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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
test_logbook_view_end_time_entity | (hass, hass_client) | Test the logbook view with end_time and entity. | Test the logbook view with end_time and entity. | async def test_logbook_view_end_time_entity(hass, hass_client):
"""Test the logbook view with end_time and entity."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].bloc... | [
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... | [
512,
0
] | [
567,
58
] | python | en | ['en', 'en', 'en'] | True |
test_logbook_entity_filter_with_automations | (hass, hass_client) | Test the logbook view with end_time and entity with automations and scripts. | Test the logbook view with end_time and entity with automations and scripts. | async def test_logbook_entity_filter_with_automations(hass, hass_client):
"""Test the logbook view with end_time and entity with automations and scripts."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await async_setup_component(hass,... | [
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"\"logbook\"",... | [
570,
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] | [
642,
56
] | python | en | ['en', 'en', 'en'] | True |
test_filter_continuous_sensor_values | (hass, hass_client) | Test remove continuous sensor events from logbook. | Test remove continuous sensor events from logbook. | async def test_filter_continuous_sensor_values(hass, hass_client):
"""Test remove continuous sensor events from logbook."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE... | [
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",",... | [
645,
0
] | [
678,
59
] | python | en | ['en', 'en', 'en'] | True |
test_exclude_new_entities | (hass, hass_client) | Test if events are excluded on first update. | Test if events are excluded on first update. | async def test_exclude_new_entities(hass, hass_client):
"""Test if events are excluded on first update."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block_till_done... | [
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"... | [
681,
0
] | [
713,
51
] | python | en | ['en', 'en', 'en'] | True |
test_exclude_removed_entities | (hass, hass_client) | Test if events are excluded on last update. | Test if events are excluded on last update. | async def test_exclude_removed_entities(hass, hass_client):
"""Test if events are excluded on last update."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block_till_d... | [
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"\"logbook\"",
",",
"{",... | [
716,
0
] | [
755,
54
] | python | en | ['en', 'en', 'en'] | True |
test_exclude_attribute_changes | (hass, hass_client) | Test if events of attribute changes are filtered. | Test if events of attribute changes are filtered. | async def test_exclude_attribute_changes(hass, hass_client):
"""Test if events of attribute changes are filtered."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block... | [
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"\"logbook\"",
",",
"{"... | [
758,
0
] | [
793,
59
] | python | en | ['en', 'en', 'en'] | True |
test_logbook_entity_context_id | (hass, hass_client) | Test the logbook view with end_time and entity with automations and scripts. | Test the logbook view with end_time and entity with automations and scripts. | async def test_logbook_entity_context_id(hass, hass_client):
"""Test the logbook view with end_time and entity with automations and scripts."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await async_setup_component(hass, "automation"... | [
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"{"... | [
796,
0
] | [
945,
80
] | python | en | ['en', 'en', 'en'] | True |
test_logbook_context_from_template | (hass, hass_client) | Test the logbook view with end_time and entity with automations and scripts. | Test the logbook view with end_time and entity with automations and scripts. | async def test_logbook_context_from_template(hass, hass_client):
"""Test the logbook view with end_time and entity with automations and scripts."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
assert await async_setup_component(
... | [
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... | [
948,
0
] | [
1031,
80
] | python | en | ['en', 'en', 'en'] | True |
test_logbook_entity_matches_only | (hass, hass_client) | Test the logbook view with a single entity and entity_matches_only. | Test the logbook view with a single entity and entity_matches_only. | async def test_logbook_entity_matches_only(hass, hass_client):
"""Test the logbook view with a single entity and entity_matches_only."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
assert await async_setup_component(
hass,
... | [
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"... | [
1034,
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] | [
1105,
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] | python | en | ['en', 'en', 'en'] | True |
test_logbook_entity_matches_only_multiple | (hass, hass_client) | Test the logbook view with a multiple entities and entity_matches_only. | Test the logbook view with a multiple entities and entity_matches_only. | async def test_logbook_entity_matches_only_multiple(hass, hass_client):
"""Test the logbook view with a multiple entities and entity_matches_only."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
assert await async_setup_component(
... | [
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... | [
1108,
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] | [
1189,
80
] | python | en | ['en', 'en', 'en'] | True |
test_logbook_invalid_entity | (hass, hass_client) | Test the logbook view with requesting an invalid entity. | Test the logbook view with requesting an invalid entity. | async def test_logbook_invalid_entity(hass, hass_client):
"""Test the logbook view with requesting an invalid entity."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_block_till_done()
client = await hass_client()
... | [
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... | [
1192,
0
] | [
1208,
33
] | python | en | ['en', 'en', 'en'] | True |
test_icon_and_state | (hass, hass_client) | Test to ensure state and custom icons are returned. | Test to ensure state and custom icons are returned. | async def test_icon_and_state(hass, hass_client):
"""Test to ensure state and custom icons are returned."""
await hass.async_add_executor_job(init_recorder_component, hass)
await async_setup_component(hass, "logbook", {})
await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block_till_don... | [
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... | [
1211,
0
] | [
1246,
49
] | python | en | ['en', 'en', 'en'] | True |
test_exclude_events_domain | (hass, hass_client) | Test if events are filtered if domain is excluded in config. | Test if events are filtered if domain is excluded in config. | async def test_exclude_events_domain(hass, hass_client):
"""Test if events are filtered if domain is excluded in config."""
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
logbook.DOMAIN: {CONF_EXCLUDE: {CONF_DOMAINS: [... | [
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",",... | [
1249,
0
] | [
1280,
63
] | python | en | ['en', 'en', 'en'] | True |
test_exclude_events_domain_glob | (hass, hass_client) | Test if events are filtered if domain or glob is excluded in config. | Test if events are filtered if domain or glob is excluded in config. | async def test_exclude_events_domain_glob(hass, hass_client):
"""Test if events are filtered if domain or glob is excluded in config."""
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
entity_id3 = "sensor.excluded"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
... | [
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... | [
1283,
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] | [
1321,
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] | python | en | ['en', 'en', 'en'] | True |
test_include_events_entity | (hass, hass_client) | Test if events are filtered if entity is included in config. | Test if events are filtered if entity is included in config. | async def test_include_events_entity(hass, hass_client):
"""Test if events are filtered if entity is included in config."""
entity_id = "sensor.bla"
entity_id2 = "sensor.blu"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
logbook.DOMAIN: {
CONF_INCLUDE:... | [
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1324,
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] | [
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] | python | en | ['en', 'en', 'en'] | True |
test_exclude_events_entity | (hass, hass_client) | Test if events are filtered if entity is excluded in config. | Test if events are filtered if entity is excluded in config. | async def test_exclude_events_entity(hass, hass_client):
"""Test if events are filtered if entity is excluded in config."""
entity_id = "sensor.bla"
entity_id2 = "sensor.blu"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
logbook.DOMAIN: {CONF_EXCLUDE: {CONF_ENTITIES: ... | [
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1362,
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] | [
1391,
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] | python | en | ['en', 'en', 'en'] | True |
test_include_events_domain | (hass, hass_client) | Test if events are filtered if domain is included in config. | Test if events are filtered if domain is included in config. | async def test_include_events_domain(hass, hass_client):
"""Test if events are filtered if domain is included in config."""
assert await async_setup_component(hass, "alexa", {})
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
... | [
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test_include_events_domain_glob | (hass, hass_client) | Test if events are filtered if domain or glob is included in config. | Test if events are filtered if domain or glob is included in config. | async def test_include_events_domain_glob(hass, hass_client):
"""Test if events are filtered if domain or glob is included in config."""
assert await async_setup_component(hass, "alexa", {})
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
entity_id3 = "switch.included"
config = logbook.CONFIG... | [
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"e... | [
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] | [
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test_include_exclude_events | (hass, hass_client) | Test if events are filtered if include and exclude is configured. | Test if events are filtered if include and exclude is configured. | async def test_include_exclude_events(hass, hass_client):
"""Test if events are filtered if include and exclude is configured."""
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
entity_id3 = "sensor.bli"
entity_id4 = "sensor.keep"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMA... | [
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] | [
1529,
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] | python | en | ['en', 'en', 'en'] | True |
test_include_exclude_events_with_glob_filters | (hass, hass_client) | Test if events are filtered if include and exclude is configured. | Test if events are filtered if include and exclude is configured. | async def test_include_exclude_events_with_glob_filters(hass, hass_client):
"""Test if events are filtered if include and exclude is configured."""
entity_id = "switch.bla"
entity_id2 = "sensor.blu"
entity_id3 = "sensor.bli"
entity_id4 = "light.included"
entity_id5 = "switch.included"
entity... | [
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"entity_id5",
... | [
1532,
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] | [
1587,
68
] | python | en | ['en', 'en', 'en'] | True |
test_empty_config | (hass, hass_client) | Test we can handle an empty entity filter. | Test we can handle an empty entity filter. | async def test_empty_config(hass, hass_client):
"""Test we can handle an empty entity filter."""
entity_id = "sensor.blu"
config = logbook.CONFIG_SCHEMA(
{
ha.DOMAIN: {},
logbook.DOMAIN: {},
}
)
await hass.async_add_executor_job(init_recorder_component, hass)... | [
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1590,
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] | [
1617,
62
] | python | en | ['en', 'en', 'en'] | True |
_assert_entry | (
entry, when=None, name=None, message=None, domain=None, entity_id=None
) | Assert an entry is what is expected. | Assert an entry is what is expected. | def _assert_entry(
entry, when=None, name=None, message=None, domain=None, entity_id=None
):
"""Assert an entry is what is expected."""
if when:
assert when.isoformat() == entry["when"]
if name:
assert name == entry["name"]
if message:
assert message == entry["message"]
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... | [
1643,
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] | [
1660,
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] | python | en | ['en', 'en', 'en'] | True |
MockLazyEventPartialState.data_entity_id | (self) | Lookup entity id. | Lookup entity id. | def data_entity_id(self):
"""Lookup entity id."""
return self.data.get(ATTR_ENTITY_ID) | [
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] | [
1669,
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] | python | en | ['en', 'so', 'en'] | True |
MockLazyEventPartialState.data_domain | (self) | Lookup domain. | Lookup domain. | def data_domain(self):
"""Lookup domain."""
return self.data.get(ATTR_DOMAIN) | [
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MockLazyEventPartialState.time_fired_minute | (self) | Minute the event was fired. | Minute the event was fired. | def time_fired_minute(self):
"""Minute the event was fired."""
return self.time_fired.minute | [
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MockLazyEventPartialState.context_user_id | (self) | Context user id of event. | Context user id of event. | def context_user_id(self):
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MockLazyEventPartialState.context_id | (self) | Context id of event. | Context id of event. | def context_id(self):
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MockLazyEventPartialState.time_fired_isoformat | (self) | Time event was fired in utc isoformat. | Time event was fired in utc isoformat. | def time_fired_isoformat(self):
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async_setup_platform | (hass, config, async_add_entities, discovery_info=None) | Set up the updater binary sensors. | Set up the updater binary sensors. | async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
"""Set up the updater binary sensors."""
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async_add_entities([UpdaterBinary(hass.data[UPDATER_DOMAIN])]) | [
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UpdaterBinary.name | (self) | Return the name of the binary sensor, if any. | Return the name of the binary sensor, if any. | def name(self) -> str:
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UpdaterBinary.unique_id | (self) | Return a unique ID. | Return a unique ID. | def unique_id(self) -> str:
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UpdaterBinary.is_on | (self) | Return true if the binary sensor is on. | Return true if the binary sensor is on. | def is_on(self) -> bool:
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UpdaterBinary.device_state_attributes | (self) | Return the optional state attributes. | Return the optional state attributes. | def device_state_attributes(self) -> dict:
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test_form | (hass) | Test we get the form. | Test we get the form. | async def test_form(hass):
"""Test we get the form."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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assert result["type"] == "form"
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test_form_2fa | (hass) | Test we get the 2fa form. | Test we get the 2fa form. | async def test_form_2fa(hass):
"""Test we get the 2fa form."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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test_form_2fa_connect_error | (hass) | Test we report a connect error during 2fa setup. | Test we report a connect error during 2fa setup. | async def test_form_2fa_connect_error(hass):
"""Test we report a connect error during 2fa setup."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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test_form_2fa_invalid_key | (hass) | Test we report an error if key is invalid. | Test we report an error if key is invalid. | async def test_form_2fa_invalid_key(hass):
"""Test we report an error if key is invalid."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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178,
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test_form_2fa_unknown_error | (hass) | Test we report an unknown error during 2fa setup. | Test we report an unknown error during 2fa setup. | async def test_form_2fa_unknown_error(hass):
"""Test we report an unknown error during 2fa setup."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
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219,
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test_form_invalid_auth | (hass) | Test we handle invalid auth. | Test we handle invalid auth. | async def test_form_invalid_auth(hass):
"""Test we handle invalid auth."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
with patch(
"homeassistant.components.blink.config_flow.Auth.startup",
side_effect=LoginError,
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test_form_unknown_error | (hass) | Test we handle unknown error at startup. | Test we handle unknown error at startup. | async def test_form_unknown_error(hass):
"""Test we handle unknown error at startup."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
with patch(
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test_reauth_shows_user_step | (hass) | Test reauth shows the user form. | Test reauth shows the user form. | async def test_reauth_shows_user_step(hass):
"""Test reauth shows the user form."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": "reauth"}
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["step_id"] == "user" | [
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test_options_flow | (hass) | Test config flow options. | Test config flow options. | async def test_options_flow(hass):
"""Test config flow options."""
config_entry = MockConfigEntry(
domain=DOMAIN,
data={"username": "blink@example.com", "password": "example"},
options={},
entry_id=1,
version=2,
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test_get_id_empty | (hass, hass_storage) | Get unique ID. | Get unique ID. | async def test_get_id_empty(hass, hass_storage):
"""Get unique ID."""
uuid = await hass.helpers.instance_id.async_get()
assert uuid is not None
# Assert it's stored
assert hass_storage["core.uuid"]["data"]["uuid"] == uuid | [
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test_get_id_migrate | (hass, hass_storage) | Migrate existing file. | Migrate existing file. | async def test_get_id_migrate(hass, hass_storage):
"""Migrate existing file."""
with patch(
"homeassistant.util.json.load_json", return_value={"uuid": "1234"}
), patch("os.path.isfile", return_value=True), patch("os.remove") as mock_remove:
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GAG.build_net | (self, is_training) | Build the whole neural network for the QA model. | Build the whole neural network for the QA model. | def build_net(self, is_training):
"""Build the whole neural network for the QA model."""
cfg = self.cfg
with tf.device('/cpu:0'):
word_embed = tf.get_variable(
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GAG.build_char_states | (self, char_embed, is_training, reuse, char_ids, char_lengths) | Build char embedding network for the QA model. | Build char embedding network for the QA model. | def build_char_states(self, char_embed, is_training, reuse, char_ids, char_lengths):
"""Build char embedding network for the QA model."""
max_char_length = self.cfg.max_char_length
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test_setting_rising | (hass, legacy_patchable_time) | Test retrieving sun setting and rising. | Test retrieving sun setting and rising. | async def test_setting_rising(hass, legacy_patchable_time):
"""Test retrieving sun setting and rising."""
utc_now = datetime(2016, 11, 1, 8, 0, 0, tzinfo=dt_util.UTC)
with patch("homeassistant.helpers.condition.dt_util.utcnow", return_value=utc_now):
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test_state_change | (hass, legacy_patchable_time) | Test if the state changes at next setting/rising. | Test if the state changes at next setting/rising. | async def test_state_change(hass, legacy_patchable_time):
"""Test if the state changes at next setting/rising."""
now = datetime(2016, 6, 1, 8, 0, 0, tzinfo=dt_util.UTC)
with patch("homeassistant.helpers.condition.dt_util.utcnow", return_value=now):
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test_norway_in_june | (hass) | Test location in Norway where the sun doesn't set in summer. | Test location in Norway where the sun doesn't set in summer. | async def test_norway_in_june(hass):
"""Test location in Norway where the sun doesn't set in summer."""
hass.config.latitude = 69.6
hass.config.longitude = 18.8
june = datetime(2016, 6, 1, tzinfo=dt_util.UTC)
with patch("homeassistant.helpers.condition.dt_util.utcnow", return_value=june):
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test_state_change_count | (hass) | Count the number of state change events in a location. | Count the number of state change events in a location. | async def test_state_change_count(hass):
"""Count the number of state change events in a location."""
# Skipped because it's a bit slow. Has been validated with
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hass.config.latitude = 10
hass.config.longitude = 0
now = datetime(2016, 6, 1, tzinfo=dt_util.UTC)
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test_climate | (
hass: HomeAssistant, vera_component_factory: ComponentFactory
) | Test function. | Test function. | async def test_climate(
hass: HomeAssistant, vera_component_factory: ComponentFactory
) -> None:
"""Test function."""
vera_device = MagicMock(spec=pv.VeraThermostat) # type: pv.VeraThermostat
vera_device.device_id = 1
vera_device.vera_device_id = vera_device.device_id
vera_device.name = "dev1"
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test_climate_f | (
hass: HomeAssistant, vera_component_factory: ComponentFactory
) | Test function. | Test function. | async def test_climate_f(
hass: HomeAssistant, vera_component_factory: ComponentFactory
) -> None:
"""Test function."""
vera_device = MagicMock(spec=pv.VeraThermostat) # type: pv.VeraThermostat
vera_device.device_id = 1
vera_device.vera_device_id = vera_device.device_id
vera_device.name = "dev1... | [
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setup | (hass, config) | Set up the STIEBEL ELTRON unit.
Will automatically load climate platform.
| Set up the STIEBEL ELTRON unit. | def setup(hass, config):
"""Set up the STIEBEL ELTRON unit.
Will automatically load climate platform.
"""
name = config[DOMAIN][CONF_NAME]
modbus_client = hass.data[MODBUS_DOMAIN][config[DOMAIN][CONF_HUB]]
hass.data[DOMAIN] = {
"name": name,
"ste_data": StiebelEltronData(name, ... | [
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StiebelEltronData.__init__ | (self, name, modbus_client) | Init the STIEBEL ELTRON data object. | Init the STIEBEL ELTRON data object. | def __init__(self, name, modbus_client):
"""Init the STIEBEL ELTRON data object."""
self.api = pystiebeleltron.StiebelEltronAPI(modbus_client, 1) | [
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StiebelEltronData.update | (self) | Update unit data. | Update unit data. | def update(self):
"""Update unit data."""
if not self.api.update():
_LOGGER.warning("Modbus read failed")
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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)
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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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_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]`.
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bsz, src_len = mask.size()
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BlenderbotSmallLearnedPositionalEmbedding.forward | (self, input_ids_shape: torch.Size, past_key_values_length: int = 0) | `input_ids_shape` is expected to be [bsz x seqlen]. | `input_ids_shape` is expected to be [bsz x seqlen]. | def forward(self, input_ids_shape: torch.Size, past_key_values_length: int = 0):
"""`input_ids_shape` is expected to be [bsz x seqlen]."""
bsz, seq_len = input_ids_shape[:2]
positions = torch.arange(
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BlenderbotSmallAttention.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,
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264,
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BlenderbotSmallEncoderLayer.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:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed... | [
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333,
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BlenderbotSmallDecoderLayer.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,
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BlenderbotSmallEncoder.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,
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Args:
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BlenderbotSmallDecoder.forward | (
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Indices can be obtained using :class:`~transfor... | r"""
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BlenderbotSmallForCausalLM.forward | (
self,
input_ids=None,
attention_mask=None,
encoder_hidden_states=None,
encoder_attention_mask=None,
head_mask=None,
encoder_head_mask=None,
past_key_values=None,
inputs_embeds=None,
labels=None,
use_cache=None,
output_atte... | r"""
Args:
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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,
encoder_hidden_states=None,
encoder_attention_mask=None,
head_mask=None,
encoder_head_mask=None,
past_key_values=None,
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TFMobileBertEmbeddings.call | (self, input_ids=None, position_ids=None, token_type_ids=None, inputs_embeds=None, training=False) |
Applies embedding based on inputs tensor.
Returns:
final_embeddings (:obj:`tf.Tensor`): output embedding tensor.
|
Applies embedding based on inputs tensor. | def call(self, input_ids=None, position_ids=None, token_type_ids=None, inputs_embeds=None, training=False):
"""
Applies embedding based on inputs tensor.
Returns:
final_embeddings (:obj:`tf.Tensor`): output embedding tensor.
"""
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handle_metrics | (split, metrics, output_dir) |
Log and save metrics
Args:
- split: one of train, val, test
- metrics: metrics dict
- output_dir: where to save the metrics
|
Log and save metrics | def handle_metrics(split, metrics, output_dir):
"""
Log and save metrics
Args:
- split: one of train, val, test
- metrics: metrics dict
- output_dir: where to save the metrics
"""
logger.info(f"***** {split} metrics *****")
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get_optim_f_stop | (maxiter, maxtime, dftol_stop, freltol_stop,
minibatch=True) |
Check stopping conditions.
|
Check stopping conditions.
| def get_optim_f_stop(maxiter, maxtime, dftol_stop, freltol_stop,
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"""
Check stopping conditions.
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discount_factor = 1. / 3
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get_init | (data_train, init_type='on', rng=np.random.RandomState(0), prev_score=None) |
Initialize the 'x' variable with different settings
|
Initialize the 'x' variable with different settings
| def get_init(data_train, init_type='on', rng=np.random.RandomState(0), prev_score=None):
"""
Initialize the 'x' variable with different settings
"""
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get_checkpoint | (S, stop_conds, rng=None, get_state=True) |
Save the necessary information into a dictionary
|
Save the necessary information into a dictionary
| def get_checkpoint(S, stop_conds, rng=None, get_state=True):
"""
Save the necessary information into a dictionary
"""
m = {}
m['ninitfeats'] = S.ninitfeats
m['x0'] = S.x0
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_train | (data_train, Nminibatch, order, C, rng, lr_train, debug, maxiter,
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path_save, shuffle, device=constants.Device.CPU,
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prev_checkpoint=None,
groups=None,
soft_groups=None) |
Main training loop.
|
Main training loop.
| def _train(data_train, Nminibatch, order, C, rng, lr_train, debug, maxiter,
maxtime, init, dftol_stop, freltol_stop, dn_log, accum_steps,
path_save, shuffle, device=constants.Device.CPU,
verbose=1,
prev_checkpoint=None,
groups=None,
soft_groups=None):
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async_setup_platform | (hass, config, async_add_entities, discovery_info=None) | Set up the IP Webcam binary sensors. | Set up the IP Webcam binary sensors. | async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
"""Set up the IP Webcam binary sensors."""
if discovery_info is None:
return
host = discovery_info[CONF_HOST]
name = discovery_info[CONF_NAME]
ipcam = hass.data[DATA_IP_WEBCAM][host]
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IPWebcamBinarySensor.__init__ | (self, name, host, ipcam, sensor) | Initialize the binary sensor. | Initialize the binary sensor. | def __init__(self, name, host, ipcam, sensor):
"""Initialize the binary sensor."""
super().__init__(host, ipcam)
self._sensor = sensor
self._mapped_name = KEY_MAP.get(self._sensor, self._sensor)
self._name = f"{name} {self._mapped_name}"
self._state = None
self._... | [
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IPWebcamBinarySensor.name | (self) | Return the name of the binary sensor, if any. | Return the name of the binary sensor, if any. | def name(self):
"""Return the name of the binary sensor, if any."""
return self._name | [
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IPWebcamBinarySensor.is_on | (self) | Return true if the binary sensor is on. | Return true if the binary sensor is on. | def is_on(self):
"""Return true if the binary sensor is on."""
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IPWebcamBinarySensor.async_update | (self) | Retrieve latest state. | Retrieve latest state. | async def async_update(self):
"""Retrieve latest state."""
state, _ = self._ipcam.export_sensor(self._sensor)
self._state = state == 1.0 | [
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IPWebcamBinarySensor.device_class | (self) | Return the class of this device, from component DEVICE_CLASSES. | Return the class of this device, from component DEVICE_CLASSES. | def device_class(self):
"""Return the class of this device, from component DEVICE_CLASSES."""
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AbsAgent.choose_action | (self, state) | This method uses the underlying model(s) to compute an action from a shaped state.
Args:
state: A state object shaped by a ``StateShaper`` to conform to the model input format.
Returns:
The action to be taken given ``state``. It is usually necessary to use an ``ActionShaper`` t... | This method uses the underlying model(s) to compute an action from a shaped state. | def choose_action(self, state):
"""This method uses the underlying model(s) to compute an action from a shaped state.
Args:
state: A state object shaped by a ``StateShaper`` to conform to the model input format.
Returns:
The action to be taken given ``state``. It is usu... | [
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AbsAgent.learn | (self, *args, **kwargs) | Algorithm-specific training logic.
The parameters are data to train the underlying model on. Algorithm-specific loss and optimization
should be reflected here.
| Algorithm-specific training logic. | def learn(self, *args, **kwargs):
"""Algorithm-specific training logic.
The parameters are data to train the underlying model on. Algorithm-specific loss and optimization
should be reflected here.
"""
return NotImplementedError | [
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AbsAgent.load_model | (self, model) | Load models from memory. | Load models from memory. | def load_model(self, model):
"""Load models from memory."""
self.model.load_state_dict(model) | [
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AbsAgent.dump_model | (self) | Return the algorithm's trainable models. | Return the algorithm's trainable models. | def dump_model(self):
"""Return the algorithm's trainable models."""
return self.model.state_dict() | [
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AbsAgent.load_model_from_file | (self, path: str) | Load trainable models from disk.
Load trainable models from the specified directory. The model file is always prefixed with the agent's name.
Args:
path (str): path to the directory where the models are saved.
| Load trainable models from disk. | def load_model_from_file(self, path: str):
"""Load trainable models from disk.
Load trainable models from the specified directory. The model file is always prefixed with the agent's name.
Args:
path (str): path to the directory where the models are saved.
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AbsAgent.dump_model_to_file | (self, path: str) | Dump the algorithm's trainable models to disk.
Dump trainable models to the specified directory. The model file is always prefixed with the agent's name.
Args:
path (str): path to the directory where the models are saved.
| Dump the algorithm's trainable models to disk. | def dump_model_to_file(self, path: str):
"""Dump the algorithm's trainable models to disk.
Dump trainable models to the specified directory. The model file is always prefixed with the agent's name.
Args:
path (str): path to the directory where the models are saved.
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ConfigFlow.async_get_options_flow | (config_entry) | Get the options flow for this handler. | Get the options flow for this handler. | def async_get_options_flow(config_entry):
"""Get the options flow for this handler."""
return OptionsFlowHandler(config_entry) | [
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ConfigFlow.async_step_user | (self, user_input=None) | Handle the initial step. | Handle the initial step. | async def async_step_user(self, user_input=None):
"""Handle the initial step."""
errors = {}
if user_input is not None:
name = user_input[CONF_NAME]
longitude = user_input[CONF_LONGITUDE]
latitude = user_input[CONF_LATITUDE]
session = aiohttp_cli... | [
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OptionsFlowHandler.__init__ | (self, config_entry) | Initialize options flow. | Initialize options flow. | def __init__(self, config_entry):
"""Initialize options flow."""
self.config_entry = config_entry | [
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OptionsFlowHandler.async_step_init | (self, user_input=None) | Manage options. | Manage options. | async def async_step_init(self, user_input=None):
"""Manage options."""
if user_input is not None:
return self.async_create_entry(title="", data=user_input)
return self.async_show_form(
step_id="init",
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{
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setup | (hass, config) | Initialize the Shiftr.io MQTT consumer. | Initialize the Shiftr.io MQTT consumer. | def setup(hass, config):
"""Initialize the Shiftr.io MQTT consumer."""
conf = config[DOMAIN]
username = conf.get(CONF_USERNAME)
password = conf.get(CONF_PASSWORD)
client_id = "HomeAssistant"
port = 1883
keepalive = 600
mqttc = mqtt.Client(client_id, protocol=mqtt.MQTTv311)
mqttc.us... | [
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async_turn_on | (hass, entity_id) | Async reset the alert.
This is a legacy helper method. Do not use it for new tests.
| Async reset the alert. | def async_turn_on(hass, entity_id):
"""Async reset the alert.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_ENTITY_ID: entity_id}
hass.async_create_task(hass.services.async_call(DOMAIN, SERVICE_TURN_ON, data)) | [
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async_turn_off | (hass, entity_id) | Async acknowledge the alert.
This is a legacy helper method. Do not use it for new tests.
| Async acknowledge the alert. | def async_turn_off(hass, entity_id):
"""Async acknowledge the alert.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_ENTITY_ID: entity_id}
hass.async_create_task(hass.services.async_call(DOMAIN, SERVICE_TURN_OFF, data)) | [
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async_toggle | (hass, entity_id) | Async toggle acknowledgment of alert.
This is a legacy helper method. Do not use it for new tests.
| Async toggle acknowledgment of alert. | def async_toggle(hass, entity_id):
"""Async toggle acknowledgment of alert.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_ENTITY_ID: entity_id}
hass.async_create_task(hass.services.async_call(DOMAIN, SERVICE_TOGGLE, data)) | [
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mock_notifier | (hass) | Mock for notifier. | Mock for notifier. | def mock_notifier(hass):
"""Mock for notifier."""
events = []
@callback
def record_event(event):
"""Add recorded event to set."""
events.append(event)
hass.services.async_register(notify.DOMAIN, NOTIFIER, record_event)
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test_is_on | (hass) | Test is_on method. | Test is_on method. | async def test_is_on(hass):
"""Test is_on method."""
hass.states.async_set(ENTITY_ID, STATE_ON)
await hass.async_block_till_done()
assert alert.is_on(hass, ENTITY_ID)
hass.states.async_set(ENTITY_ID, STATE_OFF)
await hass.async_block_till_done()
assert not alert.is_on(hass, ENTITY_ID) | [
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test_setup | (hass) | Test setup method. | Test setup method. | async def test_setup(hass):
"""Test setup method."""
assert await async_setup_component(hass, alert.DOMAIN, TEST_CONFIG)
assert STATE_IDLE == hass.states.get(ENTITY_ID).state | [
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test_fire | (hass, mock_notifier) | Test the alert firing. | Test the alert firing. | async def test_fire(hass, mock_notifier):
"""Test the alert firing."""
assert await async_setup_component(hass, alert.DOMAIN, TEST_CONFIG)
hass.states.async_set("sensor.test", STATE_ON)
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test_silence | (hass, mock_notifier) | Test silencing the alert. | Test silencing the alert. | async def test_silence(hass, mock_notifier):
"""Test silencing the alert."""
assert await async_setup_component(hass, alert.DOMAIN, TEST_CONFIG)
hass.states.async_set("sensor.test", STATE_ON)
await hass.async_block_till_done()
async_turn_off(hass, ENTITY_ID)
await hass.async_block_till_done()
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test_reset | (hass, mock_notifier) | Test resetting the alert. | Test resetting the alert. | async def test_reset(hass, mock_notifier):
"""Test resetting the alert."""
assert await async_setup_component(hass, alert.DOMAIN, TEST_CONFIG)
hass.states.async_set("sensor.test", STATE_ON)
await hass.async_block_till_done()
async_turn_off(hass, ENTITY_ID)
await hass.async_block_till_done()
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test_toggle | (hass, mock_notifier) | Test toggling alert. | Test toggling alert. | async def test_toggle(hass, mock_notifier):
"""Test toggling alert."""
assert await async_setup_component(hass, alert.DOMAIN, TEST_CONFIG)
hass.states.async_set("sensor.test", STATE_ON)
await hass.async_block_till_done()
assert STATE_ON == hass.states.get(ENTITY_ID).state
async_toggle(hass, ENTI... | [
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test_notification_no_done_message | (hass) | Test notifications. | Test notifications. | async def test_notification_no_done_message(hass):
"""Test notifications."""
events = []
config = deepcopy(TEST_CONFIG)
del config[alert.DOMAIN][NAME][alert.CONF_DONE_MESSAGE]
@callback
def record_event(event):
"""Add recorded event to set."""
events.append(event)
hass.serv... | [
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":",
"events",
"=",
"[",
"]",
"config",
"=",
"deepcopy",
"(",
"TEST_CONFIG",
")",
"del",
"config",
"[",
"alert",
".",
"DOMAIN",
"]",
"[",
"NAME",
"]",
"[",
"alert",
".",
"CONF_DONE_MESS... | [
178,
0
] | [
200,
27
] | python | en | ['en', 'en', 'en'] | False |
test_notification | (hass) | Test notifications. | Test notifications. | async def test_notification(hass):
"""Test notifications."""
events = []
@callback
def record_event(event):
"""Add recorded event to set."""
events.append(event)
hass.services.async_register(notify.DOMAIN, NOTIFIER, record_event)
assert await async_setup_component(hass, alert.... | [
"async",
"def",
"test_notification",
"(",
"hass",
")",
":",
"events",
"=",
"[",
"]",
"@",
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"record_event",
"(",
"event",
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":",
"\"\"\"Add recorded event to set.\"\"\"",
"events",
".",
"append",
"(",
"event",
")",
"hass",
".",
"services",
... | [
203,
0
] | [
223,
27
] | python | en | ['en', 'en', 'en'] | False |
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