forward

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

Class description:
An implementation of LSTM for forecasting.

Method signatures and docstrings:
- def __init__(self, input_size, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')): Initializes a LSTM instance. Args: input_size: Input features dimension out_len: Forecasting horizon d_model: Hidden layer dimension layers: Number of LSTM layers. dropout: Fraction of neurons affected by Dropout (default=0.0). device: Device used by the model
- def forward(self, x): Forward pass for LSTM. Args: x: A tensor of shape `(batch_size, seqence_length, input_size)` Returns: output: The forecast, a tensor of shape `(batch_size, out_len, 1)`

Implement the Python class `LSTM` described below.

Class description:
An implementation of LSTM for forecasting.

Method signatures and docstrings:
- def __init__(self, input_size, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')): Initializes a LSTM instance. Args: input_size: Input features dimension out_len: Forecasting horizon d_model: Hidden layer dimension layers: Number of LSTM layers. dropout: Fraction of neurons affected by Dropout (default=0.0). device: Device used by the model
- def forward(self, x): Forward pass for LSTM. Args: x: A tensor of shape `(batch_size, seqence_length, input_size)` Returns: output: The forecast, a tensor of shape `(batch_size, out_len, 1)`

<|skeleton|>
class LSTM:
    """An implementation of LSTM for forecasting."""

    def __init__(self, input_size, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')):
        """Initializes a LSTM instance. Args: input_size: Input features dimension out_len: Forecasting horizon d_model: Hidden layer dimension layers: Number of LSTM layers. dropout: Fraction of neurons affected by Dropout (default=0.0). device: Device used by the model"""
        <|body_0|>

    def forward(self, x):
        """Forward pass for LSTM. Args: x: A tensor of shape `(batch_size, seqence_length, input_size)` Returns: output: The forecast, a tensor of shape `(batch_size, out_len, 1)`"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super(LSTM, self).__init__()
        self.hidden_size = d_model
        self.lstm = nn.LSTM(input_size=input_size, hidden_size=d_model, num_layers=layers, batch_first=True)
        self.fc1 = nn.Linear(d_model, d_model)
        self.fc2 = nn.Linear(d_model, out_len)
        self.drop_out = nn.Dropout(dropout)
        self.device = device
        self.num_layers = layers
<|end_body_0|>

<|body_start_1|>
        h_0 = Variable(torch.zeros(self.num_layers, x.size(0), self.hidden_size)).to(self.device)
        c_0 = Variable(torch.zeros(self.num_layers, x.size(0), self.hidden_size)).to(self.device)
        out, (_, _) = self.lstm(x, (h_0, c_0))
        out = self.drop_out(out)
        out = out[:, -1, :]
        out = self.fc1(out)
        output = self.fc2(out)
        return output.unsqueeze(-1)
<|end_body_1|>

Solution:
class LSTM:
    """An implementation of LSTM for forecasting."""

    def __init__(self, input_size, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')):
        """Initializes a LSTM instance. Args: input_size: Input features dimension out_len: Forecasting horizon d_model: Hidden layer dimension layers: Number of LSTM layers. dropout: Fraction of neurons affected by Dropout (default=0.0). device: Device used by the model"""
        super(LSTM, self).__init__()
        self.hidden_size = d_model
        self.lstm = nn.LSTM(input_size=input_size, hidden_size=d_model, num_layers=layers, batch_first=True)
        self.fc1 = nn.Linear(d_model, d_model)
        self.fc2 = nn.Linear(d_model, out_len)
        self.drop_out = nn.Dropout(dropout)
        self.device = device
        self.num_layers = layers

    def forward(self, x):
        """Forward pass for LSTM. Args: x: A tensor of shape `(batch_size, seqence_length, input_size)` Returns: output: The forecast, a tensor of shape `(batch_size, out_len, 1)`"""
        h_0 = Variable(torch.zeros(self.num_layers, x.size(0), self.hidden_size)).to(self.device)
        c_0 = Variable(torch.zeros(self.num_layers, x.size(0), self.hidden_size)).to(self.device)
        out, (_, _) = self.lstm(x, (h_0, c_0))
        out = self.drop_out(out)
        out = out[:, -1, :]
        out = self.fc1(out)
        output = self.fc2(out)
        return output.unsqueeze(-1)


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

Class description:
Helper to process the profile data.

Method signatures and docstrings:
- def get_user_profile_controls(channel_model, profile_oid: ObjectId, requester_oid: ObjectId, permissions: Set[ProfilePermission]) -> List[ProfileControlEntry]: Check if the requester can perform certain actions on members who have the certain profile. The **certain actions** mentioned above currently are: - Control the profile attaching status Actions are unable to perform on the users who have a higher permission level. Actions also cannot be performed on default profile. .. note:: This function is expensive because it calls ``IdentitySearcher.get_batch_user_name()``. :param channel_model: channel data of the profile :param profile_oid: OID of the profile :param requester_oid: OID of the user who requested this check :param permissions: permissions that the requester has :return: list of `ProfileControlEntry` containing the check result
- def get_channel_profiles(channel_oid: ObjectId, partial_name: Optional[str]=None) -> List[ChannelProfileEntry]: Get a list of the channel profiles in ``channel_oid``. ``partial_name`` can be a part of the profile name. :param channel_oid: channel to get the profiles :param partial_name: keyword to get the profiles :return: list of channel profiles

Implement the Python class `ProfileHelper` described below.

Class description:
Helper to process the profile data.

Method signatures and docstrings:
- def get_user_profile_controls(channel_model, profile_oid: ObjectId, requester_oid: ObjectId, permissions: Set[ProfilePermission]) -> List[ProfileControlEntry]: Check if the requester can perform certain actions on members who have the certain profile. The **certain actions** mentioned above currently are: - Control the profile attaching status Actions are unable to perform on the users who have a higher permission level. Actions also cannot be performed on default profile. .. note:: This function is expensive because it calls ``IdentitySearcher.get_batch_user_name()``. :param channel_model: channel data of the profile :param profile_oid: OID of the profile :param requester_oid: OID of the user who requested this check :param permissions: permissions that the requester has :return: list of `ProfileControlEntry` containing the check result
- def get_channel_profiles(channel_oid: ObjectId, partial_name: Optional[str]=None) -> List[ChannelProfileEntry]: Get a list of the channel profiles in ``channel_oid``. ``partial_name`` can be a part of the profile name. :param channel_oid: channel to get the profiles :param partial_name: keyword to get the profiles :return: list of channel profiles

<|skeleton|>
class ProfileHelper:
    """Helper to process the profile data."""

    def get_user_profile_controls(channel_model, profile_oid: ObjectId, requester_oid: ObjectId, permissions: Set[ProfilePermission]) -> List[ProfileControlEntry]:
        """Check if the requester can perform certain actions on members who have the certain profile. The **certain actions** mentioned above currently are: - Control the profile attaching status Actions are unable to perform on the users who have a higher permission level. Actions also cannot be performed on default profile. .. note:: This function is expensive because it calls ``IdentitySearcher.get_batch_user_name()``. :param channel_model: channel data of the profile :param profile_oid: OID of the profile :param requester_oid: OID of the user who requested this check :param permissions: permissions that the requester has :return: list of `ProfileControlEntry` containing the check result"""
        <|body_0|>

    def get_channel_profiles(channel_oid: ObjectId, partial_name: Optional[str]=None) -> List[ChannelProfileEntry]:
        """Get a list of the channel profiles in ``channel_oid``. ``partial_name`` can be a part of the profile name. :param channel_oid: channel to get the profiles :param partial_name: keyword to get the profiles :return: list of channel profiles"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        ret = []
        names = IdentitySearcher.get_batch_user_name(ProfileManager.get_profile_user_oids(profile_oid), channel_model)
        perm_dict = ProfileManager.get_user_permission_lv_dict(channel_model.id)
        remove_self = ProfilePermission.PRF_CONTROL_SELF in permissions
        remove_member = ProfilePermission.PRF_CONTROL_MEMBER in permissions
        is_default = channel_model.config.default_profile_oid == profile_oid
        user_perm_lv = perm_dict.get(requester_oid, PermissionLevel.lowest())
        for uid, name in sorted(names.items(), key=lambda item: item[1]):
            if not name:
                name = str(uid)
            controllable = False
            if not is_default and user_perm_lv >= perm_dict.get(uid, PermissionLevel.lowest()):
                controllable = remove_self if uid == requester_oid else remove_member
            ret.append(ProfileControlEntry(root_oid=uid, name=name, controllable=controllable))
        return ret
<|end_body_0|>

<|body_start_1|>
        ret = []
        profs = list(ProfileManager.get_channel_profiles(channel_oid, partial_name))
        if not profs:
            return ret
        channel_model = ChannelManager.get_channel_oid(channel_oid)
        if not channel_model:
            return ret
        user_oids_dict = ProfileManager.get_profiles_user_oids([prof.id for prof in profs])
        user_oids = []
        for _, onplat_oids in user_oids_dict.items():
            user_oids.extend(onplat_oids)
        user_names = IdentitySearcher.get_batch_user_name(user_oids, channel_model)
        for prof in profs:
            uids = user_oids_dict.get(prof.id, [])
            ret.append(ChannelProfileEntry(prof, [user_names.get(uid) for uid in uids]))
        return ret
<|end_body_1|>

Solution:
class ProfileHelper:
    """Helper to process the profile data."""

    def get_user_profile_controls(channel_model, profile_oid: ObjectId, requester_oid: ObjectId, permissions: Set[ProfilePermission]) -> List[ProfileControlEntry]:
        """Check if the requester can perform certain actions on members who have the certain profile. The **certain actions** mentioned above currently are: - Control the profile attaching status Actions are unable to perform on the users who have a higher permission level. Actions also cannot be performed on default profile. .. note:: This function is expensive because it calls ``IdentitySearcher.get_batch_user_name()``. :param channel_model: channel data of the profile :param profile_oid: OID of the profile :param requester_oid: OID of the user who requested this check :param permissions: permissions that the requester has :return: list of `ProfileControlEntry` containing the check result"""
        ret = []
        names = IdentitySearcher.get_batch_user_name(ProfileManager.get_profile_user_oids(profile_oid), channel_model)
        perm_dict = ProfileManager.get_user_permission_lv_dict(channel_model.id)
        remove_self = ProfilePermission.PRF_CONTROL_SELF in permissions
        remove_member = ProfilePermission.PRF_CONTROL_MEMBER in permissions
        is_default = channel_model.config.default_profile_oid == profile_oid
        user_perm_lv = perm_dict.get(requester_oid, PermissionLevel.lowest())
        for uid, name in sorted(names.items(), key=lambda item: item[1]):
            if not name:
                name = str(uid)
            controllable = False
            if not is_default and user_perm_lv >= perm_dict.get(uid, PermissionLevel.lowest()):
                controllable = remove_self if uid == requester_oid else remove_member
            ret.append(ProfileControlEntry(root_oid=uid, name=name, controllable=controllable))
        return ret

    def get_channel_profiles(channel_oid: ObjectId, partial_name: Optional[str]=None) -> List[ChannelProfileEntry]:
        """Get a list of the channel profiles in ``channel_oid``. ``partial_name`` can be a part of the profile name. :param channel_oid: channel to get the profiles :param partial_name: keyword to get the profiles :return: list of channel profiles"""
        ret = []
        profs = list(ProfileManager.get_channel_profiles(channel_oid, partial_name))
        if not profs:
            return ret
        channel_model = ChannelManager.get_channel_oid(channel_oid)
        if not channel_model:
            return ret
        user_oids_dict = ProfileManager.get_profiles_user_oids([prof.id for prof in profs])
        user_oids = []
        for _, onplat_oids in user_oids_dict.items():
            user_oids.extend(onplat_oids)
        user_names = IdentitySearcher.get_batch_user_name(user_oids, channel_model)
        for prof in profs:
            uids = user_oids_dict.get(prof.id, [])
            ret.append(ChannelProfileEntry(prof, [user_names.get(uid) for uid in uids]))
        return ret


checkInclusion

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach5 but use Counter: HashTable + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach5: Array + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach5 but use Counter: HashTable + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach5: Array + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)

<|skeleton|>
class Solution:

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE"""
        <|body_0|>

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)"""
        <|body_1|>

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach5 but use Counter: HashTable + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)"""
        <|body_2|>

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach5: Array + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        s1 = sorted(s1)
        window_sz = len(s1)
        for i in range(len(s2) - window_sz + 1):
            sub_s2 = sorted(s2[i:i + window_sz])
            if s1 == sub_s2:
                return True
        return False
<|end_body_0|>

<|body_start_1|>
        counter1 = Counter(s1)
        window_sz = len(s1)
        for i in range(len(s2) - window_sz + 1):
            counter2 = Counter(s2[i:i + window_sz])
            if counter1 == counter2:
                return True
        return False
<|end_body_1|>

<|body_start_2|>
        counter1 = Counter(s1)
        window_sz = len(s1)
        counter2 = Counter(s2[:window_sz])
        if counter1 == counter2:
            return True
        for i in range(1, len(s2) - window_sz + 1):
            counter2[s2[i - 1]] -= 1
            if counter2[s2[i - 1]] <= 0:
                del counter2[s2[i - 1]]
            counter2[s2[i + window_sz - 1]] += 1
            if counter1 == counter2:
                return True
        return False
<|end_body_2|>

<|body_start_3|>
        if len(s1) > len(s2):
            return False
        window_sz = len(s1)
        counter1, counter2 = ([0] * 26, [0] * 26)
        for i in range(window_sz):
            counter1[ord(s1[i]) - ord('a')] += 1
            counter2[ord(s2[i]) - ord('a')] += 1
        if counter1 == counter2:
            return True
        for i in range(1, len(s2) - window_sz + 1):
            counter2[ord(s2[i - 1]) - ord('a')] -= 1
            counter2[ord(s2[i + window_sz - 1]) - ord('a')] += 1
            if counter1 == counter2:
                return True
        return False
<|end_body_3|>

Solution:
class Solution:
    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE"""
        s1 = sorted(s1)
        window_sz = len(s1)
        for i in range(len(s2) - window_sz + 1):
            sub_s2 = sorted(s2[i:i + window_sz])
            if s1 == sub_s2:
                return True
        return False

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)"""
        counter1 = Counter(s1)
        window_sz = len(s1)
        for i in range(len(s2) - window_sz + 1):
            counter2 = Counter(s2[i:i + window_sz])
            if counter1 == counter2:
                return True
        return False

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach5 but use Counter: HashTable + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)"""
        counter1 = Counter(s1)
        window_sz = len(s1)
        counter2 = Counter(s2[:window_sz])
        if counter1 == counter2:
            return True
        for i in range(1, len(s2) - window_sz + 1):
            counter2[s2[i - 1]] -= 1
            if counter2[s2[i - 1]] <= 0:
                del counter2[s2[i - 1]]
            counter2[s2[i + window_sz - 1]] += 1
            if counter1 == counter2:
                return True
        return False

    def checkInclusion(self, s1: str, s2: str) -> bool:
        """Approach5: Array + Sliding Window, Time: O(l1+(l2-l1)), Space: O(1)"""
        if len(s1) > len(s2):
            return False
        window_sz = len(s1)
        counter1, counter2 = ([0] * 26, [0] * 26)
        for i in range(window_sz):
            counter1[ord(s1[i]) - ord('a')] += 1
            counter2[ord(s2[i]) - ord('a')] += 1
        if counter1 == counter2:
            return True
        for i in range(1, len(s2) - window_sz + 1):
            counter2[ord(s2[i - 1]) - ord('a')] -= 1
            counter2[ord(s2[i + window_sz - 1]) - ord('a')] += 1
            if counter1 == counter2:
                return True
        return False


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

Class description:
Manage config from command given to sentinel

Method signatures and docstrings:
- def create_config(cls, logger=None, **kwargs): Create the config
- def swarm_consul_gen_config(logger=None, **kwargs): Generate SwarmNodeConfig from command given to sentinel

Implement the Python class `ConfigManager` described below.

Class description:
Manage config from command given to sentinel

Method signatures and docstrings:
- def create_config(cls, logger=None, **kwargs): Create the config
- def swarm_consul_gen_config(logger=None, **kwargs): Generate SwarmNodeConfig from command given to sentinel

<|skeleton|>
class ConfigManager:
    """Manage config from command given to sentinel"""

    def create_config(cls, logger=None, **kwargs):
        """Create the config"""
        <|body_0|>

    def swarm_consul_gen_config(logger=None, **kwargs):
        """Generate SwarmNodeConfig from command given to sentinel"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        orchestrator = None
        backend = 'consul'
        if kwargs.get('--orchestrator'):
            orchestrator = kwargs['--orchestrator']
        if kwargs.get('--backend'):
            backend = kwargs['--backend']
        if not orchestrator or not backend:
            logger.error('Orchestrator and backend need to be specified')
            sys.exit(1)
        try:
            getattr(cls, '%s_%s_gen_config' % (orchestrator, backend))(**kwargs)
        except AttributeError:
            logger.error("No method to configure orchestrator '%s' with backend '%s'", orchestrator, backend)
            sys.exit(1)
<|end_body_0|>

<|body_start_1|>
        if kwargs.get('--swarm-managers-hostname'):
            swarm_config = SwarmNodesConfig(managers_hostname=kwargs['--swarm-managers-hostname'], workers_hostname=kwargs['--swarm-workers-hostname'] if '--swarm-workers-hostname' in kwargs else [], bootstrap_address=kwargs['--bootstrap-address'] if '--bootstrap-address' in kwargs else None, domain=kwargs['--domain'] if '--domain' in kwargs else 'docker.local', deployment_type=kwargs['--deployment-type'] if '--deployment-type' in kwargs else 'swarmservices')
        else:
            logger.error('Create config failed : swarm managers hostname need to be specified with parameter "--swarm-managers-hostname"')
            sys.exit(1)
        swarm_config.generate()
<|end_body_1|>

Solution:
class ConfigManager:
    """Manage config from command given to sentinel"""

    def create_config(cls, logger=None, **kwargs):
        """Create the config"""
        orchestrator = None
        backend = 'consul'
        if kwargs.get('--orchestrator'):
            orchestrator = kwargs['--orchestrator']
        if kwargs.get('--backend'):
            backend = kwargs['--backend']
        if not orchestrator or not backend:
            logger.error('Orchestrator and backend need to be specified')
            sys.exit(1)
        try:
            getattr(cls, '%s_%s_gen_config' % (orchestrator, backend))(**kwargs)
        except AttributeError:
            logger.error("No method to configure orchestrator '%s' with backend '%s'", orchestrator, backend)
            sys.exit(1)

    def swarm_consul_gen_config(logger=None, **kwargs):
        """Generate SwarmNodeConfig from command given to sentinel"""
        if kwargs.get('--swarm-managers-hostname'):
            swarm_config = SwarmNodesConfig(managers_hostname=kwargs['--swarm-managers-hostname'], workers_hostname=kwargs['--swarm-workers-hostname'] if '--swarm-workers-hostname' in kwargs else [], bootstrap_address=kwargs['--bootstrap-address'] if '--bootstrap-address' in kwargs else None, domain=kwargs['--domain'] if '--domain' in kwargs else 'docker.local', deployment_type=kwargs['--deployment-type'] if '--deployment-type' in kwargs else 'swarmservices')
        else:
            logger.error('Create config failed : swarm managers hostname need to be specified with parameter "--swarm-managers-hostname"')
            sys.exit(1)
        swarm_config.generate()


revert

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

Class description:
Task to plumb a VIP.

Method signatures and docstrings:
- def execute(self, loadbalancer, amphora, subnet): Plumb a vip to an amphora.
- def revert(self, result, loadbalancer, amphora, subnet, *args, **kwargs): Handle a failure to plumb a vip.

Implement the Python class `PlugVIPAmphora` described below.

Class description:
Task to plumb a VIP.

Method signatures and docstrings:
- def execute(self, loadbalancer, amphora, subnet): Plumb a vip to an amphora.
- def revert(self, result, loadbalancer, amphora, subnet, *args, **kwargs): Handle a failure to plumb a vip.

<|skeleton|>
class PlugVIPAmphora:
    """Task to plumb a VIP."""

    def execute(self, loadbalancer, amphora, subnet):
        """Plumb a vip to an amphora."""
        <|body_0|>

    def revert(self, result, loadbalancer, amphora, subnet, *args, **kwargs):
        """Handle a failure to plumb a vip."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        LOG.debug('Plumbing VIP for amphora id: %s', amphora.get(constants.ID))
        session = db_apis.get_session()
        with session.begin():
            db_amp = self.amphora_repo.get(session, id=amphora.get(constants.ID))
            db_subnet = self.network_driver.get_subnet(subnet[constants.ID])
            db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
        amp_data = self.network_driver.plug_aap_port(db_lb, db_lb.vip, db_amp, db_subnet)
        return amp_data.to_dict()
<|end_body_0|>

<|body_start_1|>
        if isinstance(result, failure.Failure):
            return
        LOG.warning('Unable to plug VIP for amphora id %s load balancer id %s', amphora.get(constants.ID), loadbalancer[constants.LOADBALANCER_ID])
        try:
            session = db_apis.get_session()
            with session.begin():
                db_amp = self.amphora_repo.get(session, id=amphora.get(constants.ID))
                db_amp.vrrp_port_id = result[constants.VRRP_PORT_ID]
                db_amp.ha_port_id = result[constants.HA_PORT_ID]
                db_subnet = self.network_driver.get_subnet(subnet[constants.ID])
                db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
            self.network_driver.unplug_aap_port(db_lb.vip, db_amp, db_subnet)
        except Exception as e:
            LOG.error('Failed to unplug AAP port. Resources may still be in use for VIP: %s due to error: %s', db_lb.vip, str(e))
<|end_body_1|>

Solution:
class PlugVIPAmphora:
    """Task to plumb a VIP."""

    def execute(self, loadbalancer, amphora, subnet):
        """Plumb a vip to an amphora."""
        LOG.debug('Plumbing VIP for amphora id: %s', amphora.get(constants.ID))
        session = db_apis.get_session()
        with session.begin():
            db_amp = self.amphora_repo.get(session, id=amphora.get(constants.ID))
            db_subnet = self.network_driver.get_subnet(subnet[constants.ID])
            db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
        amp_data = self.network_driver.plug_aap_port(db_lb, db_lb.vip, db_amp, db_subnet)
        return amp_data.to_dict()

    def revert(self, result, loadbalancer, amphora, subnet, *args, **kwargs):
        """Handle a failure to plumb a vip."""
        if isinstance(result, failure.Failure):
            return
        LOG.warning('Unable to plug VIP for amphora id %s load balancer id %s', amphora.get(constants.ID), loadbalancer[constants.LOADBALANCER_ID])
        try:
            session = db_apis.get_session()
            with session.begin():
                db_amp = self.amphora_repo.get(session, id=amphora.get(constants.ID))
                db_amp.vrrp_port_id = result[constants.VRRP_PORT_ID]
                db_amp.ha_port_id = result[constants.HA_PORT_ID]
                db_subnet = self.network_driver.get_subnet(subnet[constants.ID])
                db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
            self.network_driver.unplug_aap_port(db_lb.vip, db_amp, db_subnet)
        except Exception as e:
            LOG.error('Failed to unplug AAP port. Resources may still be in use for VIP: %s due to error: %s', db_lb.vip, str(e))


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

Class description:
Dog repository class.

Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize dog repository.
- def read_dogs_of_owner(self, owner_id): Get dogs associated with this user_id.

Implement the Python class `DogRepository` described below.

Class description:
Dog repository class.

Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize dog repository.
- def read_dogs_of_owner(self, owner_id): Get dogs associated with this user_id.

<|skeleton|>
class DogRepository:
    """Dog repository class."""

    def __init__(self, dog_owner_repository):
        """Initialize dog repository."""
        <|body_0|>

    def read_dogs_of_owner(self, owner_id):
        """Get dogs associated with this user_id."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        model = Dog
        name = 'Dogs'
        super().__init__(model=model, collection_name=name)
        self.__dog_owner_repository = dog_owner_repository
<|end_body_0|>

<|body_start_1|>
        dogs = list()
        owners = self.__dog_owner_repository.search(f'owner_id=={owner_id}')
        for dog_owner in owners.to_list():
            try:
                dog = self.read(dog_owner.dog_id)
                dogs.append(dog)
            except NotFoundError:
                pass
        return dogs
<|end_body_1|>

Solution:
class DogRepository:
    """Dog repository class."""

    def __init__(self, dog_owner_repository):
        """Initialize dog repository."""
        model = Dog
        name = 'Dogs'
        super().__init__(model=model, collection_name=name)
        self.__dog_owner_repository = dog_owner_repository

    def read_dogs_of_owner(self, owner_id):
        """Get dogs associated with this user_id."""
        dogs = list()
        owners = self.__dog_owner_repository.search(f'owner_id=={owner_id}')
        for dog_owner in owners.to_list():
            try:
                dog = self.read(dog_owner.dog_id)
                dogs.append(dog)
            except NotFoundError:
                pass
        return dogs


contains

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

Class description:
Implement the BinarySearchTree class.

Method signatures and docstrings:
- def add(self, value): Adds node to a tree and places it dependent upon the rest of the tree
- def contains(self, value): returns boolean that expresses whether or not value exists in binary tree

Implement the Python class `BinarySearchTree` described below.

Class description:
Implement the BinarySearchTree class.

Method signatures and docstrings:
- def add(self, value): Adds node to a tree and places it dependent upon the rest of the tree
- def contains(self, value): returns boolean that expresses whether or not value exists in binary tree

<|skeleton|>
class BinarySearchTree:

    def add(self, value):
        """Adds node to a tree and places it dependent upon the rest of the tree"""
        <|body_0|>

    def contains(self, value):
        """returns boolean that expresses whether or not value exists in binary tree"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        node = _Node(value)
        if self._root is None:
            self._root = node
            return
        current = self._root
        while True:
            if value < current.value:
                if not current.left:
                    current.left = node
                    return
                else:
                    current = current.left
            elif not current.right:
                current.right = node
                return
            else:
                current = current.right
<|end_body_0|>

<|body_start_1|>
        if self._root == None:
            return False
        if self._root.value == value:
            return True
        current = self._root
        while True:
            if value == current.value:
                return True
            if value > current.value:
                if current.right:
                    current = current.right
                else:
                    return False
            if value < current.value:
                if current.left:
                    current = current.left
                else:
                    return False
<|end_body_1|>

Solution:
class BinarySearchTree:
    def add(self, value):
        """Adds node to a tree and places it dependent upon the rest of the tree"""
        node = _Node(value)
        if self._root is None:
            self._root = node
            return
        current = self._root
        while True:
            if value < current.value:
                if not current.left:
                    current.left = node
                    return
                else:
                    current = current.left
            elif not current.right:
                current.right = node
                return
            else:
                current = current.right

    def contains(self, value):
        """returns boolean that expresses whether or not value exists in binary tree"""
        if self._root == None:
            return False
        if self._root.value == value:
            return True
        current = self._root
        while True:
            if value == current.value:
                return True
            if value > current.value:
                if current.right:
                    current = current.right
                else:
                    return False
            if value < current.value:
                if current.left:
                    current = current.left
                else:
                    return False


subarraySum

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def subarraySum(self, nums: List[int], k: int) -> int: 前缀和，数组长度20000 :param nums: :param k: :return:
- def subarraySum1(self, nums: List[int], k: int) -> int: 使用字典优化前缀和 :param nums: :param k: :return:

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def subarraySum(self, nums: List[int], k: int) -> int: 前缀和，数组长度20000 :param nums: :param k: :return:
- def subarraySum1(self, nums: List[int], k: int) -> int: 使用字典优化前缀和 :param nums: :param k: :return:

<|skeleton|>
class Solution:

    def subarraySum(self, nums: List[int], k: int) -> int:
        """前缀和，数组长度20000 :param nums: :param k: :return:"""
        <|body_0|>

    def subarraySum1(self, nums: List[int], k: int) -> int:
        """使用字典优化前缀和 :param nums: :param k: :return:"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        sums = [0] * (len(nums) + 1)
        for i in range(len(nums)):
            sums[i + 1] = nums[i] + sums[i]
        res = 0
        for i in range(1, len(nums) + 1):
            for j in range(i):
                if sums[i] - sums[j] == k:
                    res += 1
        return res
<|end_body_0|>

<|body_start_1|>
        pre_sum_freq = dict()
        pre_sum_freq[0] = 1
        pre_sum = 0
        count = 0
        for num in nums:
            pre_sum += num
            count += pre_sum_freq.get(pre_sum - k, 0)
            pre_sum_freq[pre_sum] = pre_sum_freq.get(pre_sum, 0) + 1
        return count
<|end_body_1|>

Solution:
class Solution:
    def subarraySum(self, nums: List[int], k: int) -> int:
        """前缀和，数组长度20000 :param nums: :param k: :return:"""
        sums = [0] * (len(nums) + 1)
        for i in range(len(nums)):
            sums[i + 1] = nums[i] + sums[i]
        res = 0
        for i in range(1, len(nums) + 1):
            for j in range(i):
                if sums[i] - sums[j] == k:
                    res += 1
        return res

    def subarraySum1(self, nums: List[int], k: int) -> int:
        """使用字典优化前缀和 :param nums: :param k: :return:"""
        pre_sum_freq = dict()
        pre_sum_freq[0] = 1
        pre_sum = 0
        count = 0
        for num in nums:
            pre_sum += num
            count += pre_sum_freq.get(pre_sum - k, 0)
            pre_sum_freq[pre_sum] = pre_sum_freq.get(pre_sum, 0) + 1
        return count


maxProfit

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def maxProfitDpPattern(self, prices): :type prices: List[int] :rtype: int
- def maxProfitDpPattern2(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int f[k, ii] represents the max profit up until prices[ii] (Note: NOT ending with prices[ii]) using at most k transactions. f[k, ii] = max(f[k, ii-1], prices[ii] - prices[jj] + f[k-1, jj]) { jj in range of [0, ii-1] } = max(f[k, ii-1], prices[ii] + max(f[k-1, jj] - prices[jj])) f[0, ii] = 0; 0 times transation makes 0 profit f[k, 0] = 0; if there is only one price data point you can't make any money no matter how many times you can trade
- def maxProfitO1Space(self, prices): :type prices: List[int] :rtype: int The transition relation is constructed by the following four equations. Actually, sell2 is the only state we record for iterations. The others are intermediate states. buy1 and *sell1 *are for the first transaction. buy2 and *sell2 *are for the second transaction. Transition relation: buy1[i] = max( - prices[i], buy1[i - 1]) sell1[i] = max(buy1[i - 1] + price[i], sell1[i - 1]) buy2[i] = max( sell1[i -1] - prices[i], buy2[i - 1]) sell2[i] = max(buy2[i - 1] + price[i], sell2[i - 1])

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def maxProfitDpPattern(self, prices): :type prices: List[int] :rtype: int
- def maxProfitDpPattern2(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int f[k, ii] represents the max profit up until prices[ii] (Note: NOT ending with prices[ii]) using at most k transactions. f[k, ii] = max(f[k, ii-1], prices[ii] - prices[jj] + f[k-1, jj]) { jj in range of [0, ii-1] } = max(f[k, ii-1], prices[ii] + max(f[k-1, jj] - prices[jj])) f[0, ii] = 0; 0 times transation makes 0 profit f[k, 0] = 0; if there is only one price data point you can't make any money no matter how many times you can trade
- def maxProfitO1Space(self, prices): :type prices: List[int] :rtype: int The transition relation is constructed by the following four equations. Actually, sell2 is the only state we record for iterations. The others are intermediate states. buy1 and *sell1 *are for the first transaction. buy2 and *sell2 *are for the second transaction. Transition relation: buy1[i] = max( - prices[i], buy1[i - 1]) sell1[i] = max(buy1[i - 1] + price[i], sell1[i - 1]) buy2[i] = max( sell1[i -1] - prices[i], buy2[i - 1]) sell2[i] = max(buy2[i - 1] + price[i], sell2[i - 1])

<|skeleton|>
class Solution:

    def maxProfitDpPattern(self, prices):
        """:type prices: List[int] :rtype: int"""
        <|body_0|>

    def maxProfitDpPattern2(self, prices):
        """:type prices: List[int] :rtype: int"""
        <|body_1|>

    def maxProfit(self, prices):
        """:type prices: List[int] :rtype: int f[k, ii] represents the max profit up until prices[ii] (Note: NOT ending with prices[ii]) using at most k transactions. f[k, ii] = max(f[k, ii-1], prices[ii] - prices[jj] + f[k-1, jj]) { jj in range of [0, ii-1] } = max(f[k, ii-1], prices[ii] + max(f[k-1, jj] - prices[jj])) f[0, ii] = 0; 0 times transation makes 0 profit f[k, 0] = 0; if there is only one price data point you can't make any money no matter how many times you can trade"""
        <|body_2|>

    def maxProfitO1Space(self, prices):
        """:type prices: List[int] :rtype: int The transition relation is constructed by the following four equations. Actually, sell2 is the only state we record for iterations. The others are intermediate states. buy1 and *sell1 *are for the first transaction. buy2 and *sell2 *are for the second transaction. Transition relation: buy1[i] = max( - prices[i], buy1[i - 1]) sell1[i] = max(buy1[i - 1] + price[i], sell1[i - 1]) buy2[i] = max( sell1[i -1] - prices[i], buy2[i - 1]) sell2[i] = max(buy2[i - 1] + price[i], sell2[i - 1])"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        if len(prices) <= 1:
            return 0
        K, n = (2, len(prices))
        dp = [[[0] * 2 for _ in range(K + 1)] for _ in range(len(prices))]
        for i in range(n):
            for k in range(K, 0, -1):
                if i - 1 == -1:
                    dp[i][k][0] = 0
                    dp[i][k][1] = -prices[0]
                    continue
                dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i])
                dp[i][k][1] = max(dp[i - 1][k][1], dp[i - 1][k - 1][0] - prices[i])
        return dp[n - 1][K][0]
<|end_body_0|>

<|body_start_1|>
        if len(prices) <= 1:
            return 0
        K, n = (2, len(prices))
        dp = [[0] * 2 for _ in range(K + 1)]
        dp_1 = [[0] * 2 for _ in range(K + 1)]
        dp_1[2][1] = -prices[0]
        dp_1[1][1] = -prices[0]
        for i in range(1, n):
            for k in range(K, 0, -1):
                dp[k][0] = max(dp_1[k][0], dp_1[k][1] + prices[i])
                dp[k][1] = max(dp_1[k][1], dp_1[k - 1][0] - prices[i])
            dp, dp_1 = (dp_1, dp)
        return dp_1[K][0]
<|end_body_1|>

<|body_start_2|>
        if len(prices) <= 1:
            return 0
        K = 2
        maxProf = 0
        f = [[0] * len(prices) for _ in range(K + 1)]
        for kk in range(1, K + 1):
            tmpMax = f[kk - 1][0] - prices[0]
            for ii in range(1, len(prices)):
                f[kk][ii] = max(f[kk][ii - 1], prices[ii] + tmpMax)
                tmpMax = max(tmpMax, f[kk - 1][ii] - prices[ii])
                maxProf = max(maxProf, f[kk][ii])
        return maxProf
<|end_body_2|>

<|body_start_3|>
        if len(prices) <= 1:
            return 0
        sell1, sell2 = (0, 0)
        buy1, buy2 = (-sys.maxsize, -sys.maxsize)
        for p in prices:
            buy1 = max(buy1, -p)
            sell1 = max(sell1, p + buy1)
            buy2 = max(buy2, sell1 - p)
            sell2 = max(sell2, p + buy2)
        return sell2
<|end_body_3|>

Solution:
class Solution:
    def maxProfitDpPattern(self, prices):
        """:type prices: List[int] :rtype: int"""
        if len(prices) <= 1:
            return 0
        K, n = (2, len(prices))
        dp = [[[0] * 2 for _ in range(K + 1)] for _ in range(len(prices))]
        for i in range(n):
            for k in range(K, 0, -1):
                if i - 1 == -1:
                    dp[i][k][0] = 0
                    dp[i][k][1] = -prices[0]
                    continue
                dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i])
                dp[i][k][1] = max(dp[i - 1][k][1], dp[i - 1][k - 1][0] - prices[i])
        return dp[n - 1][K][0]

    def maxProfitDpPattern2(self, prices):
        """:type prices: List[int] :rtype: int"""
        if len(prices) <= 1:
            return 0
        K, n = (2, len(prices))
        dp = [[0] * 2 for _ in range(K + 1)]
        dp_1 = [[0] * 2 for _ in range(K + 1)]
        dp_1[2][1] = -prices[0]
        dp_1[1][1] = -prices[0]
        for i in range(1, n):
            for k in range(K, 0, -1):
                dp[k][0] = max(dp_1[k][0], dp_1[k][1] + prices[i])
                dp[k][1] = max(dp_1[k][1], dp_1[k - 1][0] - prices[i])
            dp, dp_1 = (dp_1, dp)
        return dp_1[K][0]

    def maxProfit(self, prices):
        """:type prices: List[int] :rtype: int f[k, ii] represents the max profit up until prices[ii] (Note: NOT ending with prices[ii]) using at most k transactions. f[k, ii] = max(f[k, ii-1], prices[ii] - prices[jj] + f[k-1, jj]) { jj in range of [0, ii-1] } = max(f[k, ii-1], prices[ii] + max(f[k-1, jj] - prices[jj])) f[0, ii] = 0; 0 times transation makes 0 profit f[k, 0] = 0; if there is only one price data point you can't make any money no matter how many times you can trade"""
        if len(prices) <= 1:
            return 0
        K = 2
        maxProf = 0
        f = [[0] * len(prices) for _ in range(K + 1)]
        for kk in range(1, K + 1):
            tmpMax = f[kk - 1][0] - prices[0]
            for ii in range(1, len(prices)):
                f[kk][ii] = max(f[kk][ii - 1], prices[ii] + tmpMax)
                tmpMax = max(tmpMax, f[kk - 1][ii] - prices[ii])
                maxProf = max(maxProf, f[kk][ii])
        return maxProf

    def maxProfitO1Space(self, prices):
        """:type prices: List[int] :rtype: int The transition relation is constructed by the following four equations. Actually, sell2 is the only state we record for iterations. The others are intermediate states. buy1 and *sell1 *are for the first transaction. buy2 and *sell2 *are for the second transaction. Transition relation: buy1[i] = max( - prices[i], buy1[i - 1]) sell1[i] = max(buy1[i - 1] + price[i], sell1[i - 1]) buy2[i] = max( sell1[i -1] - prices[i], buy2[i - 1]) sell2[i] = max(buy2[i - 1] + price[i], sell2[i - 1])"""
        if len(prices) <= 1:
            return 0
        sell1, sell2 = (0, 0)
        buy1, buy2 = (-sys.maxsize, -sys.maxsize)
        for p in prices:
            buy1 = max(buy1, -p)
            sell1 = max(sell1, p + buy1)
            buy2 = max(buy2, sell1 - p)
            sell2 = max(sell2, p + buy2)
        return sell2


peel

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

Class description:
For sampling mathematical expressions.

Method signatures and docstrings:
- def peel(self, frac=1): Peels one (or `frac`) of an op's entropy.
- def split(self, args): Splits the entropy and op counts up.

Implement the Python class `_SampleArgs` described below.

Class description:
For sampling mathematical expressions.

Method signatures and docstrings:
- def peel(self, frac=1): Peels one (or `frac`) of an op's entropy.
- def split(self, args): Splits the entropy and op counts up.

<|skeleton|>
class _SampleArgs:
    """For sampling mathematical expressions."""

    def peel(self, frac=1):
        """Peels one (or `frac`) of an op's entropy."""
        <|body_0|>

    def split(self, args):
        """Splits the entropy and op counts up."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        entropy = frac * self.entropy / self.count
        new_sample_args = _SampleArgs(self.count, self.entropy - entropy)
        return (entropy, new_sample_args)
<|end_body_0|>

<|body_start_1|>
        non_integer_count = sum((not arg.is_Integer for arg in args))
        assert non_integer_count <= self.count - 1
        count_split = combinatorics.uniform_non_negative_integers_with_sum(len(args), self.count - 1 - non_integer_count)
        for i, arg in enumerate(args):
            if not arg.is_Integer:
                count_split[i] += 1
        if all((count == 0 for count in count_split)):
            assert self.entropy == 0
            entropies = np.zeros(len(count_split))
        else:
            entropies = np.random.dirichlet(np.maximum(1e-09, count_split)) * self.entropy
        return [_SampleArgs(op_count, entropy) for op_count, entropy in zip(count_split, entropies)]
<|end_body_1|>

Solution:
class _SampleArgs:
    """For sampling mathematical expressions."""

    def peel(self, frac=1):
        """Peels one (or `frac`) of an op's entropy."""
        entropy = frac * self.entropy / self.count
        new_sample_args = _SampleArgs(self.count, self.entropy - entropy)
        return (entropy, new_sample_args)

    def split(self, args):
        """Splits the entropy and op counts up."""
        non_integer_count = sum((not arg.is_Integer for arg in args))
        assert non_integer_count <= self.count - 1
        count_split = combinatorics.uniform_non_negative_integers_with_sum(len(args), self.count - 1 - non_integer_count)
        for i, arg in enumerate(args):
            if not arg.is_Integer:
                count_split[i] += 1
        if all((count == 0 for count in count_split)):
            assert self.entropy == 0
            entropies = np.zeros(len(count_split))
        else:
            entropies = np.random.dirichlet(np.maximum(1e-09, count_split)) * self.entropy
        return [_SampleArgs(op_count, entropy) for op_count, entropy in zip(count_split, entropies)]


publish

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

Class description:
Publishes joint states. Discovers all joints with positional sensors and publishes corresponding ROS2 messages of type [`sensor_msgs/JointState`](https://github.com/ros2/common_interfaces/blob/master/sensor_msgs/msg/JointState.msg). Args: robot (WebotsNode): Webots Robot node. jointPrefix (str): Prefix to all joint names. node (Node): ROS2 node.

Method signatures and docstrings:
- def __init__(self, robot, joint_prefix, node, frame_id='joint_states'): Initialize the position sensors and the topic.
- def publish(self): Publish the 'joint_states' topic with up to date value.

Implement the Python class `JointStatePublisher` described below.

Class description:
Publishes joint states. Discovers all joints with positional sensors and publishes corresponding ROS2 messages of type [`sensor_msgs/JointState`](https://github.com/ros2/common_interfaces/blob/master/sensor_msgs/msg/JointState.msg). Args: robot (WebotsNode): Webots Robot node. jointPrefix (str): Prefix to all joint names. node (Node): ROS2 node.

Method signatures and docstrings:
- def __init__(self, robot, joint_prefix, node, frame_id='joint_states'): Initialize the position sensors and the topic.
- def publish(self): Publish the 'joint_states' topic with up to date value.

<|skeleton|>
class JointStatePublisher:
    """Publishes joint states. Discovers all joints with positional sensors and publishes corresponding ROS2 messages of type [`sensor_msgs/JointState`](https://github.com/ros2/common_interfaces/blob/master/sensor_msgs/msg/JointState.msg). Args: robot (WebotsNode): Webots Robot node. jointPrefix (str): Prefix to all joint names. node (Node): ROS2 node."""

    def __init__(self, robot, joint_prefix, node, frame_id='joint_states'):
        """Initialize the position sensors and the topic."""
        <|body_0|>

    def publish(self):
        """Publish the 'joint_states' topic with up to date value."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.__robot = robot
        self.__frame_id = frame_id
        self.__joint_prefix = joint_prefix
        self.__node = node
        self.__sensors = []
        self.__timestep = int(robot.getBasicTimeStep())
        self.__last_joint_states = None
        self.__previous_time = 0
        self.__previous_position = []
        self.__joint_names = []
        for i in range(robot.getNumberOfDevices()):
            device = robot.getDeviceByIndex(i)
            if device.getNodeType() == Node.POSITION_SENSOR:
                motor = device.getMotor()
                name = motor.getName() if motor is not None else device.getName()
                self.__joint_names.append(name)
                self.__sensors.append(device)
                self.__previous_position.append(0)
                device.enable(self.__timestep)
        self.__publisher = self.__node.create_publisher(JointState, 'joint_states', 1)
<|end_body_0|>

<|body_start_1|>
        msg = JointState()
        msg.header.stamp = Time(seconds=self.__robot.getTime()).to_msg()
        msg.header.frame_id = self.__frame_id
        msg.name = [s + self.__joint_prefix for s in self.__joint_names]
        msg.position = []
        time_difference = self.__robot.getTime() - self.__previous_time
        for i in range(len(self.__sensors)):
            value = self.__sensors[i].getValue()
            msg.position.append(value)
            msg.velocity.append((value - self.__previous_position[i]) / time_difference if time_difference > 0 else 0.0)
            self.__previous_position[i] = value
        msg.effort = [0.0] * 6
        self.__publisher.publish(msg)
        self.__last_joint_states = msg
        self.__previous_time = self.__robot.getTime()
<|end_body_1|>

Solution:
class JointStatePublisher:
    """Publishes joint states. Discovers all joints with positional sensors and publishes corresponding ROS2 messages of type [`sensor_msgs/JointState`](https://github.com/ros2/common_interfaces/blob/master/sensor_msgs/msg/JointState.msg). Args: robot (WebotsNode): Webots Robot node. jointPrefix (str): Prefix to all joint names. node (Node): ROS2 node."""

    def __init__(self, robot, joint_prefix, node, frame_id='joint_states'):
        """Initialize the position sensors and the topic."""
        self.__robot = robot
        self.__frame_id = frame_id
        self.__joint_prefix = joint_prefix
        self.__node = node
        self.__sensors = []
        self.__timestep = int(robot.getBasicTimeStep())
        self.__last_joint_states = None
        self.__previous_time = 0
        self.__previous_position = []
        self.__joint_names = []
        for i in range(robot.getNumberOfDevices()):
            device = robot.getDeviceByIndex(i)
            if device.getNodeType() == Node.POSITION_SENSOR:
                motor = device.getMotor()
                name = motor.getName() if motor is not None else device.getName()
                self.__joint_names.append(name)
                self.__sensors.append(device)
                self.__previous_position.append(0)
                device.enable(self.__timestep)
        self.__publisher = self.__node.create_publisher(JointState, 'joint_states', 1)

    def publish(self):
        """Publish the 'joint_states' topic with up to date value."""
        msg = JointState()
        msg.header.stamp = Time(seconds=self.__robot.getTime()).to_msg()
        msg.header.frame_id = self.__frame_id
        msg.name = [s + self.__joint_prefix for s in self.__joint_names]
        msg.position = []
        time_difference = self.__robot.getTime() - self.__previous_time
        for i in range(len(self.__sensors)):
            value = self.__sensors[i].getValue()
            msg.position.append(value)
            msg.velocity.append((value - self.__previous_position[i]) / time_difference if time_difference > 0 else 0.0)
            self.__previous_position[i] = value
        msg.effort = [0.0] * 6
        self.__publisher.publish(msg)
        self.__last_joint_states = msg
        self.__previous_time = self.__robot.getTime()


DeleteOperation

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

Class description:
Manages long-running operations with an API service. When an API method normally takes long time to complete, it can be designed to return [Operation][google.longrunning.Operation] to the client, and the client can use this interface to receive the real response asynchronously by polling the operation resource, or using `google.watcher.v1.Watcher` interface to watch the response, or pass the operation resource to another API (such as Google Cloud Pub/Sub API) to receive the response. Any API service that returns long-running operations should implement the `Operations` interface so developers can have a consistent client experience.

Method signatures and docstrings:
- def GetOperation(self, request, context): Gets the latest state of a long-running operation. Clients may use this method to poll the operation result at intervals as recommended by the API service.
- def ListOperations(self, request, context): Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
- def CancelOperation(self, request, context): Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients may use [Operations.GetOperation] or other methods to check whether the cancellation succeeded or the operation completed despite cancellation.
- def DeleteOperation(self, request, context): Deletes a long-running operation. It indicates the client is no longer interested in the operation result. It does not cancel the operation.

Implement the Python class `OperationsServicer` described below.

Class description:
Manages long-running operations with an API service. When an API method normally takes long time to complete, it can be designed to return [Operation][google.longrunning.Operation] to the client, and the client can use this interface to receive the real response asynchronously by polling the operation resource, or using `google.watcher.v1.Watcher` interface to watch the response, or pass the operation resource to another API (such as Google Cloud Pub/Sub API) to receive the response. Any API service that returns long-running operations should implement the `Operations` interface so developers can have a consistent client experience.

Method signatures and docstrings:
- def GetOperation(self, request, context): Gets the latest state of a long-running operation. Clients may use this method to poll the operation result at intervals as recommended by the API service.
- def ListOperations(self, request, context): Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
- def CancelOperation(self, request, context): Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients may use [Operations.GetOperation] or other methods to check whether the cancellation succeeded or the operation completed despite cancellation.
- def DeleteOperation(self, request, context): Deletes a long-running operation. It indicates the client is no longer interested in the operation result. It does not cancel the operation.

<|skeleton|>
class OperationsServicer:
    """Manages long-running operations with an API service. When an API method normally takes long time to complete, it can be designed to return [Operation][google.longrunning.Operation] to the client, and the client can use this interface to receive the real response asynchronously by polling the operation resource, or using `google.watcher.v1.Watcher` interface to watch the response, or pass the operation resource to another API (such as Google Cloud Pub/Sub API) to receive the response. Any API service that returns long-running operations should implement the `Operations` interface so developers can have a consistent client experience."""

    def GetOperation(self, request, context):
        """Gets the latest state of a long-running operation. Clients may use this method to poll the operation result at intervals as recommended by the API service."""
        <|body_0|>

    def ListOperations(self, request, context):
        """Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`."""
        <|body_1|>

    def CancelOperation(self, request, context):
        """Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients may use [Operations.GetOperation] or other methods to check whether the cancellation succeeded or the operation completed despite cancellation."""
        <|body_2|>

    def DeleteOperation(self, request, context):
        """Deletes a long-running operation. It indicates the client is no longer interested in the operation result. It does not cancel the operation."""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')
<|end_body_0|>

<|body_start_1|>
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')
<|end_body_1|>

<|body_start_2|>
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')
<|end_body_2|>

<|body_start_3|>
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')
<|end_body_3|>

Solution:
class OperationsServicer:
    """Manages long-running operations with an API service. When an API method normally takes long time to complete, it can be designed to return [Operation][google.longrunning.Operation] to the client, and the client can use this interface to receive the real response asynchronously by polling the operation resource, or using `google.watcher.v1.Watcher` interface to watch the response, or pass the operation resource to another API (such as Google Cloud Pub/Sub API) to receive the response. Any API service that returns long-running operations should implement the `Operations` interface so developers can have a consistent client experience."""

    def GetOperation(self, request, context):
        """Gets the latest state of a long-running operation. Clients may use this method to poll the operation result at intervals as recommended by the API service."""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')

    def ListOperations(self, request, context):
        """Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`."""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')

    def CancelOperation(self, request, context):
        """Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients may use [Operations.GetOperation] or other methods to check whether the cancellation succeeded or the operation completed despite cancellation."""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')

    def DeleteOperation(self, request, context):
        """Deletes a long-running operation. It indicates the client is no longer interested in the operation result. It does not cancel the operation."""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')


totalHammingDistance

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def totalHammingDistance(self, nums: List[int]) -> int: According to the question's statement, the numbers in the input list is less than 10^9, which is less than 2^30. So for each bit of the input number, if there are k numbers with that bit as 1 while n - k numbers with that bit as 0, then they could form k * (n - k) pairs of difference for that bit, where n is the total length of the input list.
- def totalHammingDistance2(self, nums: List[int]) -> int: Same idea as the above, but turning it into char group for each bit first: 1. map('{:030b}'.format, nums) will return an iterator that turns each numbers in the input list to a 30 bits binary format string filled with leading zeros, for example: {:030b}'.format(100) = '000000000000000000000001100100'. 2. *map will make each string as a parameter to the zip function. 3. Then the zip function will take each char at the same position from each string and form a tuple, in other words, it will take all the bit at the same position from each number in the input list.

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def totalHammingDistance(self, nums: List[int]) -> int: According to the question's statement, the numbers in the input list is less than 10^9, which is less than 2^30. So for each bit of the input number, if there are k numbers with that bit as 1 while n - k numbers with that bit as 0, then they could form k * (n - k) pairs of difference for that bit, where n is the total length of the input list.
- def totalHammingDistance2(self, nums: List[int]) -> int: Same idea as the above, but turning it into char group for each bit first: 1. map('{:030b}'.format, nums) will return an iterator that turns each numbers in the input list to a 30 bits binary format string filled with leading zeros, for example: {:030b}'.format(100) = '000000000000000000000001100100'. 2. *map will make each string as a parameter to the zip function. 3. Then the zip function will take each char at the same position from each string and form a tuple, in other words, it will take all the bit at the same position from each number in the input list.

<|skeleton|>
class Solution:

    def totalHammingDistance(self, nums: List[int]) -> int:
        """According to the question's statement, the numbers in the input list is less than 10^9, which is less than 2^30. So for each bit of the input number, if there are k numbers with that bit as 1 while n - k numbers with that bit as 0, then they could form k * (n - k) pairs of difference for that bit, where n is the total length of the input list."""
        <|body_0|>

    def totalHammingDistance2(self, nums: List[int]) -> int:
        """Same idea as the above, but turning it into char group for each bit first: 1. map('{:030b}'.format, nums) will return an iterator that turns each numbers in the input list to a 30 bits binary format string filled with leading zeros, for example: {:030b}'.format(100) = '000000000000000000000001100100'. 2. *map will make each string as a parameter to the zip function. 3. Then the zip function will take each char at the same position from each string and form a tuple, in other words, it will take all the bit at the same position from each number in the input list."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        total, n = (0, len(nums))
        for currBit in range(31):
            currOnes = 0
            for num in nums:
                currOnes += num >> currBit & 1
            total += currOnes * (n - currOnes)
        return total
<|end_body_0|>

<|body_start_1|>
        total = 0
        for b in zip(*map('{:030b}'.format, nums)):
            zeros = b.count('0')
            total += zeros * (len(b) - zeros)
        return total
<|end_body_1|>

Solution:
class Solution:
    def totalHammingDistance(self, nums: List[int]) -> int:
        """According to the question's statement, the numbers in the input list is less than 10^9, which is less than 2^30. So for each bit of the input number, if there are k numbers with that bit as 1 while n - k numbers with that bit as 0, then they could form k * (n - k) pairs of difference for that bit, where n is the total length of the input list."""
        total, n = (0, len(nums))
        for currBit in range(31):
            currOnes = 0
            for num in nums:
                currOnes += num >> currBit & 1
            total += currOnes * (n - currOnes)
        return total

    def totalHammingDistance2(self, nums: List[int]) -> int:
        """Same idea as the above, but turning it into char group for each bit first: 1. map('{:030b}'.format, nums) will return an iterator that turns each numbers in the input list to a 30 bits binary format string filled with leading zeros, for example: {:030b}'.format(100) = '000000000000000000000001100100'. 2. *map will make each string as a parameter to the zip function. 3. Then the zip function will take each char at the same position from each string and form a tuple, in other words, it will take all the bit at the same position from each number in the input list."""
        total = 0
        for b in zip(*map('{:030b}'.format, nums)):
            zeros = b.count('0')
            total += zeros * (len(b) - zeros)
        return total


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

Class description:
A class for communicating with a ZMQ-based driver process using python thread for catching asynchronous driver events.

Method signatures and docstrings:
- def __init__(self, host, cmd_port, event_port): Initialize members. @param host Host string address of the driver process. @param cmd_port Port number for the driver process command port. @param event_port Port number for the driver process event port.
- def start_messaging(self, evt_callback=None): Initialize and start messaging resources for the driver process client. Initializes command socket for sending requests, and starts event thread that listens for events from the driver process independently of command request-reply.
- def stop_messaging(self): Close messaging resources for the driver process client. Close ZMQ command socket and terminate command context. Set flag to cause event thread to close event socket and context and terminate. Await event thread completion and return.
- def cmd_dvr(self, cmd, *args, **kwargs): Command a driver by request-reply messaging. Package command message and send on blocking command socket. Block on same socket to receive the reply. Return the driver reply. @param cmd The driver command identifier. @param args Positional arguments of the command. @param kwargs Keyword arguments of the command. @retval Command result.

Implement the Python class `ZmqDriverClient` described below.

Class description:
A class for communicating with a ZMQ-based driver process using python thread for catching asynchronous driver events.

Method signatures and docstrings:
- def __init__(self, host, cmd_port, event_port): Initialize members. @param host Host string address of the driver process. @param cmd_port Port number for the driver process command port. @param event_port Port number for the driver process event port.
- def start_messaging(self, evt_callback=None): Initialize and start messaging resources for the driver process client. Initializes command socket for sending requests, and starts event thread that listens for events from the driver process independently of command request-reply.
- def stop_messaging(self): Close messaging resources for the driver process client. Close ZMQ command socket and terminate command context. Set flag to cause event thread to close event socket and context and terminate. Await event thread completion and return.
- def cmd_dvr(self, cmd, *args, **kwargs): Command a driver by request-reply messaging. Package command message and send on blocking command socket. Block on same socket to receive the reply. Return the driver reply. @param cmd The driver command identifier. @param args Positional arguments of the command. @param kwargs Keyword arguments of the command. @retval Command result.

<|skeleton|>
class ZmqDriverClient:
    """A class for communicating with a ZMQ-based driver process using python thread for catching asynchronous driver events."""

    def __init__(self, host, cmd_port, event_port):
        """Initialize members. @param host Host string address of the driver process. @param cmd_port Port number for the driver process command port. @param event_port Port number for the driver process event port."""
        <|body_0|>

    def start_messaging(self, evt_callback=None):
        """Initialize and start messaging resources for the driver process client. Initializes command socket for sending requests, and starts event thread that listens for events from the driver process independently of command request-reply."""
        <|body_1|>

    def stop_messaging(self):
        """Close messaging resources for the driver process client. Close ZMQ command socket and terminate command context. Set flag to cause event thread to close event socket and context and terminate. Await event thread completion and return."""
        <|body_2|>

    def cmd_dvr(self, cmd, *args, **kwargs):
        """Command a driver by request-reply messaging. Package command message and send on blocking command socket. Block on same socket to receive the reply. Return the driver reply. @param cmd The driver command identifier. @param args Positional arguments of the command. @param kwargs Keyword arguments of the command. @retval Command result."""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        DriverClient.__init__(self)
        self.host = host
        self.cmd_port = cmd_port
        self.event_port = event_port
        self.cmd_host_string = 'tcp://%s:%i' % (self.host, self.cmd_port)
        self.event_host_string = 'tcp://%s:%i' % (self.host, self.event_port)
        self.zmq_context = None
        self.zmq_cmd_socket = None
        self.event_thread = None
        self.stop_event_thread = True
<|end_body_0|>

<|body_start_1|>
        self.zmq_context = zmq.Context()
        self.zmq_cmd_socket = self.zmq_context.socket(zmq.REQ)
        self.zmq_cmd_socket.connect(self.cmd_host_string)
        log.info('Driver client cmd socket connected to %s.' % self.cmd_host_string)
        self.evt_callback = evt_callback

        def recv_evt_messages(driver_client):
            """
                    A looping function that monitors a ZMQ SUB socket for asynchronous
                    driver events. Can be run as a thread or greenlet.
                    @param driver_client The client object that launches the thread.
                    """
            context = zmq.Context()
            sock = context.socket(zmq.SUB)
            sock.connect(driver_client.event_host_string)
            sock.setsockopt(zmq.SUBSCRIBE, '')
            log.info('Driver client event thread connected to %s.' % driver_client.event_host_string)
            driver_client.stop_event_thread = False
            while not driver_client.stop_event_thread:
                try:
                    evt = sock.recv_pyobj(flags=zmq.NOBLOCK)
                    log.debug('got event: %s' % str(evt))
                    if driver_client.evt_callback:
                        driver_client.evt_callback(evt)
                except zmq.ZMQError:
                    time.sleep(0.5)
            sock.close()
            context.term()
            log.info('Client event socket closed.')
        self.event_thread = thread.start_new_thread(recv_evt_messages, (self,))
        log.info('Driver client messaging started.')
<|end_body_1|>

<|body_start_2|>
        self.zmq_cmd_socket.close()
        self.zmq_cmd_socket = None
        self.zmq_context.term()
        self.zmq_context = None
        self.stop_event_thread = True
        self.event_thread = None
        self.evt_callback = None
        log.info('Driver client messaging closed.')
<|end_body_2|>

<|body_start_3|>
        msg = {'cmd': cmd, 'args': args, 'kwargs': kwargs}
        log.debug('Sending command %s.' % str(msg))
        while True:
            try:
                self.zmq_cmd_socket.send_pyobj(msg)
                if msg == 'stop_driver_process':
                    return 'driver stopping'
                break
            except zmq.ZMQError:
                time.sleep(0.5)
        log.debug('Awaiting reply.')
        while True:
            try:
                reply = self.zmq_cmd_socket.recv_pyobj(flags=zmq.NOBLOCK)
                break
            except zmq.ZMQError:
                time.sleep(0.5)
        log.debug('Reply: %s.' % str(reply))
        if isinstance(reply, Exception):
            raise reply
        else:
            return reply
<|end_body_3|>

Solution:
class ZmqDriverClient:
    """A class for communicating with a ZMQ-based driver process using python thread for catching asynchronous driver events."""

    def __init__(self, host, cmd_port, event_port):
        """Initialize members. @param host Host string address of the driver process. @param cmd_port Port number for the driver process command port. @param event_port Port number for the driver process event port."""
        DriverClient.__init__(self)
        self.host = host
        self.cmd_port = cmd_port
        self.event_port = event_port
        self.cmd_host_string = 'tcp://%s:%i' % (self.host, self.cmd_port)
        self.event_host_string = 'tcp://%s:%i' % (self.host, self.event_port)
        self.zmq_context = None
        self.zmq_cmd_socket = None
        self.event_thread = None
        self.stop_event_thread = True

    def start_messaging(self, evt_callback=None):
        """Initialize and start messaging resources for the driver process client. Initializes command socket for sending requests, and starts event thread that listens for events from the driver process independently of command request-reply."""
        self.zmq_context = zmq.Context()
        self.zmq_cmd_socket = self.zmq_context.socket(zmq.REQ)
        self.zmq_cmd_socket.connect(self.cmd_host_string)
        log.info('Driver client cmd socket connected to %s.' % self.cmd_host_string)
        self.evt_callback = evt_callback

        def recv_evt_messages(driver_client):
            """
                    A looping function that monitors a ZMQ SUB socket for asynchronous
                    driver events. Can be run as a thread or greenlet.
                    @param driver_client The client object that launches the thread.
                    """
            context = zmq.Context()
            sock = context.socket(zmq.SUB)
            sock.connect(driver_client.event_host_string)
            sock.setsockopt(zmq.SUBSCRIBE, '')
            log.info('Driver client event thread connected to %s.' % driver_client.event_host_string)
            driver_client.stop_event_thread = False
            while not driver_client.stop_event_thread:
                try:
                    evt = sock.recv_pyobj(flags=zmq.NOBLOCK)
                    log.debug('got event: %s' % str(evt))
                    if driver_client.evt_callback:
                        driver_client.evt_callback(evt)
                except zmq.ZMQError:
                    time.sleep(0.5)
            sock.close()
            context.term()
            log.info('Client event socket closed.')
        self.event_thread = thread.start_new_thread(recv_evt_messages, (self,))
        log.info('Driver client messaging started.')

    def stop_messaging(self):
        """Close messaging resources for the driver process client. Close ZMQ command socket and terminate command context. Set flag to cause event thread to close event socket and context and terminate. Await event thread completion and return."""
        self.zmq_cmd_socket.close()
        self.zmq_cmd_socket = None
        self.zmq_context.term()
        self.zmq_context = None
        self.stop_event_thread = True
        self.event_thread = None
        self.evt_callback = None
        log.info('Driver client messaging closed.')

    def cmd_dvr(self, cmd, *args, **kwargs):
        """Command a driver by request-reply messaging. Package command message and send on blocking command socket. Block on same socket to receive the reply. Return the driver reply. @param cmd The driver command identifier. @param args Positional arguments of the command. @param kwargs Keyword arguments of the command. @retval Command result."""
        msg = {'cmd': cmd, 'args': args, 'kwargs': kwargs}
        log.debug('Sending command %s.' % str(msg))
        while True:
            try:
                self.zmq_cmd_socket.send_pyobj(msg)
                if msg == 'stop_driver_process':
                    return 'driver stopping'
                break
            except zmq.ZMQError:
                time.sleep(0.5)
        log.debug('Awaiting reply.')
        while True:
            try:
                reply = self.zmq_cmd_socket.recv_pyobj(flags=zmq.NOBLOCK)
                break
            except zmq.ZMQError:
                time.sleep(0.5)
        log.debug('Reply: %s.' % str(reply))
        if isinstance(reply, Exception):
            raise reply
        else:
            return reply


click

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

Class description:
The advanced mouse node on Windows.

Method signatures and docstrings:
- def set_x(self, x): Set the x-coord of the mouse pointer. x: int. The new x-coord of the mouse pointer.
- def set_y(self, y): Set the y-coord of the mouse pointer. y: int. The new y-coord of the mouse pointer.
- def click(self, button='left'): Simulate a mouse click. button: ["left", "right", "middle"]. The button which will be simulated.

Implement the Python class `Mouse` described below.

Class description:
The advanced mouse node on Windows.

Method signatures and docstrings:
- def set_x(self, x): Set the x-coord of the mouse pointer. x: int. The new x-coord of the mouse pointer.
- def set_y(self, y): Set the y-coord of the mouse pointer. y: int. The new y-coord of the mouse pointer.
- def click(self, button='left'): Simulate a mouse click. button: ["left", "right", "middle"]. The button which will be simulated.

<|skeleton|>
class Mouse:
    """The advanced mouse node on Windows."""

    def set_x(self, x):
        """Set the x-coord of the mouse pointer. x: int. The new x-coord of the mouse pointer."""
        <|body_0|>

    def set_y(self, y):
        """Set the y-coord of the mouse pointer. y: int. The new y-coord of the mouse pointer."""
        <|body_1|>

    def click(self, button='left'):
        """Simulate a mouse click. button: ["left", "right", "middle"]. The button which will be simulated."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        x = self.root_node.gui.dialogs.constant_handler_ASK_INTEGER(x, title='Set Mouse Cursor Position', prompt='Please input x-coordinate:')
        y = self.get_y()
        ctypes.windll.user32.SetCursorPos(x, y)
<|end_body_0|>

<|body_start_1|>
        x = self.get_x()
        y = self.root_node.gui.dialogs.constant_handler_ASK_INTEGER(y, title='Set Mouse Cursor Position', prompt='Please input y-coordinate:')
        ctypes.windll.user32.SetCursorPos(x, y)
<|end_body_1|>

<|body_start_2|>
        button = button.upper()
        for action in ('DOWN', 'UP'):
            const = getattr(win32con, 'MOUSEEVENTF_{}{}'.format(button, action))
            ctypes.windll.user32.mouse_event(const, 0, 0, 0, 0)
<|end_body_2|>

Solution:
class Mouse:
    """The advanced mouse node on Windows."""

    def set_x(self, x):
        """Set the x-coord of the mouse pointer. x: int. The new x-coord of the mouse pointer."""
        x = self.root_node.gui.dialogs.constant_handler_ASK_INTEGER(x, title='Set Mouse Cursor Position', prompt='Please input x-coordinate:')
        y = self.get_y()
        ctypes.windll.user32.SetCursorPos(x, y)

    def set_y(self, y):
        """Set the y-coord of the mouse pointer. y: int. The new y-coord of the mouse pointer."""
        x = self.get_x()
        y = self.root_node.gui.dialogs.constant_handler_ASK_INTEGER(y, title='Set Mouse Cursor Position', prompt='Please input y-coordinate:')
        ctypes.windll.user32.SetCursorPos(x, y)

    def click(self, button='left'):
        """Simulate a mouse click. button: ["left", "right", "middle"]. The button which will be simulated."""
        button = button.upper()
        for action in ('DOWN', 'UP'):
            const = getattr(win32con, 'MOUSEEVENTF_{}{}'.format(button, action))
            ctypes.windll.user32.mouse_event(const, 0, 0, 0, 0)


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

Class description:
@brief Representa un nodo(posible estado) en el A*

Method signatures and docstrings:
- def __init__(self, row, column, target_pos, father=None): @brief Constructor @param row Fila del nodo en el mapa @param column Columna del nodo en el mapa @param target_pos Posicion del objetivo al que se desea llegar. @param father Nodo padre, None por defecto
- def __str__(self): @brief Conversor a cadena

Implement the Python class `Nodo` described below.

Class description:
@brief Representa un nodo(posible estado) en el A*

Method signatures and docstrings:
- def __init__(self, row, column, target_pos, father=None): @brief Constructor @param row Fila del nodo en el mapa @param column Columna del nodo en el mapa @param target_pos Posicion del objetivo al que se desea llegar. @param father Nodo padre, None por defecto
- def __str__(self): @brief Conversor a cadena

<|skeleton|>
class Nodo:
    """@brief Representa un nodo(posible estado) en el A*"""

    def __init__(self, row, column, target_pos, father=None):
        """@brief Constructor @param row Fila del nodo en el mapa @param column Columna del nodo en el mapa @param target_pos Posicion del objetivo al que se desea llegar. @param father Nodo padre, None por defecto"""
        <|body_0|>

    def __str__(self):
        """@brief Conversor a cadena"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.father = father
        self.row = row
        self.column = column
        self.h = distance((row, column), (target_pos[0], target_pos[1]))
        if not father:
            self.g = 0
        else:
            self.g = self.father.g + values[map[row][column]]
        self.f = self.h + self.g
<|end_body_0|>

<|body_start_1|>
        result = ''
        result += 'Fila: ' + str(self.row)
        result += ' Columna: ' + str(self.column)
        result += ' h: ' + str(self.h)
        result += ' g: ' + str(self.g)
        result += ' f: ' + str(self.f)
        return result
<|end_body_1|>

Solution:
class Nodo:
    """@brief Representa un nodo(posible estado) en el A*"""

    def __init__(self, row, column, target_pos, father=None):
        """@brief Constructor @param row Fila del nodo en el mapa @param column Columna del nodo en el mapa @param target_pos Posicion del objetivo al que se desea llegar. @param father Nodo padre, None por defecto"""
        self.father = father
        self.row = row
        self.column = column
        self.h = distance((row, column), (target_pos[0], target_pos[1]))
        if not father:
            self.g = 0
        else:
            self.g = self.father.g + values[map[row][column]]
        self.f = self.h + self.g

    def __str__(self):
        """@brief Conversor a cadena"""
        result = ''
        result += 'Fila: ' + str(self.row)
        result += ' Columna: ' + str(self.column)
        result += ' h: ' + str(self.h)
        result += ' g: ' + str(self.g)
        result += ' f: ' + str(self.f)
        return result


checkSubarraySum

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def checkSubarraySum(self, nums: List[int], k: int) -> bool: 简单前缀和，超时，O(n ** 2) :param nums: :param k: :return:
- def checkSubarraySum1(self, nums: List[int], k: int) -> bool: 前缀和 + 同余定理 (sums[j] - sums[i]) % k == 0 同理有 sums[i] % k == sums[i] % k :param nums: :param k: :return:

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def checkSubarraySum(self, nums: List[int], k: int) -> bool: 简单前缀和，超时，O(n ** 2) :param nums: :param k: :return:
- def checkSubarraySum1(self, nums: List[int], k: int) -> bool: 前缀和 + 同余定理 (sums[j] - sums[i]) % k == 0 同理有 sums[i] % k == sums[i] % k :param nums: :param k: :return:

<|skeleton|>
class Solution:

    def checkSubarraySum(self, nums: List[int], k: int) -> bool:
        """简单前缀和，超时，O(n ** 2) :param nums: :param k: :return:"""
        <|body_0|>

    def checkSubarraySum1(self, nums: List[int], k: int) -> bool:
        """前缀和 + 同余定理 (sums[j] - sums[i]) % k == 0 同理有 sums[i] % k == sums[i] % k :param nums: :param k: :return:"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        sums = [0] * (len(nums) + 1)
        for i in range(len(nums)):
            sums[i + 1] = nums[i] + sums[i]
        for i in range(len(nums) - 1):
            for j in range(i + 1, len(nums) + 1):
                if (sums[j] - sums[i]) % k == 0:
                    return True
        return False
<|end_body_0|>

<|body_start_1|>
        modes = set()
        presum = 0
        for num in nums:
            last = presum
            presum += num
            presum %= k
            if presum in modes:
                return True
            modes.add(last)
        return False
<|end_body_1|>

Solution:
class Solution:
    def checkSubarraySum(self, nums: List[int], k: int) -> bool:
        """简单前缀和，超时，O(n ** 2) :param nums: :param k: :return:"""
        sums = [0] * (len(nums) + 1)
        for i in range(len(nums)):
            sums[i + 1] = nums[i] + sums[i]
        for i in range(len(nums) - 1):
            for j in range(i + 1, len(nums) + 1):
                if (sums[j] - sums[i]) % k == 0:
                    return True
        return False

    def checkSubarraySum1(self, nums: List[int], k: int) -> bool:
        """前缀和 + 同余定理 (sums[j] - sums[i]) % k == 0 同理有 sums[i] % k == sums[i] % k :param nums: :param k: :return:"""
        modes = set()
        presum = 0
        for num in nums:
            last = presum
            presum += num
            presum %= k
            if presum in modes:
                return True
            modes.add(last)
        return False