cmd = ['--board=randonname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper')
        self.PatchObject(command, 'UseProgressBar', return_value=False)
        with MockBuildCommand(cmd) as build:
            operation_run = self.PatchObject(cros_build.BrilloBuildOperation, 'Run')
            build.inst.Run()
            self.assertFalse(operation_run.called)

    def testSuccess(self):
        """Test that successful commands work."""
        cmds = [['--host', 'power_manager'], ['--board=randomname', 'power_manager'], ['--board=randomname', '--debug', 'power_manager'], ['--board=randomname', '--no-deps', 'power_manager'], ['--board=randomname', '--no-chroot-update', 'power_manager'], ['--board=randomname', '--no-enable-only-latest', 'power_manager']]
        for cmd in cmds:
            update_chroot = not ('--no-deps' in cmd or '--no-chroot-update' in cmd)
            enable_only_latest = '--no-enable-only-latest' not in cmd
            fake_workon_helper = FakeWorkonHelper()
            self.PatchObject(workon_helper, 'WorkonHelper', return_value=fake_workon_helper)
            with MockBuildCommand(cmd) as build:
                build.inst.Run()
                self.assertEquals(1 if update_chroot else 0, build.chroot_update_called)
                self.assertEquals(1 if enable_only_latest else 0, fake_workon_helper.start_called)
                self.assertEquals(True if enable_only_latest else None, fake_workon_helper.use_workon_only)

    def testFailedDeps(self):
        """Test that failures are detected correctly."""
        args = ['--board=randomname', 'power_manager']
        self.PatchObject(workon_helper, 'WorkonHelper', return_value=FakeWorkonHelper())
        with MockBuildCommand(args) as build:
            cmd = partial_mock.In('--backtrack=0')
            build.rc_mock.AddCmdResult(cmd=cmd, returncode=1, error='error\n')
            with self.OutputCapturer():
                try:
                    build.inst.Run()
                except Exception as e:
                    logging.error(e)
            self.AssertOutputContainsError(cros_build.BuildCommand._BAD_DEPEND_MSG, check_stderr=True)


Prompt:
Implement the Python class `CarService` described below.

Class description:
Implement the CarService class.

Method signatures and docstrings:
- def get_available_cars(self): Saekir alla bila sem eru ekki i leigu og skilar theim
- def get_booked_cars(self): Saekir alla bila sem eru i leigu og skilar theim

Implement the Python class `CarService` described below.

Class description:
Implement the CarService class.

Method signatures and docstrings:
- def get_available_cars(self): Saekir alla bila sem eru ekki i leigu og skilar theim
- def get_booked_cars(self): Saekir alla bila sem eru i leigu og skilar theim

<|skeleton|>
class CarService:

    def get_available_cars(self):
        """Saekir alla bila sem eru ekki i leigu og skilar theim"""
        <|body_0|>

    def get_booked_cars(self):
        """Saekir alla bila sem eru i leigu og skilar theim"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        available_cars = []
        all_cars = self.get_full_content()
        for car in all_cars:
            if not car.is_booked():
                available_cars.append(car)
        return available_cars
<|end_body_0|>

<|body_start_1|>
        booked_cars = []
        all_cars = self.get_full_content()
        for car in all_cars:
            if car.is_booked():
                booked_cars.append(car)
        return booked_cars
<|end_body_1|>

Solution:
class CarService:
    def get_available_cars(self):
        """Saekir alla bila sem eru ekki i leigu og skilar theim"""
        available_cars = []
        all_cars = self.get_full_content()
        for car in all_cars:
            if not car.is_booked():
                available_cars.append(car)
        return available_cars

    def get_booked_cars(self):
        """Saekir alla bila sem eru i leigu og skilar theim"""
        booked_cars = []
        all_cars = self.get_full_content()
        for car in all_cars:
            if car.is_booked():
                booked_cars.append(car)
        return booked_cars


Prompt:
Implement the Python class `ProjectViewSet` described below.

Class description:
Project ModelViewSet Filters: is_demo

Method signatures and docstrings:
- def delete_tag(self, request, pk=None): delete tag
- def relabel_keep_alive(self, request, pk=None) -> Response: relabel_keep_alive. Args: request: kwargs: Returns: Response: Return project with updated timestamp

Implement the Python class `ProjectViewSet` described below.

Class description:
Project ModelViewSet Filters: is_demo

Method signatures and docstrings:
- def delete_tag(self, request, pk=None): delete tag
- def relabel_keep_alive(self, request, pk=None) -> Response: relabel_keep_alive. Args: request: kwargs: Returns: Response: Return project with updated timestamp

<|skeleton|>
class ProjectViewSet:
    """Project ModelViewSet Filters: is_demo"""

    def delete_tag(self, request, pk=None):
        """delete tag"""
        <|body_0|>

    def relabel_keep_alive(self, request, pk=None) -> Response:
        """relabel_keep_alive. Args: request: kwargs: Returns: Response: Return project with updated timestamp"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        try:
            project_obj = self.get_object()
            part_id = request.query_params.get('part_id') or None
            part_name = request.query_params.get('part_name') or None
            if part_id is not None:
                project_obj.delete_tag_by_id(tag_id=part_id)
                return Response({'status': 'ok'})
            if part_name is not None:
                project_obj.delete_tag_by_name(tag_name=part_name)
                return Response({'status': 'ok'})
            raise AttributeError('part_name or part_id not found')
        except AttributeError as attr_err:
            return Response({'status': 'failed', 'log': str(attr_err)}, status=status.HTTP_400_BAD_REQUEST)
        except CustomVisionErrorException as customvision_err:
            return Response({'status': 'failed', 'log': str(customvision_err)}, status=status.HTTP_503_SERVICE_UNAVAILABLE)
<|end_body_0|>

<|body_start_1|>
        queryset = self.get_queryset()
        obj = get_object_or_404(queryset, pk=pk)
        obj.relabel_expired_time = timezone.now() + datetime.timedelta(seconds=PROJECT_RELABEL_TIME_THRESHOLD)
        obj.save()
        serializer = ProjectSerializer(obj)
        return Response(serializer.data)
<|end_body_1|>

Solution:
class ProjectViewSet:
    """Project ModelViewSet Filters: is_demo"""

    def delete_tag(self, request, pk=None):
        """delete tag"""
        try:
            project_obj = self.get_object()
            part_id = request.query_params.get('part_id') or None
            part_name = request.query_params.get('part_name') or None
            if part_id is not None:
                project_obj.delete_tag_by_id(tag_id=part_id)
                return Response({'status': 'ok'})
            if part_name is not None:
                project_obj.delete_tag_by_name(tag_name=part_name)
                return Response({'status': 'ok'})
            raise AttributeError('part_name or part_id not found')
        except AttributeError as attr_err:
            return Response({'status': 'failed', 'log': str(attr_err)}, status=status.HTTP_400_BAD_REQUEST)
        except CustomVisionErrorException as customvision_err:
            return Response({'status': 'failed', 'log': str(customvision_err)}, status=status.HTTP_503_SERVICE_UNAVAILABLE)

    def relabel_keep_alive(self, request, pk=None) -> Response:
        """relabel_keep_alive. Args: request: kwargs: Returns: Response: Return project with updated timestamp"""
        queryset = self.get_queryset()
        obj = get_object_or_404(queryset, pk=pk)
        obj.relabel_expired_time = timezone.now() + datetime.timedelta(seconds=PROJECT_RELABEL_TIME_THRESHOLD)
        obj.save()
        serializer = ProjectSerializer(obj)
        return Response(serializer.data)


Prompt:
Implement the Python class `SfNotifySmsClient` described below.

Class description:
Implement the SfNotifySmsClient class.

Method signatures and docstrings:
- def sms_create(self, phone, message): create sms :param phone(required): The phone number to send :param message(required): Content of short message
- def sms_config_set(self, cfg, **kwargs): update config ini file :param cfg: dict of config like this: {section:{option:value}} :param kwargs: multiple section
- def sms_config_get(self): get config ini file

Implement the Python class `SfNotifySmsClient` described below.

Class description:
Implement the SfNotifySmsClient class.

Method signatures and docstrings:
- def sms_create(self, phone, message): create sms :param phone(required): The phone number to send :param message(required): Content of short message
- def sms_config_set(self, cfg, **kwargs): update config ini file :param cfg: dict of config like this: {section:{option:value}} :param kwargs: multiple section
- def sms_config_get(self): get config ini file

<|skeleton|>
class SfNotifySmsClient:

    def sms_create(self, phone, message):
        """create sms :param phone(required): The phone number to send :param message(required): Content of short message"""
        <|body_0|>

    def sms_config_set(self, cfg, **kwargs):
        """update config ini file :param cfg: dict of config like this: {section:{option:value}} :param kwargs: multiple section"""
        <|body_1|>

    def sms_config_get(self):
        """get config ini file"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        uri = '%s/sms/send' % self.uri_prefix
        post_body = {'phone': phone, 'sms': message}
        post_body = json.dumps(post_body)
        resp, body = self.post(uri, post_body)
        self.expected_success(201, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)
<|end_body_0|>

<|body_start_1|>
        uri = '%s/sms/config' % self.uri_prefix
        if kwargs:
            cfg.update(kwargs)
        cfg = json.dumps(cfg)
        post_body = {'config': cfg}
        post_body = json.dumps(post_body)
        resp, body = self.post(uri, post_body)
        self.expected_success(201, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)
<|end_body_1|>

<|body_start_2|>
        uri = '%s/sms/config' % self.uri_prefix
        resp, body = self.get(uri)
        self.expected_success(200, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)
<|end_body_2|>

Solution:
class SfNotifySmsClient:
    def sms_create(self, phone, message):
        """create sms :param phone(required): The phone number to send :param message(required): Content of short message"""
        uri = '%s/sms/send' % self.uri_prefix
        post_body = {'phone': phone, 'sms': message}
        post_body = json.dumps(post_body)
        resp, body = self.post(uri, post_body)
        self.expected_success(201, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)

    def sms_config_set(self, cfg, **kwargs):
        """update config ini file :param cfg: dict of config like this: {section:{option:value}} :param kwargs: multiple section"""
        uri = '%s/sms/config' % self.uri_prefix
        if kwargs:
            cfg.update(kwargs)
        cfg = json.dumps(cfg)
        post_body = {'config': cfg}
        post_body = json.dumps(post_body)
        resp, body = self.post(uri, post_body)
        self.expected_success(201, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)

    def sms_config_get(self):
        """get config ini file"""
        uri = '%s/sms/config' % self.uri_prefix
        resp, body = self.get(uri)
        self.expected_success(200, resp.status)
        body = json.loads(body)
        return service_client.ResponseBody(resp, body)


Prompt:
Implement the Python class `stock_picking` described below.

Class description:
Implement the stock_picking class.

Method signatures and docstrings:
- def _get_discount_invoice(self, cr, uid, move_line): Return the discount for the move line
- def _get_discount2_invoice(self, cr, uid, move_line): Return the discount for the move line
- def _get_price_unit_invoice(self, cr, uid, move_line, type, context=None): Gets price unit for invoice @param move_line: Stock move lines @param type: Type of invoice @return: The price unit for the move line
- def _prepare_invoice_line(self, cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None): Builds the dict containing the values for the invoice line @param group: True or False @param picking: picking object @param: move_line: move_line object @param: invoice_id: ID of the related invoice @param: invoice_vals: dict used to created the invoice @return: dict that will be used to create the invoice line

Implement the Python class `stock_picking` described below.

Class description:
Implement the stock_picking class.

Method signatures and docstrings:
- def _get_discount_invoice(self, cr, uid, move_line): Return the discount for the move line
- def _get_discount2_invoice(self, cr, uid, move_line): Return the discount for the move line
- def _get_price_unit_invoice(self, cr, uid, move_line, type, context=None): Gets price unit for invoice @param move_line: Stock move lines @param type: Type of invoice @return: The price unit for the move line
- def _prepare_invoice_line(self, cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None): Builds the dict containing the values for the invoice line @param group: True or False @param picking: picking object @param: move_line: move_line object @param: invoice_id: ID of the related invoice @param: invoice_vals: dict used to created the invoice @return: dict that will be used to create the invoice line

<|skeleton|>
class stock_picking:

    def _get_discount_invoice(self, cr, uid, move_line):
        """Return the discount for the move line"""
        <|body_0|>

    def _get_discount2_invoice(self, cr, uid, move_line):
        """Return the discount for the move line"""
        <|body_1|>

    def _get_price_unit_invoice(self, cr, uid, move_line, type, context=None):
        """Gets price unit for invoice @param move_line: Stock move lines @param type: Type of invoice @return: The price unit for the move line"""
        <|body_2|>

    def _prepare_invoice_line(self, cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None):
        """Builds the dict containing the values for the invoice line @param group: True or False @param picking: picking object @param: move_line: move_line object @param: invoice_id: ID of the related invoice @param: invoice_vals: dict used to created the invoice @return: dict that will be used to create the invoice line"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        discount = 0.0
        if move_line.purchase_line_id.id:
            discount = move_line.purchase_line_id.discount
        elif move_line.sale_line_id.id:
            discount = move_line.sale_line_id.discount
        return discount
<|end_body_0|>

<|body_start_1|>
        discount = 0.0
        if move_line.purchase_line_id.id:
            discount = move_line.purchase_line_id.discount2
        elif move_line.sale_line_id.id:
            discount = move_line.sale_line_id.discount2
        return discount
<|end_body_1|>

<|body_start_2|>
        price_unit = super(stock_picking, self)._get_price_unit_invoice(cr, uid, move_line, type)
        if move_line.purchase_line_id.id:
            price_unit = move_line.purchase_line_id.price_unit
        elif move_line.sale_line_id.id:
            price_unit = move_line.sale_line_id.price_unit
        return price_unit
<|end_body_2|>

<|body_start_3|>
        result = super(stock_picking, self)._prepare_invoice_line(cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None)
        result['discount'] = self._get_discount_invoice(cr, uid, move_line)
        result['discount2'] = self._get_discount2_invoice(cr, uid, move_line)
        result['price_unit'] = self._get_price_unit_invoice(cr, uid, move_line, invoice_vals['type'], context=None)
        return result
<|end_body_3|>

Solution:
class stock_picking:
    def _get_discount_invoice(self, cr, uid, move_line):
        """Return the discount for the move line"""
        discount = 0.0
        if move_line.purchase_line_id.id:
            discount = move_line.purchase_line_id.discount
        elif move_line.sale_line_id.id:
            discount = move_line.sale_line_id.discount
        return discount

    def _get_discount2_invoice(self, cr, uid, move_line):
        """Return the discount for the move line"""
        discount = 0.0
        if move_line.purchase_line_id.id:
            discount = move_line.purchase_line_id.discount2
        elif move_line.sale_line_id.id:
            discount = move_line.sale_line_id.discount2
        return discount

    def _get_price_unit_invoice(self, cr, uid, move_line, type, context=None):
        """Gets price unit for invoice @param move_line: Stock move lines @param type: Type of invoice @return: The price unit for the move line"""
        price_unit = super(stock_picking, self)._get_price_unit_invoice(cr, uid, move_line, type)
        if move_line.purchase_line_id.id:
            price_unit = move_line.purchase_line_id.price_unit
        elif move_line.sale_line_id.id:
            price_unit = move_line.sale_line_id.price_unit
        return price_unit

    def _prepare_invoice_line(self, cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None):
        """Builds the dict containing the values for the invoice line @param group: True or False @param picking: picking object @param: move_line: move_line object @param: invoice_id: ID of the related invoice @param: invoice_vals: dict used to created the invoice @return: dict that will be used to create the invoice line"""
        result = super(stock_picking, self)._prepare_invoice_line(cr, uid, group, picking, move_line, invoice_id, invoice_vals, context=None)
        result['discount'] = self._get_discount_invoice(cr, uid, move_line)
        result['discount2'] = self._get_discount2_invoice(cr, uid, move_line)
        result['price_unit'] = self._get_price_unit_invoice(cr, uid, move_line, invoice_vals['type'], context=None)
        return result


Prompt:
Implement the Python class `MileageCalculator` described below.

Class description:
Calculate mileage

Method signatures and docstrings:
- def __init__(self): Init.
- def calculate(self, bag_file): Calculate mileage

Implement the Python class `MileageCalculator` described below.

Class description:
Calculate mileage

Method signatures and docstrings:
- def __init__(self): Init.
- def calculate(self, bag_file): Calculate mileage

<|skeleton|>
class MileageCalculator:
    """Calculate mileage"""

    def __init__(self):
        """Init."""
        <|body_0|>

    def calculate(self, bag_file):
        """Calculate mileage"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.auto_mileage = 0.0
        self.manual_mileage = 0.0
        self.disengagements = 0
<|end_body_0|>

<|body_start_1|>
        last_pos = None
        last_mode = 'Unknown'
        mileage = collections.defaultdict(lambda: 0.0)
        chassis = chassis_pb2.Chassis()
        localization = localization_pb2.LocalizationEstimate()
        reader = RecordReader(bag_file)
        for msg in reader.read_messages():
            if msg.topic == kChassisTopic:
                chassis.ParseFromString(msg.message)
                if last_mode != chassis.driving_mode:
                    if last_mode == Chassis.COMPLETE_AUTO_DRIVE and chassis.driving_mode == Chassis.EMERGENCY_MODE:
                        self.disengagements += 1
                    last_mode = chassis.driving_mode
                    last_pos = None
            elif msg.topic == kLocalizationTopic:
                localization.ParseFromString(msg.message)
                cur_pos = localization.pose.position
                if last_pos:
                    mileage[last_mode] += 0.000621371 * math.sqrt((cur_pos.x - last_pos.x) ** 2 + (cur_pos.y - last_pos.y) ** 2 + (cur_pos.z - last_pos.z) ** 2)
                last_pos = cur_pos
        self.auto_mileage += mileage[Chassis.COMPLETE_AUTO_DRIVE]
        self.manual_mileage += mileage[Chassis.COMPLETE_MANUAL] + mileage[Chassis.EMERGENCY_MODE]
<|end_body_1|>

Solution:
class MileageCalculator:
    """Calculate mileage"""

    def __init__(self):
        """Init."""
        self.auto_mileage = 0.0
        self.manual_mileage = 0.0
        self.disengagements = 0

    def calculate(self, bag_file):
        """Calculate mileage"""
        last_pos = None
        last_mode = 'Unknown'
        mileage = collections.defaultdict(lambda: 0.0)
        chassis = chassis_pb2.Chassis()
        localization = localization_pb2.LocalizationEstimate()
        reader = RecordReader(bag_file)
        for msg in reader.read_messages():
            if msg.topic == kChassisTopic:
                chassis.ParseFromString(msg.message)
                if last_mode != chassis.driving_mode:
                    if last_mode == Chassis.COMPLETE_AUTO_DRIVE and chassis.driving_mode == Chassis.EMERGENCY_MODE:
                        self.disengagements += 1
                    last_mode = chassis.driving_mode
                    last_pos = None
            elif msg.topic == kLocalizationTopic:
                localization.ParseFromString(msg.message)
                cur_pos = localization.pose.position
                if last_pos:
                    mileage[last_mode] += 0.000621371 * math.sqrt((cur_pos.x - last_pos.x) ** 2 + (cur_pos.y - last_pos.y) ** 2 + (cur_pos.z - last_pos.z) ** 2)
                last_pos = cur_pos
        self.auto_mileage += mileage[Chassis.COMPLETE_AUTO_DRIVE]
        self.manual_mileage += mileage[Chassis.COMPLETE_MANUAL] + mileage[Chassis.EMERGENCY_MODE]


deserialize

Prompt:
Implement the Python class `Codec` described below.

Class description:
Implement the Codec class.

Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tree. :type data: str :rtype: Node

Implement the Python class `Codec` described below.

Class description:
Implement the Codec class.

Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tree. :type data: str :rtype: Node

<|skeleton|>
class Codec:

    def serialize(self, root: 'Node') -> str:
        """Encodes a tree to a single string. :type root: Node :rtype: str"""
        <|body_0|>

    def deserialize(self, data: str) -> 'Node':
        """Decodes your encoded data to tree. :type data: str :rtype: Node"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if root is None:
            return ''
        data = []
        deq = collections.deque([root])
        while deq:
            node = deq.popleft()
            data.append(node.val)
            data.append(str(0 if not node.children else len(node.children)))
            if node.children:
                for child in node.children:
                    deq.append(child)
        return ','.join(data)
<|end_body_0|>

<|body_start_1|>
        if len(data) == 0:
            return None
        data = data.split(',')
        root = Node(int(data[0]), [])
        n = int(data[1])
        deq = collections.deque([(root, n)])
        i = 2
        while deq:
            node, n = deq.popleft()
            for j in range(i, i + 2 * n, 2):
                child = Node(int(data[j]), [])
                k = int(data[j + 1])
                node.children.append(child)
                deq.append((child, k))
            i += 2 * n
        return root
<|end_body_1|>

Solution:
class Codec:
    def serialize(self, root: 'Node') -> str:
        """Encodes a tree to a single string. :type root: Node :rtype: str"""
        if root is None:
            return ''
        data = []
        deq = collections.deque([root])
        while deq:
            node = deq.popleft()
            data.append(node.val)
            data.append(str(0 if not node.children else len(node.children)))
            if node.children:
                for child in node.children:
                    deq.append(child)
        return ','.join(data)

    def deserialize(self, data: str) -> 'Node':
        """Decodes your encoded data to tree. :type data: str :rtype: Node"""
        if len(data) == 0:
            return None
        data = data.split(',')
        root = Node(int(data[0]), [])
        n = int(data[1])
        deq = collections.deque([(root, n)])
        i = 2
        while deq:
            node, n = deq.popleft()
            for j in range(i, i + 2 * n, 2):
                child = Node(int(data[j]), [])
                k = int(data[j + 1])
                node.children.append(child)
                deq.append((child, k))
            i += 2 * n
        return root

Leetcode 0428. Serialize and Deserialize N-ary Tree.py


Prompt:
Implement the Python class `OptunaSolver` described below.

Class description:
Implement the OptunaSolver class.

Method signatures and docstrings:
- def __init__(self, project=None): The constructor accepts a HyppopyProject. :param project: [HyppopyProject] project instance, default=None
- def define_interface(self): This function is called when HyppopySolver.__init__ function finished. Child classes need to define their individual parameter here by calling the _add_member function for each class member variable need to be defined. Using _add_hyperparameter_signature the structure of a hyperparameter the solver expects must be defined. Both, members and hyperparameter signatures are later get checked, before executing the solver, ensuring settings passed fullfill solver needs.
- def get_candidates(self, trial=None): This function converts the searchspace to a candidate_list that can then be used to distribute via MPI. :param searchspace: converted hyperparameter space
- def trial_cache(self, trial): Optuna specific loss function wrapper :param trial: [Trial] instance :return: [function] loss function
- def execute_solver(self, searchspace): This function is called immediately after convert_searchspace and get the output of the latter as input. It's purpose is to call the solver libs main optimization function. :param searchspace: converted hyperparameter space
- def convert_searchspace(self, hyperparameter): This function gets the unified hyppopy-like parameterspace description as input and, if necessary, should convert it into a solver lib specific format. The function is invoked when run is called and what it returns is passed as searchspace argument to the function execute_solver. :param hyperparameter: [dict] nested parameter description dict e.g. {'name': {'domain':'uniform', 'data':[0,1], 'type':'float'}, ...} :return: [object] converted hyperparameter space

Implement the Python class `OptunaSolver` described below.

Class description:
Implement the OptunaSolver class.

Method signatures and docstrings:
- def __init__(self, project=None): The constructor accepts a HyppopyProject. :param project: [HyppopyProject] project instance, default=None
- def define_interface(self): This function is called when HyppopySolver.__init__ function finished. Child classes need to define their individual parameter here by calling the _add_member function for each class member variable need to be defined. Using _add_hyperparameter_signature the structure of a hyperparameter the solver expects must be defined. Both, members and hyperparameter signatures are later get checked, before executing the solver, ensuring settings passed fullfill solver needs.
- def get_candidates(self, trial=None): This function converts the searchspace to a candidate_list that can then be used to distribute via MPI. :param searchspace: converted hyperparameter space
- def trial_cache(self, trial): Optuna specific loss function wrapper :param trial: [Trial] instance :return: [function] loss function
- def execute_solver(self, searchspace): This function is called immediately after convert_searchspace and get the output of the latter as input. It's purpose is to call the solver libs main optimization function. :param searchspace: converted hyperparameter space
- def convert_searchspace(self, hyperparameter): This function gets the unified hyppopy-like parameterspace description as input and, if necessary, should convert it into a solver lib specific format. The function is invoked when run is called and what it returns is passed as searchspace argument to the function execute_solver. :param hyperparameter: [dict] nested parameter description dict e.g. {'name': {'domain':'uniform', 'data':[0,1], 'type':'float'}, ...} :return: [object] converted hyperparameter space

<|skeleton|>
class OptunaSolver:

    def __init__(self, project=None):
        """The constructor accepts a HyppopyProject. :param project: [HyppopyProject] project instance, default=None"""
        <|body_0|>

    def define_interface(self):
        """This function is called when HyppopySolver.__init__ function finished. Child classes need to define their individual parameter here by calling the _add_member function for each class member variable need to be defined. Using _add_hyperparameter_signature the structure of a hyperparameter the solver expects must be defined. Both, members and hyperparameter signatures are later get checked, before executing the solver, ensuring settings passed fullfill solver needs."""
        <|body_1|>

    def get_candidates(self, trial=None):
        """This function converts the searchspace to a candidate_list that can then be used to distribute via MPI. :param searchspace: converted hyperparameter space"""
        <|body_2|>

    def trial_cache(self, trial):
        """Optuna specific loss function wrapper :param trial: [Trial] instance :return: [function] loss function"""
        <|body_3|>

    def execute_solver(self, searchspace):
        """This function is called immediately after convert_searchspace and get the output of the latter as input. It's purpose is to call the solver libs main optimization function. :param searchspace: converted hyperparameter space"""
        <|body_4|>

    def convert_searchspace(self, hyperparameter):
        """This function gets the unified hyppopy-like parameterspace description as input and, if necessary, should convert it into a solver lib specific format. The function is invoked when run is called and what it returns is passed as searchspace argument to the function execute_solver. :param hyperparameter: [dict] nested parameter description dict e.g. {'name': {'domain':'uniform', 'data':[0,1], 'type':'float'}, ...} :return: [object] converted hyperparameter space"""
        <|body_5|>

<|end_skeleton|>

<|body_start_0|>
        HyppopySolver.__init__(self, project)
        self._searchspace = None
        self.candidates_list = list()
<|end_body_0|>

<|body_start_1|>
        self._add_member('max_iterations', int)
        self._add_hyperparameter_signature(name='domain', dtype=str, options=['uniform', 'categorical'])
        self._add_hyperparameter_signature(name='data', dtype=list)
        self._add_hyperparameter_signature(name='type', dtype=type)
<|end_body_1|>

<|body_start_2|>
        candidates_list = list()
        N = self.max_iterations
        for n in range(N):
            print(n)
            from optuna import trial as trial_module
            trial_id = self.study._storage.create_new_trial_id(0)
            trial = trial_module.Trial(self.study, trial_id)
            params = {}
            for name, param in self._searchspace.items():
                if param['domain'] == 'categorical':
                    params[name] = trial.suggest_categorical(name, param['data'])
                else:
                    params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
            candidates_list.append(CandidateDescriptor(**params))
        return candidates_list
        N = self.max_iterations
        for n in range(N):
            params = {}
            for name, param in self._searchspace.items():
                if param['domain'] == 'categorical':
                    params[name] = trial.suggest_categorical(name, param['data'])
                else:
                    params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
            candidates_list.append(CandidateDescriptor(**params))
        return candidates_list
<|end_body_2|>

<|body_start_3|>
        params = {}
        for name, param in self._searchspace.items():
            if param['domain'] == 'categorical':
                params[name] = trial.suggest_categorical(name, param['data'])
            else:
                params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
        return self.loss_function(**params)
<|end_body_3|>

<|body_start_4|>
        LOG.debug('execute_solver using solution space:\n\n\t{}\n'.format(pformat(searchspace)))
        self._searchspace = searchspace
        try:
            study = optuna.create_study()
            study.optimize(self.trial_cache, n_trials=self.max_iterations)
            self.best = study.best_trial.params
        except Exception as e:
            LOG.error('internal error in bayes_opt maximize occured. {}'.format(e))
            raise BrokenPipeError('internal error in bayes_opt maximize occured. {}'.format(e))
<|end_body_4|>

<|body_start_5|>
        LOG.debug('convert input parameter\n\n\t{}\n'.format(pformat(hyperparameter)))
        for name, param in hyperparameter.items():
            if param['domain'] != 'categorical' and param['domain'] != 'uniform':
                msg = 'Warning: Optuna cannot handle {} domain. Only uniform and categorical domains are supported!'.format(param['domain'])
                warnings.warn(msg)
                LOG.warning(msg)
        return hyperparameter
<|end_body_5|>

Solution:
class OptunaSolver:
    def __init__(self, project=None):
        """The constructor accepts a HyppopyProject. :param project: [HyppopyProject] project instance, default=None"""
        HyppopySolver.__init__(self, project)
        self._searchspace = None
        self.candidates_list = list()

    def define_interface(self):
        """This function is called when HyppopySolver.__init__ function finished. Child classes need to define their individual parameter here by calling the _add_member function for each class member variable need to be defined. Using _add_hyperparameter_signature the structure of a hyperparameter the solver expects must be defined. Both, members and hyperparameter signatures are later get checked, before executing the solver, ensuring settings passed fullfill solver needs."""
        self._add_member('max_iterations', int)
        self._add_hyperparameter_signature(name='domain', dtype=str, options=['uniform', 'categorical'])
        self._add_hyperparameter_signature(name='data', dtype=list)
        self._add_hyperparameter_signature(name='type', dtype=type)

    def get_candidates(self, trial=None):
        """This function converts the searchspace to a candidate_list that can then be used to distribute via MPI. :param searchspace: converted hyperparameter space"""
        candidates_list = list()
        N = self.max_iterations
        for n in range(N):
            print(n)
            from optuna import trial as trial_module
            trial_id = self.study._storage.create_new_trial_id(0)
            trial = trial_module.Trial(self.study, trial_id)
            params = {}
            for name, param in self._searchspace.items():
                if param['domain'] == 'categorical':
                    params[name] = trial.suggest_categorical(name, param['data'])
                else:
                    params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
            candidates_list.append(CandidateDescriptor(**params))
        return candidates_list
        N = self.max_iterations
        for n in range(N):
            params = {}
            for name, param in self._searchspace.items():
                if param['domain'] == 'categorical':
                    params[name] = trial.suggest_categorical(name, param['data'])
                else:
                    params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
            candidates_list.append(CandidateDescriptor(**params))
        return candidates_list

    def trial_cache(self, trial):
        """Optuna specific loss function wrapper :param trial: [Trial] instance :return: [function] loss function"""
        params = {}
        for name, param in self._searchspace.items():
            if param['domain'] == 'categorical':
                params[name] = trial.suggest_categorical(name, param['data'])
            else:
                params[name] = trial.suggest_uniform(name, param['data'][0], param['data'][1])
        return self.loss_function(**params)

    def execute_solver(self, searchspace):
        """This function is called immediately after convert_searchspace and get the output of the latter as input. It's purpose is to call the solver libs main optimization function. :param searchspace: converted hyperparameter space"""
        LOG.debug('execute_solver using solution space:\n\n\t{}\n'.format(pformat(searchspace)))
        self._searchspace = searchspace
        try:
            study = optuna.create_study()
            study.optimize(self.trial_cache, n_trials=self.max_iterations)
            self.best = study.best_trial.params
        except Exception as e:
            LOG.error('internal error in bayes_opt maximize occured. {}'.format(e))
            raise BrokenPipeError('internal error in bayes_opt maximize occured. {}'.format(e))

    def convert_searchspace(self, hyperparameter):
        """This function gets the unified hyppopy-like parameterspace description as input and, if necessary, should convert it into a solver lib specific format. The function is invoked when run is called and what it returns is passed as searchspace argument to the function execute_solver. :param hyperparameter: [dict] nested parameter description dict e.g. {'name': {'domain':'uniform', 'data':[0,1], 'type':'float'}, ...} :return: [object] converted hyperparameter space"""
        LOG.debug('convert input parameter\n\n\t{}\n'.format(pformat(hyperparameter)))
        for name, param in hyperparameter.items():
            if param['domain'] != 'categorical' and param['domain'] != 'uniform':
                msg = 'Warning: Optuna cannot handle {} domain. Only uniform and categorical domains are supported!'.format(param['domain'])
                warnings.warn(msg)
                LOG.warning(msg)
        return hyperparameter


nextMessage

Prompt:
Implement the Python class `GameController` described below.

Class description:
Controller for running a game of Chess

Method signatures and docstrings:
- def __init__(self, game): Initialize the Game Controller
- def nextMessage(self, event): Tell the screen to print the next message

Implement the Python class `GameController` described below.

Class description:
Controller for running a game of Chess

Method signatures and docstrings:
- def __init__(self, game): Initialize the Game Controller
- def nextMessage(self, event): Tell the screen to print the next message

<|skeleton|>
class GameController:
    """Controller for running a game of Chess"""

    def __init__(self, game):
        """Initialize the Game Controller"""
        <|body_0|>

    def nextMessage(self, event):
        """Tell the screen to print the next message"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.game = game
        screen = GameScreen()
        ConsoleController.__init__(self, screen, commands={ENDL: self.nextMessage})
<|end_body_0|>

<|body_start_1|>
        while not self.game.over:
            self.runController(RoundController(self.game))
        self.stopRunning()
<|end_body_1|>

Solution:
class GameController:
    """Controller for running a game of Chess"""

    def __init__(self, game):
        """Initialize the Game Controller"""
        self.game = game
        screen = GameScreen()
        ConsoleController.__init__(self, screen, commands={ENDL: self.nextMessage})

    def nextMessage(self, event):
        """Tell the screen to print the next message"""
        while not self.game.over:
            self.runController(RoundController(self.game))
        self.stopRunning()


Prompt:
Implement the Python class `AutoGateS2TrainerCallback` described below.

Class description:
AutoGateS2TrainerCallback module.

Method signatures and docstrings:
- def __init__(self): Construct AutoGateS2TrainerCallback class.
- def before_train(self, logs=None): Call before_train of the managed callbacks.
- def after_train(self, logs=None): Call after_train of the managed callbacks.

Implement the Python class `AutoGateS2TrainerCallback` described below.

Class description:
AutoGateS2TrainerCallback module.

Method signatures and docstrings:
- def __init__(self): Construct AutoGateS2TrainerCallback class.
- def before_train(self, logs=None): Call before_train of the managed callbacks.
- def after_train(self, logs=None): Call after_train of the managed callbacks.

<|skeleton|>
class AutoGateS2TrainerCallback:
    """AutoGateS2TrainerCallback module."""

    def __init__(self):
        """Construct AutoGateS2TrainerCallback class."""
        <|body_0|>

    def before_train(self, logs=None):
        """Call before_train of the managed callbacks."""
        <|body_1|>

    def after_train(self, logs=None):
        """Call after_train of the managed callbacks."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        super(CtrTrainerCallback, self).__init__()
        self.sieve_board = pd.DataFrame(columns=['selected_feature_pairs', 'score'])
        self.selected_pairs = list()
        logging.info('init autogate s2 trainer callback')
<|end_body_0|>

<|body_start_1|>
        super().before_train(logs)
        'Be called before the training process.'
        hpo_result = FileOps.load_pickle(FileOps.join_path(self.trainer.local_output_path, 'best_config.pickle'))
        logging.info('loading stage1_hpo_result \n{}'.format(hpo_result))
        feature_interaction_score = hpo_result['feature_interaction_score']
        print('feature_interaction_score:', feature_interaction_score)
        sorted_pairs = sorted(feature_interaction_score.items(), key=lambda x: abs(x[1]), reverse=True)
        if ModelConfig.model_desc:
            fis_ratio = ModelConfig.model_desc['custom']['fis_ratio']
        else:
            fis_ratio = 1.0
        top_k = int(len(feature_interaction_score) * min(1.0, fis_ratio))
        self.selected_pairs = list(map(lambda x: x[0], sorted_pairs[:top_k]))
        setattr(ModelConfig.model_desc['custom'], 'selected_pairs', self.selected_pairs)
<|end_body_1|>

<|body_start_2|>
        curr_auc = float(self.trainer.valid_metrics.results['auc'])
        self.sieve_board = self.sieve_board.append({'selected_feature_pairs': self.selected_pairs, 'score': curr_auc}, ignore_index=True)
        result_file = FileOps.join_path(self.trainer.local_output_path, '{}_result.csv'.format(self.trainer.__worker_id__))
        self.sieve_board.to_csv(result_file, sep='\t')
<|end_body_2|>

Solution:
class AutoGateS2TrainerCallback:
    """AutoGateS2TrainerCallback module."""

    def __init__(self):
        """Construct AutoGateS2TrainerCallback class."""
        super(CtrTrainerCallback, self).__init__()
        self.sieve_board = pd.DataFrame(columns=['selected_feature_pairs', 'score'])
        self.selected_pairs = list()
        logging.info('init autogate s2 trainer callback')

    def before_train(self, logs=None):
        """Call before_train of the managed callbacks."""
        super().before_train(logs)
        'Be called before the training process.'
        hpo_result = FileOps.load_pickle(FileOps.join_path(self.trainer.local_output_path, 'best_config.pickle'))
        logging.info('loading stage1_hpo_result \n{}'.format(hpo_result))
        feature_interaction_score = hpo_result['feature_interaction_score']
        print('feature_interaction_score:', feature_interaction_score)
        sorted_pairs = sorted(feature_interaction_score.items(), key=lambda x: abs(x[1]), reverse=True)
        if ModelConfig.model_desc:
            fis_ratio = ModelConfig.model_desc['custom']['fis_ratio']
        else:
            fis_ratio = 1.0
        top_k = int(len(feature_interaction_score) * min(1.0, fis_ratio))
        self.selected_pairs = list(map(lambda x: x[0], sorted_pairs[:top_k]))
        setattr(ModelConfig.model_desc['custom'], 'selected_pairs', self.selected_pairs)

    def after_train(self, logs=None):
        """Call after_train of the managed callbacks."""
        curr_auc = float(self.trainer.valid_metrics.results['auc'])
        self.sieve_board = self.sieve_board.append({'selected_feature_pairs': self.selected_pairs, 'score': curr_auc}, ignore_index=True)
        result_file = FileOps.join_path(self.trainer.local_output_path, '{}_result.csv'.format(self.trainer.__worker_id__))
        self.sieve_board.to_csv(result_file, sep='\t')


Prompt:
Implement the Python class `AccumulateDiffStatsTest` described below.

Class description:
Checks for accumulate_diff_stats function

Method signatures and docstrings:
- def test_accumulate_diff_stats_ideal(self): Tests that accumulate_diff_stats function can handle simple ideal input
- def test_accumulate_diff_stats_check_output(self): Tests that accumulate_diff_stats function can generate correct correct output according to given specs
- def test_accumulate_diff_stats_calls_required_function(self, mock): Tests that accumulate_diff_stats function can call required function
- def test_accumulate_diff_stats_calls_second_required_function(self, mock): Tests that accumulate_diff_stats function can call required function
- def test_accumulate_diff_stats_calls_third_required_function(self, mock): Tests that accumulate_diff_stats function can call required function

Implement the Python class `AccumulateDiffStatsTest` described below.

Class description:
Checks for accumulate_diff_stats function

Method signatures and docstrings:
- def test_accumulate_diff_stats_ideal(self): Tests that accumulate_diff_stats function can handle simple ideal input
- def test_accumulate_diff_stats_check_output(self): Tests that accumulate_diff_stats function can generate correct correct output according to given specs
- def test_accumulate_diff_stats_calls_required_function(self, mock): Tests that accumulate_diff_stats function can call required function
- def test_accumulate_diff_stats_calls_second_required_function(self, mock): Tests that accumulate_diff_stats function can call required function
- def test_accumulate_diff_stats_calls_third_required_function(self, mock): Tests that accumulate_diff_stats function can call required function

<|skeleton|>
class AccumulateDiffStatsTest:
    """Checks for accumulate_diff_stats function"""

    def test_accumulate_diff_stats_ideal(self):
        """Tests that accumulate_diff_stats function can handle simple ideal input"""
        <|body_0|>

    def test_accumulate_diff_stats_check_output(self):
        """Tests that accumulate_diff_stats function can generate correct correct output according to given specs"""
        <|body_1|>

    def test_accumulate_diff_stats_calls_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        <|body_2|>

    def test_accumulate_diff_stats_calls_second_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        <|body_3|>

    def test_accumulate_diff_stats_calls_third_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        <|body_4|>

<|end_skeleton|>

<|body_start_0|>
        first_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        second_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'paw'))
        expected = {'text_plagiarism': 0.875, 'sentence_plagiarism': [1.0, 0.75], 'sentence_lcs_length': [4, 3], 'difference_indexes': [((), ()), ((3, 4), (3, 4))]}
        actual = accumulate_diff_stats(first_text, second_text)
        self.assertEqual(expected, actual)
<|end_body_0|>

<|body_start_1|>
        expected = {'text_plagiarism': 0.875, 'sentence_plagiarism': [1.0, 0.75], 'sentence_lcs_length': [4, 3], 'difference_indexes': [((), ()), ((3, 4), (3, 4))]}
        text_first = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        text_second = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'paw'))
        actual = accumulate_diff_stats(text_first, text_second)
        self.assertIn('text_plagiarism', actual)
        self.assertIn('sentence_plagiarism', actual)
        self.assertIn('sentence_lcs_length', actual)
        self.assertIn('difference_indexes', actual)
        self.assertEqual(expected['text_plagiarism'], actual['text_plagiarism'])
        self.assertEqual(expected['sentence_plagiarism'], actual['sentence_plagiarism'])
        self.assertEqual(expected['sentence_lcs_length'], actual['sentence_lcs_length'])
        self.assertEqual(expected['difference_indexes'], actual['difference_indexes'])
<|end_body_1|>

<|body_start_2|>
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)
<|end_body_2|>

<|body_start_3|>
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)
<|end_body_3|>

<|body_start_4|>
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)
<|end_body_4|>

Solution:
class AccumulateDiffStatsTest:
    """Checks for accumulate_diff_stats function"""

    def test_accumulate_diff_stats_ideal(self):
        """Tests that accumulate_diff_stats function can handle simple ideal input"""
        first_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        second_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'paw'))
        expected = {'text_plagiarism': 0.875, 'sentence_plagiarism': [1.0, 0.75], 'sentence_lcs_length': [4, 3], 'difference_indexes': [((), ()), ((3, 4), (3, 4))]}
        actual = accumulate_diff_stats(first_text, second_text)
        self.assertEqual(expected, actual)

    def test_accumulate_diff_stats_check_output(self):
        """Tests that accumulate_diff_stats function can generate correct correct output according to given specs"""
        expected = {'text_plagiarism': 0.875, 'sentence_plagiarism': [1.0, 0.75], 'sentence_lcs_length': [4, 3], 'difference_indexes': [((), ()), ((3, 4), (3, 4))]}
        text_first = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        text_second = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'paw'))
        actual = accumulate_diff_stats(text_first, text_second)
        self.assertIn('text_plagiarism', actual)
        self.assertIn('sentence_plagiarism', actual)
        self.assertIn('sentence_lcs_length', actual)
        self.assertIn('difference_indexes', actual)
        self.assertEqual(expected['text_plagiarism'], actual['text_plagiarism'])
        self.assertEqual(expected['sentence_plagiarism'], actual['sentence_plagiarism'])
        self.assertEqual(expected['sentence_lcs_length'], actual['sentence_lcs_length'])
        self.assertEqual(expected['difference_indexes'], actual['difference_indexes'])

    def test_accumulate_diff_stats_calls_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)

    def test_accumulate_diff_stats_calls_second_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)

    def test_accumulate_diff_stats_calls_third_required_function(self, mock):
        """Tests that accumulate_diff_stats function can call required function"""
        patches_text = (('i', 'have', 'a', 'cat'), ('his', 'name', 'is', 'bruno'))
        accumulate_diff_stats(patches_text, patches_text)
        self.assertTrue(mock.called)


testStats

Prompt:
Implement the Python class `TestStats` described below.

Class description:
Test the statistics interface.

Method signatures and docstrings:
- def PopulateData(): Populates data into the stats object.
- def testStats(self): Test the statistics interface. Unfortunately this test is pretty lame because we can not look into the canvas object with selenium.

Implement the Python class `TestStats` described below.

Class description:
Test the statistics interface.

Method signatures and docstrings:
- def PopulateData(): Populates data into the stats object.
- def testStats(self): Test the statistics interface. Unfortunately this test is pretty lame because we can not look into the canvas object with selenium.

<|skeleton|>
class TestStats:
    """Test the statistics interface."""

    def PopulateData():
        """Populates data into the stats object."""
        <|body_0|>

    def testStats(self):
        """Test the statistics interface. Unfortunately this test is pretty lame because we can not look into the canvas object with selenium."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        token = access_control.ACLToken(username='test', reason='fixture')
        with aff4.FACTORY.Create('aff4:/stats/ClientFleetStats', 'ClientFleetStats', token=token) as fd:
            now = 1321057655
            for i in range(10, 15):
                histogram = fd.Schema.OS_HISTOGRAM(age=int((now + i * 60 * 60 * 24) * 1000000.0))
                for number in [1, 7, 14, 30]:
                    graph = rdfvalue.Graph(title='%s day actives' % number)
                    graph.Append(label='Windows', y_value=i + number)
                    graph.Append(label='Linux', y_value=i * 2 + number)
                    histogram.Append(graph)
                fd.AddAttribute(histogram)
<|end_body_0|>

<|body_start_1|>
        self.Open('/')
        self.WaitUntil(self.IsElementPresent, 'client_query')
        self.assert_(not self.IsElementPresent('css=a[grrtarget=ReadOnlyForemanRuleTable]'))
        with self.ACLChecksDisabled():
            self.CreateAdminUser('test')
        self.Open('/')
        self.WaitUntil(self.IsElementPresent, 'client_query')
        self.WaitUntil(self.IsElementPresent, 'css=a[grrtarget=ReadOnlyForemanRuleTable]')
        self.Click("css=a:contains('Statistics')")
        self.Click('css=#_Clients ins.jstree-icon')
        self.Click('css=#_Clients-OS_20Breakdown ins.jstree-icon')
        self.WaitUntil(self.IsElementPresent, 'css=#_Clients-OS_20Breakdown-_207_20Day_20Active')
        self.Click("css=li[path='/Clients/OS Breakdown/ 7 Day Active'] a")
        self.WaitUntilEqual(u'No data Available', self.GetText, 'css=#main_rightPane h3')
        with self.ACLChecksDisabled():
            self.PopulateData()
        self.Click("css=li[path='/Clients/OS Breakdown/ 7 Day Active'] a")
        self.WaitUntilEqual(u'Operating system break down.', self.GetText, 'css=#main_rightPane h3')
<|end_body_1|>

Solution:
class TestStats:
    """Test the statistics interface."""

    def PopulateData():
        """Populates data into the stats object."""
        token = access_control.ACLToken(username='test', reason='fixture')
        with aff4.FACTORY.Create('aff4:/stats/ClientFleetStats', 'ClientFleetStats', token=token) as fd:
            now = 1321057655
            for i in range(10, 15):
                histogram = fd.Schema.OS_HISTOGRAM(age=int((now + i * 60 * 60 * 24) * 1000000.0))
                for number in [1, 7, 14, 30]:
                    graph = rdfvalue.Graph(title='%s day actives' % number)
                    graph.Append(label='Windows', y_value=i + number)
                    graph.Append(label='Linux', y_value=i * 2 + number)
                    histogram.Append(graph)
                fd.AddAttribute(histogram)

    def testStats(self):
        """Test the statistics interface. Unfortunately this test is pretty lame because we can not look into the canvas object with selenium."""
        self.Open('/')
        self.WaitUntil(self.IsElementPresent, 'client_query')
        self.assert_(not self.IsElementPresent('css=a[grrtarget=ReadOnlyForemanRuleTable]'))
        with self.ACLChecksDisabled():
            self.CreateAdminUser('test')
        self.Open('/')
        self.WaitUntil(self.IsElementPresent, 'client_query')
        self.WaitUntil(self.IsElementPresent, 'css=a[grrtarget=ReadOnlyForemanRuleTable]')
        self.Click("css=a:contains('Statistics')")
        self.Click('css=#_Clients ins.jstree-icon')
        self.Click('css=#_Clients-OS_20Breakdown ins.jstree-icon')
        self.WaitUntil(self.IsElementPresent, 'css=#_Clients-OS_20Breakdown-_207_20Day_20Active')
        self.Click("css=li[path='/Clients/OS Breakdown/ 7 Day Active'] a")
        self.WaitUntilEqual(u'No data Available', self.GetText, 'css=#main_rightPane h3')
        with self.ACLChecksDisabled():
            self.PopulateData()
        self.Click("css=li[path='/Clients/OS Breakdown/ 7 Day Active'] a")
        self.WaitUntilEqual(u'Operating system break down.', self.GetText, 'css=#main_rightPane h3')


Prompt:
Implement the Python class `UseCaseAdminInLine` described below.

Class description:
Implement the UseCaseAdminInLine class.

Method signatures and docstrings:
- def has_delete_permission(self, request, obj=None): Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft or rejected state
- def get_readonly_fields(self, request, obj=None): Overriding the method such that all the fields on the UseCaseAdminInline form on change form are read-only for all the users except the original author or users with 'can_edit_all' permission. Only the original author or users with 'can_edit_all' permission can edit the fields that too when the related MUOContainer is in the 'draft' state
- def get_max_num(self, request, obj=None, **kwargs): Overriding the method such that the 'Add another Use Case' option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The 'Add another UseCase' option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft state

Implement the Python class `UseCaseAdminInLine` described below.

Class description:
Implement the UseCaseAdminInLine class.

Method signatures and docstrings:
- def has_delete_permission(self, request, obj=None): Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft or rejected state
- def get_readonly_fields(self, request, obj=None): Overriding the method such that all the fields on the UseCaseAdminInline form on change form are read-only for all the users except the original author or users with 'can_edit_all' permission. Only the original author or users with 'can_edit_all' permission can edit the fields that too when the related MUOContainer is in the 'draft' state
- def get_max_num(self, request, obj=None, **kwargs): Overriding the method such that the 'Add another Use Case' option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The 'Add another UseCase' option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft state

<|skeleton|>
class UseCaseAdminInLine:

    def has_delete_permission(self, request, obj=None):
        """Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft or rejected state"""
        <|body_0|>

    def get_readonly_fields(self, request, obj=None):
        """Overriding the method such that all the fields on the UseCaseAdminInline form on change form are read-only for all the users except the original author or users with 'can_edit_all' permission. Only the original author or users with 'can_edit_all' permission can edit the fields that too when the related MUOContainer is in the 'draft' state"""
        <|body_1|>

    def get_max_num(self, request, obj=None, **kwargs):
        """Overriding the method such that the 'Add another Use Case' option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The 'Add another UseCase' option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft state"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        if obj is None:
            return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status in ('draft', 'rejected'):
            return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)
        else:
            return False
<|end_body_0|>

<|body_start_1|>
        if obj is None:
            return super(UseCaseAdminInLine, self).get_readonly_fields(request, obj)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status == 'draft':
            return super(UseCaseAdminInLine, self).get_readonly_fields(request, obj)
        else:
            return list(set([field.name for field in self.opts.local_fields] + [field.name for field in self.opts.local_many_to_many]))
<|end_body_1|>

<|body_start_2|>
        if obj is None:
            return super(UseCaseAdminInLine, self).get_max_num(request, obj=None, **kwargs)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status == 'draft':
            return super(UseCaseAdminInLine, self).get_max_num(request, obj=None, **kwargs)
        else:
            return 0
<|end_body_2|>

Solution:
class UseCaseAdminInLine:
    def has_delete_permission(self, request, obj=None):
        """Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft or rejected state"""
        if obj is None:
            return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status in ('draft', 'rejected'):
            return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)
        else:
            return False

    def get_readonly_fields(self, request, obj=None):
        """Overriding the method such that all the fields on the UseCaseAdminInline form on change form are read-only for all the users except the original author or users with 'can_edit_all' permission. Only the original author or users with 'can_edit_all' permission can edit the fields that too when the related MUOContainer is in the 'draft' state"""
        if obj is None:
            return super(UseCaseAdminInLine, self).get_readonly_fields(request, obj)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status == 'draft':
            return super(UseCaseAdminInLine, self).get_readonly_fields(request, obj)
        else:
            return list(set([field.name for field in self.opts.local_fields] + [field.name for field in self.opts.local_many_to_many]))

    def get_max_num(self, request, obj=None, **kwargs):
        """Overriding the method such that the 'Add another Use Case' option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The 'Add another UseCase' option is only available to the original author or users with 'can_edit_all' permission if the related MUOContainer is in draft state"""
        if obj is None:
            return super(UseCaseAdminInLine, self).get_max_num(request, obj=None, **kwargs)
        elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status == 'draft':
            return super(UseCaseAdminInLine, self).get_max_num(request, obj=None, **kwargs)
        else:
            return 0


Prompt:
Implement the Python class `TestShipmentMigration` described below.

Class description:
Test data migration for the "SalesOrderShipment" model.

Method signatures and docstrings:
- def prepare(self): Create an initial SalesOrder.
- def test_shipment_creation(self): Check that a SalesOrderShipment has been created.

Implement the Python class `TestShipmentMigration` described below.

Class description:
Test data migration for the "SalesOrderShipment" model.

Method signatures and docstrings:
- def prepare(self): Create an initial SalesOrder.
- def test_shipment_creation(self): Check that a SalesOrderShipment has been created.

<|skeleton|>
class TestShipmentMigration:
    """Test data migration for the "SalesOrderShipment" model."""

    def prepare(self):
        """Create an initial SalesOrder."""
        <|body_0|>

    def test_shipment_creation(self):
        """Check that a SalesOrderShipment has been created."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        Company = self.old_state.apps.get_model('company', 'company')
        customer = Company.objects.create(name='My customer', description='A customer we sell stuff too', is_customer=True)
        SalesOrder = self.old_state.apps.get_model('order', 'salesorder')
        for ii in range(5):
            order = SalesOrder.objects.create(reference=f'SO{ii}', customer=customer, description='A sales order for stuffs', status=SalesOrderStatus.PENDING.value)
        order.save()
        with self.assertRaises(LookupError):
            self.old_state.apps.get_model('order', 'salesordershipment')
<|end_body_0|>

<|body_start_1|>
        SalesOrder = self.new_state.apps.get_model('order', 'salesorder')
        Shipment = self.new_state.apps.get_model('order', 'salesordershipment')
        self.assertEqual(SalesOrder.objects.count(), 5)
        self.assertEqual(Shipment.objects.count(), 5)
<|end_body_1|>

Solution:
class TestShipmentMigration:
    """Test data migration for the "SalesOrderShipment" model."""

    def prepare(self):
        """Create an initial SalesOrder."""
        Company = self.old_state.apps.get_model('company', 'company')
        customer = Company.objects.create(name='My customer', description='A customer we sell stuff too', is_customer=True)
        SalesOrder = self.old_state.apps.get_model('order', 'salesorder')
        for ii in range(5):
            order = SalesOrder.objects.create(reference=f'SO{ii}', customer=customer, description='A sales order for stuffs', status=SalesOrderStatus.PENDING.value)
        order.save()
        with self.assertRaises(LookupError):
            self.old_state.apps.get_model('order', 'salesordershipment')

    def test_shipment_creation(self):
        """Check that a SalesOrderShipment has been created."""
        SalesOrder = self.new_state.apps.get_model('order', 'salesorder')
        Shipment = self.new_state.apps.get_model('order', 'salesordershipment')
        self.assertEqual(SalesOrder.objects.count(), 5)
        self.assertEqual(Shipment.objects.count(), 5)