Best Python code snippet using slash
recommendations.py
Source:recommendations.py
...43 # Removes the distance from the dictionaries and returns the best n tracks.44 for d in ordered_songs:45 del d['distance']46 return ordered_songs[:n]47def _get_parameter_string(min_key=-1, min_mode=0,48 min_acousticness=0.0, min_danceablility=0.0,49 min_energy=0.0, min_instrumentalness=0.0,50 min_liveness=0.0, min_loudness=-60,51 min_speechiness=0.0, min_valence=0.0, min_tempo=0,52 max_key=11, max_mode=1,53 max_acousticness=1.0, max_danceablility=1.0,54 max_energy=1.0, max_instrumentalness=1.0,55 max_liveness=1.0, max_loudness=0,56 max_speechiness=1.0, max_valence=1.0, max_tempo=99999):57 """ Fills in emtpy parameters with their default value. """58 return (f"&min_key={min_key}&max_key={max_key}" +59 f"&min_mode={min_mode}&max_mode={max_mode}" +60 f"&min_acousticness={min_acousticness}&max_acousticness={max_acousticness}" +61 f"&min_danceablility={min_danceablility}&max_danceablility={max_danceablility}" +62 f"&min_energy={min_energy}&max_energy={max_energy}" +63 f"&min_instrumentalness={min_instrumentalness}&max_instrumentalness={max_instrumentalness}" +64 f"&min_liveness={min_liveness}&max_liveness={max_liveness}" +65 f"&min_loudness={min_loudness}&max_loudness={max_loudness}" +66 f"&min_speechiness={min_speechiness}&max_speechiness={max_speechiness}" +67 f"&min_valence={min_valence}&max_valence={max_valence}" +68 f"&min_tempo={min_tempo}&max_tempo={max_tempo}")69def calculate_target_mood(target, current):70 """71 Updates the target mood, the new mood is the weighted mean between the target and current.72 :param target: the target mood formatted as: (excitedness, happiness).73 :param current: the current mood formatted as: (excitedness, happiness).74 :return: new target formatted as: (excitedness, happiness).75 """76 return 0.6 *target[0] + 0.4 * current[0], 0.6 * target[1] + 0.4 * current[1]77def recommend_input(tracks, userid, target=(0.0, 0.0), n=5):78 """79 Find recommendations given max 5 song ID's.80 The recommendations are based on the given songs and the given target mood.81 :param tracks: list of given songs.82 :param userid: Spotify user id of the user.83 :param target: the target mood formatted as: (excitedness, happiness).84 :param n: the amount of recommendations that are returned, standard is 5.85 :return: ascending list of n dictionaries formatted as:86 [{'songid': actual song id, excitedness: actual excitedness, happiness: actual happiness}].87 """88 access_token = spotify.get_access_token(User.get_refresh_token(userid))89 return find_song_recommendations(access_token, tracks, target, n, _get_parameter_string())90def recommend_metric(tracks, userid, metric, excitedness, happiness, n=5):91 """92 Find recommendations based on the last 5 songs, the given metric and the current mood.93 :param tracks: list of given songs.94 :param userid: Spotify user id of the user.95 :param metric: keywords for moods and events, the possible keywords are: sad, mellow, angry, excited, dance, study,96 karaoke, neutral.97 :param excitedness: the excitedness of a user.98 :param happiness: the happiness of a user.99 :param n: the amount of recommendations that are returned, standard is 5.100 :return: ascending list of n dictionaries formatted as: [{'songid': actual song id, excitedness: actual excitedness,101 happiness: actual happiness}].102 """103 moods = {'sad': (-10, -10), 'mellow': (-10, 10), 'angry': (10, -10), 'excited': (10, 10), }104 events = {'dance': _get_parameter_string(min_danceablility=0.4,105 min_energy=0.5, min_loudness=-10, min_speechiness=0.0,106 min_tempo=60, max_acousticness=0.2,107 max_instrumentalness=0.15, max_loudness=-2, max_speechiness=0.3,108 max_tempo=130),109 'study': _get_parameter_string(min_acousticness=0.6,110 min_instrumentalness=0.5, min_loudness=-30,111 max_danceablility=0.1, max_energy=0.35, max_instrumentalness=1.0,112 max_loudness=-10, max_speechiness=0.1),113 'karaoke': _get_parameter_string(min_energy=0.1,114 min_loudness=-15, max_instrumentalness=0.15,115 max_loudness=-4, max_speechiness=0.2),116 'neutral': _get_parameter_string()}117 access_token = spotify.get_access_token(User.get_refresh_token(userid))118 # Calculates the target mood and recommends songs based on this target.119 if metric in moods:120 target = calculate_target_mood(moods[metric], (excitedness, happiness))121 return find_song_recommendations(access_token, tracks, target, n, _get_parameter_string())122 # Recommends songs based on parameters corresponding to events, the target mood is the current mood.123 if metric in events:124 return find_song_recommendations(access_token, tracks, (excitedness, happiness), n, events[metric])125def find_song_recommendations(access_token, tracks, target, n, params):126 """127 Find recommendations based on the last 5 songs, the given metric and the current mood.128 :param access_token: A valid access token from the Spotify Accounts service.129 :param tracks: list of given songs.130 :param target: the target mood formatted as: (excitedness, happiness).131 :param n: the amount of recommendations that are returned, standard is 5.132 :param params: Audio feature parameters.133 :return: ascending list of n dictionaries formatted as:134 [{'songid': actual song id, excitedness: actual excitedness, happiness: actual happiness}].135 """...
function.py
Source:function.py
...49 def _body_context(self, code_formatter):50 self._write_decorators(code_formatter)51 code_formatter.writeln('def {}({}):'.format(52 self._get_function_name(),53 self._get_parameter_string()))54 with code_formatter.indented():55 if not self.suite.debug_info:56 code_formatter.writeln('pass')57 self._write_parameter_values(code_formatter)58 self._write_immediate_events(code_formatter)59 self._write_deferred_events(code_formatter)60 self._write_prologue(code_formatter)61 yield62 self._write_epilogue(code_formatter)63 self._write_return(code_formatter)64 code_formatter.writeln()65 def _get_parameter_string(self):66 returned = ', '.join(self._get_argument_strings())67 if returned and self._additional_parameter_string:68 returned += ', '69 returned += self._additional_parameter_string70 return returned71 def _write_prologue(self, code_formatter):72 pass73 def _write_epilogue(self, code_formatter):74 pass75 def _write_immediate_events(self, code_formatter):76 for event in self._events:77 self._write_event(code_formatter, event)78 def _write_deferred_events(self, code_formatter):79 if not self.suite.debug_info:...
Vulnerabilities.py
Source:Vulnerabilities.py
...6logger = logging.getLogger(__name__)7def _get_vulnerabilities_url(self):8 return self.config['baseurl'] + '/api/vulnerabilities'9def get_vulnerabilities(self, vulnerability, parameters={}):10 url = self._get_vulnerabilities_url() + "/{}".format(vulnerability) + self._get_parameter_string(parameters)11 headers = {'Accept': 'application/vnd.blackducksoftware.vulnerability-4+json'}12 response = self.execute_get(url, custom_headers=headers)13 return response.json()14def get_vulnerability_affected_projects(self, vulnerability):15 url = self._get_vulnerabilities_url() + "/{}/affected-projects".format(vulnerability) 16 custom_headers = {'Accept': 'application/vnd.blackducksoftware.vulnerability-4+json'}17 response = self.execute_get(url, custom_headers=custom_headers)18 return response.json()19# TODO: Refactor this, i.e. use get_link method?20def get_vulnerable_bom_components(self, version_obj, limit=9999):21 url = "{}/vulnerable-bom-components".format(version_obj['_meta']['href'])22 custom_headers = {'Accept': 'application/vnd.blackducksoftware.bill-of-materials-6+json'}23 param_string = self._get_parameter_string({'limit': limit})24 url = "{}{}".format(url, param_string)25 response = self.execute_get(url, custom_headers=custom_headers)26 return response.json()27# TODO: Remove or refactor this28def get_component_remediation(self, bom_component):29 url = "{}/remediating".format(bom_component['componentVersion'])30 logger.debug("Url for getting remediation info is : {}".format(url))31 response = self.execute_get(url)...
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