Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
AbstractDemoPlayer.select_sound_mode | (self, sound_mode) | Select sound mode. | Select sound mode. | def select_sound_mode(self, sound_mode):
"""Select sound mode."""
self._sound_mode = sound_mode
self.schedule_update_ha_state() | [
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DemoYoutubePlayer.__init__ | (self, name, youtube_id=None, media_title=None, duration=360) | Initialize the demo device. | Initialize the demo device. | def __init__(self, name, youtube_id=None, media_title=None, duration=360):
"""Initialize the demo device."""
super().__init__(name)
self.youtube_id = youtube_id
self._media_title = media_title
self._duration = duration
self._progress = int(duration * 0.15)
self._p... | [
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DemoYoutubePlayer.media_content_id | (self) | Return the content ID of current playing media. | Return the content ID of current playing media. | def media_content_id(self):
"""Return the content ID of current playing media."""
return self.youtube_id | [
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DemoYoutubePlayer.media_content_type | (self) | Return the content type of current playing media. | Return the content type of current playing media. | def media_content_type(self):
"""Return the content type of current playing media."""
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DemoYoutubePlayer.media_duration | (self) | Return the duration of current playing media in seconds. | Return the duration of current playing media in seconds. | def media_duration(self):
"""Return the duration of current playing media in seconds."""
return self._duration | [
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DemoYoutubePlayer.media_image_url | (self) | Return the image url of current playing media. | Return the image url of current playing media. | def media_image_url(self):
"""Return the image url of current playing media."""
return f"https://img.youtube.com/vi/{self.youtube_id}/hqdefault.jpg" | [
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DemoYoutubePlayer.media_title | (self) | Return the title of current playing media. | Return the title of current playing media. | def media_title(self):
"""Return the title of current playing media."""
return self._media_title | [
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DemoYoutubePlayer.app_name | (self) | Return the current running application. | Return the current running application. | def app_name(self):
"""Return the current running application."""
return "YouTube" | [
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DemoYoutubePlayer.supported_features | (self) | Flag media player features that are supported. | Flag media player features that are supported. | def supported_features(self):
"""Flag media player features that are supported."""
return YOUTUBE_PLAYER_SUPPORT | [
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] | python | en | ['en', 'en', 'en'] | True |
DemoYoutubePlayer.media_position | (self) | Position of current playing media in seconds. | Position of current playing media in seconds. | def media_position(self):
"""Position of current playing media in seconds."""
if self._progress is None:
return None
position = self._progress
if self._player_state == STATE_PLAYING:
position += (dt_util.utcnow() - self._progress_updated_at).total_seconds()
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DemoYoutubePlayer.media_position_updated_at | (self) | When was the position of the current playing media valid.
Returns value from homeassistant.util.dt.utcnow().
| When was the position of the current playing media valid. | def media_position_updated_at(self):
"""When was the position of the current playing media valid.
Returns value from homeassistant.util.dt.utcnow().
"""
if self._player_state == STATE_PLAYING:
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DemoYoutubePlayer.play_media | (self, media_type, media_id, **kwargs) | Play a piece of media. | Play a piece of media. | def play_media(self, media_type, media_id, **kwargs):
"""Play a piece of media."""
self.youtube_id = media_id
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DemoYoutubePlayer.media_pause | (self) | Send pause command. | Send pause command. | def media_pause(self):
"""Send pause command."""
self._progress = self.media_position
self._progress_updated_at = dt_util.utcnow()
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DemoMusicPlayer.__init__ | (self) | Initialize the demo device. | Initialize the demo device. | def __init__(self):
"""Initialize the demo device."""
super().__init__("Walkman")
self._cur_track = 0
self._repeat = REPEAT_MODE_OFF | [
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DemoMusicPlayer.media_content_id | (self) | Return the content ID of current playing media. | Return the content ID of current playing media. | def media_content_id(self):
"""Return the content ID of current playing media."""
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DemoMusicPlayer.media_content_type | (self) | Return the content type of current playing media. | Return the content type of current playing media. | def media_content_type(self):
"""Return the content type of current playing media."""
return MEDIA_TYPE_MUSIC | [
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] | python | en | ['en', 'en', 'en'] | True |
DemoMusicPlayer.media_duration | (self) | Return the duration of current playing media in seconds. | Return the duration of current playing media in seconds. | def media_duration(self):
"""Return the duration of current playing media in seconds."""
return 213 | [
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DemoMusicPlayer.media_image_url | (self) | Return the image url of current playing media. | Return the image url of current playing media. | def media_image_url(self):
"""Return the image url of current playing media."""
return "https://graph.facebook.com/v2.5/107771475912710/picture?type=large" | [
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DemoMusicPlayer.media_title | (self) | Return the title of current playing media. | Return the title of current playing media. | def media_title(self):
"""Return the title of current playing media."""
return self.tracks[self._cur_track][1] if self.tracks else "" | [
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DemoMusicPlayer.media_artist | (self) | Return the artist of current playing media (Music track only). | Return the artist of current playing media (Music track only). | def media_artist(self):
"""Return the artist of current playing media (Music track only)."""
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354,
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DemoMusicPlayer.media_album_name | (self) | Return the album of current playing media (Music track only). | Return the album of current playing media (Music track only). | def media_album_name(self):
"""Return the album of current playing media (Music track only)."""
return "Bounzz" | [
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DemoMusicPlayer.media_track | (self) | Return the track number of current media (Music track only). | Return the track number of current media (Music track only). | def media_track(self):
"""Return the track number of current media (Music track only)."""
return self._cur_track + 1 | [
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DemoMusicPlayer.repeat | (self) | Return current repeat mode. | Return current repeat mode. | def repeat(self):
"""Return current repeat mode."""
return self._repeat | [
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DemoMusicPlayer.supported_features | (self) | Flag media player features that are supported. | Flag media player features that are supported. | def supported_features(self):
"""Flag media player features that are supported."""
return MUSIC_PLAYER_SUPPORT | [
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DemoMusicPlayer.media_previous_track | (self) | Send previous track command. | Send previous track command. | def media_previous_track(self):
"""Send previous track command."""
if self._cur_track > 0:
self._cur_track -= 1
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DemoMusicPlayer.media_next_track | (self) | Send next track command. | Send next track command. | def media_next_track(self):
"""Send next track command."""
if self._cur_track < len(self.tracks) - 1:
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DemoMusicPlayer.clear_playlist | (self) | Clear players playlist. | Clear players playlist. | def clear_playlist(self):
"""Clear players playlist."""
self.tracks = []
self._cur_track = 0
self._player_state = STATE_OFF
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DemoMusicPlayer.set_repeat | (self, repeat) | Enable/disable repeat mode. | Enable/disable repeat mode. | def set_repeat(self, repeat):
"""Enable/disable repeat mode."""
self._repeat = repeat
self.schedule_update_ha_state() | [
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DemoTVShowPlayer.__init__ | (self) | Initialize the demo device. | Initialize the demo device. | def __init__(self):
"""Initialize the demo device."""
super().__init__("Lounge room")
self._cur_episode = 1
self._episode_count = 13
self._source = "dvd"
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DemoTVShowPlayer.media_content_id | (self) | Return the content ID of current playing media. | Return the content ID of current playing media. | def media_content_id(self):
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DemoTVShowPlayer.media_content_type | (self) | Return the content type of current playing media. | Return the content type of current playing media. | def media_content_type(self):
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DemoTVShowPlayer.media_duration | (self) | Return the duration of current playing media in seconds. | Return the duration of current playing media in seconds. | def media_duration(self):
"""Return the duration of current playing media in seconds."""
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DemoTVShowPlayer.media_image_url | (self) | Return the image url of current playing media. | Return the image url of current playing media. | def media_image_url(self):
"""Return the image url of current playing media."""
return "https://graph.facebook.com/v2.5/HouseofCards/picture?width=400" | [
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DemoTVShowPlayer.media_title | (self) | Return the title of current playing media. | Return the title of current playing media. | def media_title(self):
"""Return the title of current playing media."""
return f"Chapter {self._cur_episode}" | [
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DemoTVShowPlayer.media_series_title | (self) | Return the series title of current playing media (TV Show only). | Return the series title of current playing media (TV Show only). | def media_series_title(self):
"""Return the series title of current playing media (TV Show only)."""
return "House of Cards" | [
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DemoTVShowPlayer.media_season | (self) | Return the season of current playing media (TV Show only). | Return the season of current playing media (TV Show only). | def media_season(self):
"""Return the season of current playing media (TV Show only)."""
return 1 | [
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DemoTVShowPlayer.media_episode | (self) | Return the episode of current playing media (TV Show only). | Return the episode of current playing media (TV Show only). | def media_episode(self):
"""Return the episode of current playing media (TV Show only)."""
return self._cur_episode | [
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DemoTVShowPlayer.app_name | (self) | Return the current running application. | Return the current running application. | def app_name(self):
"""Return the current running application."""
return "Netflix" | [
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DemoTVShowPlayer.source | (self) | Return the current input source. | Return the current input source. | def source(self):
"""Return the current input source."""
return self._source | [
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DemoTVShowPlayer.source_list | (self) | List of available sources. | List of available sources. | def source_list(self):
"""List of available sources."""
return self._source_list | [
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DemoTVShowPlayer.supported_features | (self) | Flag media player features that are supported. | Flag media player features that are supported. | def supported_features(self):
"""Flag media player features that are supported."""
return NETFLIX_PLAYER_SUPPORT | [
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37
] | python | en | ['en', 'en', 'en'] | True |
DemoTVShowPlayer.media_previous_track | (self) | Send previous track command. | Send previous track command. | def media_previous_track(self):
"""Send previous track command."""
if self._cur_episode > 1:
self._cur_episode -= 1
self.schedule_update_ha_state() | [
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DemoTVShowPlayer.media_next_track | (self) | Send next track command. | Send next track command. | def media_next_track(self):
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DemoTVShowPlayer.select_source | (self, source) | Set the input source. | Set the input source. | def select_source(self, source):
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test_form | (hass, mock_simple_nws_config) | Test we get the form. | Test we get the form. | async def test_form(hass, mock_simple_nws_config):
"""Test we get the form."""
hass.config.latitude = 35
hass.config.longitude = -90
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test_form_cannot_connect | (hass, mock_simple_nws_config) | Test we handle cannot connect error. | Test we handle cannot connect error. | async def test_form_cannot_connect(hass, mock_simple_nws_config):
"""Test we handle cannot connect error."""
mock_instance = mock_simple_nws_config.return_value
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test_form_unknown_error | (hass, mock_simple_nws_config) | Test we handle unknown error. | Test we handle unknown error. | async def test_form_unknown_error(hass, mock_simple_nws_config):
"""Test we handle unknown error."""
mock_instance = mock_simple_nws_config.return_value
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test_form_already_configured | (hass, mock_simple_nws_config) | Test we handle duplicate entries. | Test we handle duplicate entries. | async def test_form_already_configured(hass, mock_simple_nws_config):
"""Test we handle duplicate entries."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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with patch(
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ModelContainer.check_bounds | (self, theta) | Step 6 check for overlapping periods (within 2.5% arbitrarily chosen) | Step 6 check for overlapping periods (within 2.5% arbitrarily chosen) | def check_bounds(self, theta):
for ii in range(0, self.ndim):
if not (self.bounds[ii, 0] < theta[ii] < self.bounds[ii, 1]):
return False
period_storage = []
period_storage_ordered = np.zeros(len(self.ordered_planets))
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ModelContainer.log_priors_likelihood | (self, theta, return_priors=True) |
Constant term added either by dataset.model_logchi2() or gp.log_likelihood()
|
Constant term added either by dataset.model_logchi2() or gp.log_likelihood()
| def log_priors_likelihood(self, theta, return_priors=True):
log_priors = 0.00
log_likelihood = 0.00
"""
Constant term added either by dataset.model_logchi2() or gp.log_likelihood()
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icloud_bypass_setup_fixture | () | Mock component setup. | Mock component setup. | def icloud_bypass_setup_fixture():
"""Mock component setup."""
with patch("homeassistant.components.icloud.async_setup_entry", return_value=True):
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setup_platform | (hass, config, add_entities, discovery_info=None) | Set up the Tahoma covers. | Set up the Tahoma covers. | def setup_platform(hass, config, add_entities, discovery_info=None):
"""Set up the Tahoma covers."""
if discovery_info is None:
return
controller = hass.data[TAHOMA_DOMAIN]["controller"]
devices = []
for device in hass.data[TAHOMA_DOMAIN]["devices"]["cover"]:
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TahomaCover.__init__ | (self, tahoma_device, controller) | Initialize the device. | Initialize the device. | def __init__(self, tahoma_device, controller):
"""Initialize the device."""
super().__init__(tahoma_device, controller)
self._closure = 0
# 100 equals open
self._position = 100
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TahomaCover.update | (self) | Update method. | Update method. | def update(self):
"""Update method."""
self.controller.get_states([self.tahoma_device])
# For vertical covers
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TahomaCover.current_cover_position | (self) | Return current position of cover. | Return current position of cover. | def current_cover_position(self):
"""Return current position of cover."""
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TahomaCover.set_cover_position | (self, **kwargs) | Move the cover to a specific position. | Move the cover to a specific position. | def set_cover_position(self, **kwargs):
"""Move the cover to a specific position."""
if self.tahoma_device.type == "io:WindowOpenerVeluxIOComponent":
command = "setClosure"
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TahomaCover.is_closed | (self) | Return if the cover is closed. | Return if the cover is closed. | def is_closed(self):
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TahomaCover.device_class | (self) | Return the class of the device. | Return the class of the device. | def device_class(self):
"""Return the class of the device."""
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TahomaCover.device_state_attributes | (self) | Return the device state attributes. | Return the device state attributes. | def device_state_attributes(self):
"""Return the device state attributes."""
attr = {}
super_attr = super().device_state_attributes
if super_attr is not None:
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TahomaCover.icon | (self) | Return the icon to use in the frontend, if any. | Return the icon to use in the frontend, if any. | def icon(self):
"""Return the icon to use in the frontend, if any."""
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TahomaCover.open_cover | (self, **kwargs) | Open the cover. | Open the cover. | def open_cover(self, **kwargs):
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TahomaCover.close_cover | (self, **kwargs) | Close the cover. | Close the cover. | def close_cover(self, **kwargs):
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TahomaCover.stop_cover | (self, **kwargs) | Stop the cover. | Stop the cover. | def stop_cover(self, **kwargs):
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setup | (hass, base_config) | Set up the Lutron component. | Set up the Lutron component. | def setup(hass, base_config):
"""Set up the Lutron component."""
hass.data[LUTRON_BUTTONS] = []
hass.data[LUTRON_CONTROLLER] = None
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LutronDevice.__init__ | (self, area_name, lutron_device, controller) | Initialize the device. | Initialize the device. | def __init__(self, area_name, lutron_device, controller):
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LutronDevice.async_added_to_hass | (self) | Register callbacks. | Register callbacks. | async def async_added_to_hass(self):
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LutronDevice._update_callback | (self, _device, _context, _event, _params) | Run when invoked by pylutron when the device state changes. | Run when invoked by pylutron when the device state changes. | def _update_callback(self, _device, _context, _event, _params):
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LutronDevice.name | (self) | Return the name of the device. | Return the name of the device. | def name(self):
"""Return the name of the device."""
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LutronDevice.should_poll | (self) | No polling needed. | No polling needed. | def should_poll(self):
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LutronButton.__init__ | (self, hass, area_name, keypad, button) | Register callback for activity on the button. | Register callback for activity on the button. | def __init__(self, hass, area_name, keypad, button):
"""Register callback for activity on the button."""
name = f"{keypad.name}: {button.name}"
self._hass = hass
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LutronButton.button_callback | (self, button, context, event, params) | Fire an event about a button being pressed or released. | Fire an event about a button being pressed or released. | def button_callback(self, button, context, event, params):
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shift_tokens_right | (input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int) |
Shift input ids one token to the right.
|
Shift input ids one token to the right.
| def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
"""
Shift input ids one token to the right.
"""
shifted_input_ids = input_ids.new_zeros(input_ids.shape)
shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()
shifted_input_ids[:, 0] = decoder_start_t... | [
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_make_causal_mask | (input_ids_shape: torch.Size, dtype: torch.dtype, past_key_values_length: int = 0) |
Make causal mask used for bi-directional self-attention.
|
Make causal mask used for bi-directional self-attention.
| def _make_causal_mask(input_ids_shape: torch.Size, dtype: torch.dtype, past_key_values_length: int = 0):
"""
Make causal mask used for bi-directional self-attention.
"""
bsz, tgt_len = input_ids_shape
mask = torch.full((tgt_len, tgt_len), float("-inf"))
mask_cond = torch.arange(mask.size(-1))
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86,
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_expand_mask | (mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None) |
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
|
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
| def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None):
"""
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
"""
bsz, src_len = mask.size()
tgt_len = tgt_len if tgt_len is not None else src_len
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create_position_ids_from_input_ids | (input_ids, padding_idx, past_key_values_length=0) |
Replace non-padding symbols with their position numbers. Position numbers begin at padding_idx+1. Padding symbols
are ignored. This is modified from fairseq's `utils.make_positions`.
|
Replace non-padding symbols with their position numbers. Position numbers begin at padding_idx+1. Padding symbols
are ignored. This is modified from fairseq's `utils.make_positions`.
| def create_position_ids_from_input_ids(input_ids, padding_idx, past_key_values_length=0):
"""
Replace non-padding symbols with their position numbers. Position numbers begin at padding_idx+1. Padding symbols
are ignored. This is modified from fairseq's `utils.make_positions`.
"""
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M2M100SinusoidalPositionalEmbedding.get_embedding | (num_embeddings: int, embedding_dim: int, padding_idx: Optional[int] = None) |
Build sinusoidal embeddings.
This matches the implementation in tensor2tensor, but differs slightly from the description in Section 3.5 of
"Attention Is All You Need".
|
Build sinusoidal embeddings. | def get_embedding(num_embeddings: int, embedding_dim: int, padding_idx: Optional[int] = None):
"""
Build sinusoidal embeddings.
This matches the implementation in tensor2tensor, but differs slightly from the description in Section 3.5 of
"Attention Is All You Need".
"""
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M2M100SinusoidalPositionalEmbedding.create_position_ids_from_inputs_embeds | (self, inputs_embeds) |
We are provided embeddings directly. We cannot infer which are padded so just generate sequential position ids.
Args:
inputs_embeds: torch.Tensor
Returns: torch.Tensor
|
We are provided embeddings directly. We cannot infer which are padded so just generate sequential position ids. | def create_position_ids_from_inputs_embeds(self, inputs_embeds):
"""
We are provided embeddings directly. We cannot infer which are padded so just generate sequential position ids.
Args:
inputs_embeds: torch.Tensor
Returns: torch.Tensor
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M2M100Attention.forward | (
self,
hidden_states: torch.Tensor,
key_value_states: Optional[torch.Tensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
output_attentions: bool = Fal... | Input shape: Batch x Time x Channel | Input shape: Batch x Time x Channel | def forward(
self,
hidden_states: torch.Tensor,
key_value_states: Optional[torch.Tensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
output_attentions:... | [
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335,
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M2M100EncoderLayer.forward | (
self,
hidden_states: torch.Tensor,
attention_mask: torch.Tensor,
layer_head_mask: torch.Tensor,
output_attentions: bool = False,
) |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... | def forward(
self,
hidden_states: torch.Tensor,
attention_mask: torch.Tensor,
layer_head_mask: torch.Tensor,
output_attentions: bool = False,
):
"""
Args:
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404,
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M2M100DecoderLayer.forward | (
self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
encoder_hidden_states: Optional[torch.Tensor] = None,
encoder_attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
encoder_layer_head_mask... |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... | def forward(
self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
encoder_hidden_states: Optional[torch.Tensor] = None,
encoder_attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
encoder_laye... | [
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521,
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M2M100Encoder.forward | (
self,
input_ids=None,
attention_mask=None,
head_mask=None,
inputs_embeds=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
) | r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it.
Indices can be obtained using :class:`~transfor... | r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it. | def forward(
self,
input_ids=None,
attention_mask=None,
head_mask=None,
inputs_embeds=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
):
r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:... | [
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M2M100Decoder.forward | (
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encoder_attention_mask=None,
head_mask=None,
encoder_head_mask=None,
past_key_values=None,
inputs_embeds=None,
use_cache=None,
output_attentions=None,
... | r"""
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Indices can be obtained using :class:`~transfor... | r"""
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1034,
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device_reg | (hass) | Return an empty, loaded, registry. | Return an empty, loaded, registry. | def device_reg(hass):
"""Return an empty, loaded, registry."""
return mock_device_registry(hass) | [
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entity_reg | (hass) | Return an empty, loaded, registry. | Return an empty, loaded, registry. | def entity_reg(hass):
"""Return an empty, loaded, registry."""
return mock_registry(hass) | [
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calls | (hass) | Track calls to a mock service. | Track calls to a mock service. | def calls(hass):
"""Track calls to a mock service."""
return async_mock_service(hass, "test", "automation") | [
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test_get_conditions | (hass, device_reg, entity_reg) | Test we get the expected conditions from a remote. | Test we get the expected conditions from a remote. | async def test_get_conditions(hass, device_reg, entity_reg):
"""Test we get the expected conditions from a remote."""
config_entry = MockConfigEntry(domain="test", data={})
config_entry.add_to_hass(hass)
device_entry = device_reg.async_get_or_create(
config_entry_id=config_entry.entry_id,
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test_get_condition_capabilities | (hass, device_reg, entity_reg) | Test we get the expected capabilities from a remote condition. | Test we get the expected capabilities from a remote condition. | async def test_get_condition_capabilities(hass, device_reg, entity_reg):
"""Test we get the expected capabilities from a remote condition."""
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test_if_state | (hass, calls) | Test for turn_on and turn_off conditions. | Test for turn_on and turn_off conditions. | async def test_if_state(hass, calls):
"""Test for turn_on and turn_off conditions."""
platform = getattr(hass.components, f"test.{DOMAIN}")
platform.init()
assert await async_setup_component(hass, DOMAIN, {DOMAIN: {CONF_PLATFORM: "test"}})
await hass.async_block_till_done()
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test_if_fires_on_for_condition | (hass, calls) | Test for firing if condition is on with delay. | Test for firing if condition is on with delay. | async def test_if_fires_on_for_condition(hass, calls):
"""Test for firing if condition is on with delay."""
point1 = dt_util.utcnow()
point2 = point1 + timedelta(seconds=10)
point3 = point2 + timedelta(seconds=10)
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test_config_entry_not_ready | (
hass: HomeAssistant, aioclient_mock: AiohttpClientMocker
) | Test the Elgato Key Light configuration entry not ready. | Test the Elgato Key Light configuration entry not ready. | async def test_config_entry_not_ready(
hass: HomeAssistant, aioclient_mock: AiohttpClientMocker
) -> None:
"""Test the Elgato Key Light configuration entry not ready."""
aioclient_mock.get(
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test_unload_config_entry | (
hass: HomeAssistant, aioclient_mock: AiohttpClientMocker
) | Test the Elgato Key Light configuration entry unloading. | Test the Elgato Key Light configuration entry unloading. | async def test_unload_config_entry(
hass: HomeAssistant, aioclient_mock: AiohttpClientMocker
) -> None:
"""Test the Elgato Key Light configuration entry unloading."""
entry = await init_integration(hass, aioclient_mock)
assert hass.data[DOMAIN]
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setup_platform | (hass, config, add_entities, discovery_info=None) | Set up Hikvision camera. | Set up Hikvision camera. | def setup_platform(hass, config, add_entities, discovery_info=None):
"""Set up Hikvision camera."""
host = config.get(CONF_HOST)
port = config.get(CONF_PORT)
name = config.get(CONF_NAME)
username = config.get(CONF_USERNAME)
password = config.get(CONF_PASSWORD)
try:
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HikvisionMotionSwitch.__init__ | (self, name, hikvision_cam) | Initialize the switch. | Initialize the switch. | def __init__(self, name, hikvision_cam):
"""Initialize the switch."""
self._name = name
self._hikvision_cam = hikvision_cam
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4
] | [
68,
31
] | python | en | ['en', 'en', 'en'] | True |
HikvisionMotionSwitch.name | (self) | Return the name of the device if any. | Return the name of the device if any. | def name(self):
"""Return the name of the device if any."""
return self._name | [
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] | [
71,
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] | [
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25
] | python | en | ['en', 'en', 'en'] | True |
HikvisionMotionSwitch.state | (self) | Return the state of the device if any. | Return the state of the device if any. | def state(self):
"""Return the state of the device if any."""
return self._state | [
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] | [
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] | [
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26
] | python | en | ['en', 'en', 'en'] | True |
HikvisionMotionSwitch.is_on | (self) | Return true if device is on. | Return true if device is on. | def is_on(self):
"""Return true if device is on."""
return self._state == STATE_ON | [
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] | [
83,
38
] | python | en | ['en', 'fy', 'en'] | True |
HikvisionMotionSwitch.turn_on | (self, **kwargs) | Turn the device on. | Turn the device on. | def turn_on(self, **kwargs):
"""Turn the device on."""
_LOGGING.info("Turning on Motion Detection ")
self._hikvision_cam.enable_motion_detection() | [
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HikvisionMotionSwitch.turn_off | (self, **kwargs) | Turn the device off. | Turn the device off. | def turn_off(self, **kwargs):
"""Turn the device off."""
_LOGGING.info("Turning off Motion Detection ")
self._hikvision_cam.disable_motion_detection() | [
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HikvisionMotionSwitch.update | (self) | Update Motion Detection state. | Update Motion Detection state. | def update(self):
"""Update Motion Detection state."""
enabled = self._hikvision_cam.is_motion_detection_enabled()
_LOGGING.info("enabled: %s", enabled)
self._state = STATE_ON if enabled else STATE_OFF | [
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] | python | en | ['da', 'en', 'en'] | True |
async_activate_log_queue_handler | (hass: HomeAssistant) |
Migrate the existing log handlers to use the queue.
This allows us to avoid blocking I/O and formatting messages
in the event loop as log messages are written in another thread.
|
Migrate the existing log handlers to use the queue. | def async_activate_log_queue_handler(hass: HomeAssistant) -> None:
"""
Migrate the existing log handlers to use the queue.
This allows us to avoid blocking I/O and formatting messages
in the event loop as log messages are written in another thread.
"""
simple_queue = queue.SimpleQueue() # type... | [
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... | [
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] | [
89,
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] | python | en | ['en', 'error', 'th'] | False |
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