cerebralcortex package¶
Subpackages¶
- cerebralcortex.algorithms package
- Subpackages
- cerebralcortex.algorithms.bluetooth package
- cerebralcortex.algorithms.ecg package
- cerebralcortex.algorithms.ema package
- cerebralcortex.algorithms.glucose package
- cerebralcortex.algorithms.gps package
- cerebralcortex.algorithms.raw_byte_decode package
- cerebralcortex.algorithms.rr_intervals package
- cerebralcortex.algorithms.signal_processing package
- cerebralcortex.algorithms.stats package
- cerebralcortex.algorithms.stress_prediction package
- cerebralcortex.algorithms.utils package
- cerebralcortex.algorithms.visualization package
- Module contents
- Subpackages
- cerebralcortex.core package
- cerebralcortex.examples package
- cerebralcortex.markers package
- cerebralcortex.plotting package
- cerebralcortex.test_suite package
- Subpackages
- Submodules
- cerebralcortex.test_suite.join_spark module
- cerebralcortex.test_suite.test_glucose_metrics module
- cerebralcortex.test_suite.test_gps_cluster_udf module
- cerebralcortex.test_suite.test_import_data module
- cerebralcortex.test_suite.test_main module
- cerebralcortex.test_suite.test_nosql_storage module
- cerebralcortex.test_suite.test_rest_api_server module
- cerebralcortex.test_suite.test_sql_storage module
- cerebralcortex.test_suite.tt module
- Module contents
- cerebralcortex.util package
Submodules¶
cerebralcortex.kernel module¶
-
class
Kernel
(configs_dir_path: str = '', cc_configs: dict = None, study_name: str = 'default', new_study: bool = False, enable_spark: bool = True, enable_spark_ui=False)[source]¶ Bases:
object
-
connect
(username: str, password: str, encrypt_password: bool = False) → dict[source]¶ Authenticate a user based on username and password and return an auth token
Parameters: - username (str) – username of a user
- password (str) – password of a user
- encrypt_password (str) – is password encrypted or not. mCerebrum sends encrypted passwords
Raises: ValueError
– User name and password cannot be empty/None.Returns: return eturn {“status”:bool, “auth_token”: str, “msg”: str}
Return type: dict
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.connect("nasir_ali", "2ksdfhoi2r2ljndf823hlkf8234hohwef0234hlkjwer98u234", True) >>> True
-
create_user
(username: str, user_password: str, user_role: str, user_metadata: dict, user_settings: dict, encrypt_password: bool = False) → bool[source]¶ Create a user in SQL storage if it doesn’t exist
Parameters: - username (str) – Only alphanumeric usernames are allowed with the max length of 25 chars.
- user_password (str) – no size limit on password
- user_role (str) – role of a user
- user_metadata (dict) – metadata of a user
- user_settings (dict) – user settings, mCerebrum configurations of a user
- encrypt_password (bool) – encrypt password if set to true
Returns: True if user is successfully registered or throws any error in case of failure
Return type: bool
Raises: ValueError
– if selected username is not availableException
– if sql query fails
-
encrypt_user_password
(user_password: str) → str[source]¶ Encrypt password
Parameters: user_password (str) – unencrypted password Raises: ValueError
– password cannot be None or empty.Returns: encrypted password Return type: str
-
gen_random_pass
(string_type: str = 'varchar', size: int = 8) → str[source]¶ Generate a random password
Parameters: - string_type – Accepted parameters are “varchar” and “char”. (Default=”varchar”)
- size – password length (default=8)
Returns: random password
Return type: str
-
get_stream
(stream_name: str, version: str = 'latest', user_id: str = None, data_type=<DataSet.COMPLETE: (1, )>) → cerebralcortex.core.datatypes.datastream.DataStream[source]¶ Retrieve a data-stream with it’s metadata.
Parameters: - stream_name (str) – name of a stream
- version (str) – version of a stream. Acceptable parameters are all, latest, or a specific version of a stream (e.g., 2.0) (Default=”all”)
- data_type (DataSet) – DataSet.COMPLETE returns both Data and Metadata. DataSet.ONLY_DATA returns only Data. DataSet.ONLY_METADATA returns only metadata of a stream. (Default=DataSet.COMPLETE)
Returns: contains Data and/or metadata
Return type: Raises: ValueError
– if stream name is empty or NoneNote
Please specify a version if you know the exact version of a stream. Getting all the stream data and then filtering versions won’t be efficient.
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> ds = CC.get_stream("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> ds.data # an object of a dataframe >>> ds.metadata # an object of MetaData class >>> ds.get_metadata(version=1) # get the specific version metadata of a stream
-
get_stream_metadata_by_hash
(metadata_hash: <module 'uuid' from '/home/docs/.pyenv/versions/3.6.8/lib/python3.6/uuid.py'>) → str[source]¶ metadata_hash are unique to each stream version. This reverse look can return the stream name of a metadata_hash.
Parameters: metadata_hash (uuid) – This could be an actual uuid object or a string form of uuid. Returns: [stream_name, metadata] Return type: List Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_by_hash("00ab666c-afb8-476e-9872-6472b4e66b68") >>> ["name" .....] # stream metadata and other information
-
get_stream_metadata_by_name
(stream_name: str, version: str = 1) → List[cerebralcortex.core.metadata_manager.stream.metadata.Metadata][source]¶ Get a list of metadata for all versions available for a stream.
Parameters: - stream_name (str) – name of a stream
- version (str) – version of a stream. Acceptable parameters are all, latest, or a specific version of a stream (e.g., 2.0) (Default=”all”)
Returns: Returns an empty list if no metadata is available for a stream_name or a list of metadata otherwise.
Return type: Raises: ValueError
– stream_name cannot be None or empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_by_name("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST", version=1) >>> Metadata # list of MetaData class objects
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get_stream_metadata_hash
(stream_name: str) → list[source]¶ Get all the metadata_hash associated with a stream name.
Parameters: stream_name (str) – name of a stream Returns: list of all the metadata hashes with name and versions Return type: list Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_hash("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> [["stream_name", "version", "metadata_hash"]]
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get_stream_name
(metadata_hash: <module 'uuid' from '/home/docs/.pyenv/versions/3.6.8/lib/python3.6/uuid.py'>) → str[source]¶ metadata_hash are unique to each stream version. This reverse look can return the stream name of a metadata_hash.
Parameters: metadata_hash (uuid) – This could be an actual uuid object or a string form of uuid. Returns: name of a stream Return type: str Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_name("00ab666c-afb8-476e-9872-6472b4e66b68") >>> ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST
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get_stream_versions
(stream_name: str) → list[source]¶ Returns a list of versions available for a stream
Parameters: stream_name (str) – name of a stream Returns: list of int Return type: list Raises: ValueError
– if stream_name is empty or NoneExamples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_versions("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> [1, 2, 4]
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get_user_id
(user_name: str) → str[source]¶ Get the user id linked to user_name.
Parameters: user_name (str) – username of a user Returns: user id associated to user_name Return type: str Raises: ValueError
– User name is a required field.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_id("nasir_ali") >>> '76cc444c-4fb8-776e-2872-9472b4e66b16'
-
get_user_metadata
(user_id: str = None, username: str = None) → dict[source]¶ Get user metadata by user_id or by username
Parameters: - user_id (str) – id (uuid) of a user
- user_name (str) – username of a user
Returns: user metadata
Return type: dict
Todo
Return list of User class object
Raises: ValueError
– User ID/name cannot be empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_metadata(username="nasir_ali") >>> {"study_name":"mperf"........}
-
get_user_name
(user_id: str) → str[source]¶ Get the user name linked to a user id.
Parameters: user_name (str) – username of a user Returns: user_id associated to username Return type: bool Raises: ValueError
– User ID is a required field.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_username("76cc444c-4fb8-776e-2872-9472b4e66b16") >>> 'nasir_ali'
-
get_user_settings
(username: str = None, auth_token: str = None) → dict[source]¶ Get user settings by auth-token or by username. These are user’s mCerebrum settings
Parameters: - username (str) – username of a user
- auth_token (str) – auth-token
Returns: List of dictionaries of user metadata
Return type: list[dict]
Todo
Return list of User class object
Raises: ValueError
– User ID/name cannot be empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_settings(username="nasir_ali") >>> [{"mcerebrum":"some-conf"........}]
-
is_auth_token_valid
(username: str, auth_token: str, checktime: bool = False) → bool[source]¶ Validate whether a token is valid or expired based on the token expiry datetime stored in SQL
Parameters: - username (str) – username of a user
- auth_token (str) – token generated by API-Server
- checktime (bool) – setting this to False will only check if the token is available in system. Setting this to true will check if the token is expired based on the token expiry date.
Raises: ValueError
– Auth token and auth-token expiry time cannot be null/empty.Returns: returns True if token is valid or False otherwise.
Return type: bool
-
is_stream
(stream_name: str) → bool[source]¶ Returns true if provided stream exists.
Parameters: stream_name (str) – name of a stream Returns: True if stream_name exist False otherwise Return type: bool Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.is_stream("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> True
-
is_user
(user_id: str = None, user_name: str = None) → bool[source]¶ Checks whether a user exists in the system. One of both parameters could be set to verify whether user exist.
Parameters: - user_id (str) – id (uuid) of a user
- user_name (str) – username of a user
Returns: True if a user exists in the system or False otherwise.
Return type: bool
Raises: ValueError
– Both user_id and user_name cannot be None or empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.is_user(user_id="76cc444c-4fb8-776e-2872-9472b4e66b16") >>> True
-
list_streams
() → List[str][source]¶ Get all the available stream names with metadata
Returns: list of available streams metadata Return type: List[str] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.list_streams()
-
list_users
() → List[dict][source]¶ Get a list of all users part of a study.
Parameters: study_name (str) – name of a study. If no study_name is provided then all users’ list will be returned Raises: ValueError
– Study name is a requied field.Returns: Returns empty list if there is no user associated to the study_name and/or study_name does not exist. Return type: list[dict] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.list_users() >>> [{"76cc444c-4fb8-776e-2872-9472b4e66b16": "nasir_ali"}] # [{user_id, user_name}]
-
read_csv
(file_path, stream_name: str, header: bool = False, delimiter: str = ', ', column_names: list = [], timestamp_column_index: int = 0, timein: str = 'milliseconds', metadata: cerebralcortex.core.metadata_manager.stream.metadata.Metadata = None) → cerebralcortex.core.datatypes.datastream.DataStream[source]¶ Reads a csv file (compressed or uncompressed), parse it, convert it into CC DataStream object format and returns it
Parameters: - file_path (str) – path of the file
- stream_name (str) – name of the stream
- header (bool) – set it to True if csv contains header column
- delimiter (str) – seprator used in csv file. Default is comma
- column_names (list[str]) – list of column names
- timestamp_column_index (int) – index of the timestamp column name
- timein (str) – if timestamp is epoch time, provide whether it is in milliseconds or seconds
- metadata (Metadata) – metadata object for the csv file
Returns: DataStream object
-
save_stream
(datastream: cerebralcortex.core.datatypes.datastream.DataStream, overwrite=False) → bool[source]¶ Saves datastream raw data in selected NoSQL storage and metadata in MySQL.
Parameters: - datastream (DataStream) – a DataStream object
- overwrite (bool) – if set to true, whole existing datastream data will be overwritten by new data
Returns: True if stream is successfully stored or throws an exception
Return type: bool
Raises: Exception
– log or throws exception if stream is not storedTodo
Add functionality to store data in influxdb.
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> ds = DataStream(dataframe, MetaData) >>> CC.save_stream(ds)
-
search_stream
(stream_name)[source]¶ Find all the stream names similar to stream_name arg. For example, passing “location” argument will return all stream names that contain the word location
Returns: list of stream names similar to stream_name arg Return type: List[str] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.search_stream("battery") >>> ["BATTERY--org.md2k.motionsense--MOTION_SENSE_HRV--LEFT_WRIST", "BATTERY--org.md2k.phonesensor--PHONE".....]
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update_auth_token
(username: str, auth_token: str, auth_token_issued_time: datetime.datetime, auth_token_expiry_time: datetime.datetime) → bool[source]¶ Update an auth token in SQL database to keep user stay logged in. Auth token valid duration can be changed in configuration files.
Notes
This method is used by API-server to store newly created auth-token
Parameters: - username (str) – username of a user
- auth_token (str) – issued new auth token
- auth_token_issued_time (datetime) – datetime when the old auth token was issue
- auth_token_expiry_time (datetime) – datetime when the token will get expired
Raises: ValueError
– Auth token and auth-token issue/expiry time cannot be None/empty.Returns: Returns True if the new auth token is set or False otherwise.
Return type: bool
-
Module contents¶
-
class
Kernel
(configs_dir_path: str = '', cc_configs: dict = None, study_name: str = 'default', new_study: bool = False, enable_spark: bool = True, enable_spark_ui=False)[source]¶ Bases:
object
-
connect
(username: str, password: str, encrypt_password: bool = False) → dict[source]¶ Authenticate a user based on username and password and return an auth token
Parameters: - username (str) – username of a user
- password (str) – password of a user
- encrypt_password (str) – is password encrypted or not. mCerebrum sends encrypted passwords
Raises: ValueError
– User name and password cannot be empty/None.Returns: return eturn {“status”:bool, “auth_token”: str, “msg”: str}
Return type: dict
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.connect("nasir_ali", "2ksdfhoi2r2ljndf823hlkf8234hohwef0234hlkjwer98u234", True) >>> True
-
create_user
(username: str, user_password: str, user_role: str, user_metadata: dict, user_settings: dict, encrypt_password: bool = False) → bool[source]¶ Create a user in SQL storage if it doesn’t exist
Parameters: - username (str) – Only alphanumeric usernames are allowed with the max length of 25 chars.
- user_password (str) – no size limit on password
- user_role (str) – role of a user
- user_metadata (dict) – metadata of a user
- user_settings (dict) – user settings, mCerebrum configurations of a user
- encrypt_password (bool) – encrypt password if set to true
Returns: True if user is successfully registered or throws any error in case of failure
Return type: bool
Raises: ValueError
– if selected username is not availableException
– if sql query fails
-
encrypt_user_password
(user_password: str) → str[source]¶ Encrypt password
Parameters: user_password (str) – unencrypted password Raises: ValueError
– password cannot be None or empty.Returns: encrypted password Return type: str
-
gen_random_pass
(string_type: str = 'varchar', size: int = 8) → str[source]¶ Generate a random password
Parameters: - string_type – Accepted parameters are “varchar” and “char”. (Default=”varchar”)
- size – password length (default=8)
Returns: random password
Return type: str
-
get_stream
(stream_name: str, version: str = 'latest', user_id: str = None, data_type=<DataSet.COMPLETE: (1, )>) → cerebralcortex.core.datatypes.datastream.DataStream[source]¶ Retrieve a data-stream with it’s metadata.
Parameters: - stream_name (str) – name of a stream
- version (str) – version of a stream. Acceptable parameters are all, latest, or a specific version of a stream (e.g., 2.0) (Default=”all”)
- data_type (DataSet) – DataSet.COMPLETE returns both Data and Metadata. DataSet.ONLY_DATA returns only Data. DataSet.ONLY_METADATA returns only metadata of a stream. (Default=DataSet.COMPLETE)
Returns: contains Data and/or metadata
Return type: Raises: ValueError
– if stream name is empty or NoneNote
Please specify a version if you know the exact version of a stream. Getting all the stream data and then filtering versions won’t be efficient.
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> ds = CC.get_stream("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> ds.data # an object of a dataframe >>> ds.metadata # an object of MetaData class >>> ds.get_metadata(version=1) # get the specific version metadata of a stream
-
get_stream_metadata_by_hash
(metadata_hash: <module 'uuid' from '/home/docs/.pyenv/versions/3.6.8/lib/python3.6/uuid.py'>) → str[source]¶ metadata_hash are unique to each stream version. This reverse look can return the stream name of a metadata_hash.
Parameters: metadata_hash (uuid) – This could be an actual uuid object or a string form of uuid. Returns: [stream_name, metadata] Return type: List Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_by_hash("00ab666c-afb8-476e-9872-6472b4e66b68") >>> ["name" .....] # stream metadata and other information
-
get_stream_metadata_by_name
(stream_name: str, version: str = 1) → List[cerebralcortex.core.metadata_manager.stream.metadata.Metadata][source]¶ Get a list of metadata for all versions available for a stream.
Parameters: - stream_name (str) – name of a stream
- version (str) – version of a stream. Acceptable parameters are all, latest, or a specific version of a stream (e.g., 2.0) (Default=”all”)
Returns: Returns an empty list if no metadata is available for a stream_name or a list of metadata otherwise.
Return type: Raises: ValueError
– stream_name cannot be None or empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_by_name("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST", version=1) >>> Metadata # list of MetaData class objects
-
get_stream_metadata_hash
(stream_name: str) → list[source]¶ Get all the metadata_hash associated with a stream name.
Parameters: stream_name (str) – name of a stream Returns: list of all the metadata hashes with name and versions Return type: list Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_metadata_hash("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> [["stream_name", "version", "metadata_hash"]]
-
get_stream_name
(metadata_hash: <module 'uuid' from '/home/docs/.pyenv/versions/3.6.8/lib/python3.6/uuid.py'>) → str[source]¶ metadata_hash are unique to each stream version. This reverse look can return the stream name of a metadata_hash.
Parameters: metadata_hash (uuid) – This could be an actual uuid object or a string form of uuid. Returns: name of a stream Return type: str Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_name("00ab666c-afb8-476e-9872-6472b4e66b68") >>> ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST
-
get_stream_versions
(stream_name: str) → list[source]¶ Returns a list of versions available for a stream
Parameters: stream_name (str) – name of a stream Returns: list of int Return type: list Raises: ValueError
– if stream_name is empty or NoneExamples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_stream_versions("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> [1, 2, 4]
-
get_user_id
(user_name: str) → str[source]¶ Get the user id linked to user_name.
Parameters: user_name (str) – username of a user Returns: user id associated to user_name Return type: str Raises: ValueError
– User name is a required field.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_id("nasir_ali") >>> '76cc444c-4fb8-776e-2872-9472b4e66b16'
-
get_user_metadata
(user_id: str = None, username: str = None) → dict[source]¶ Get user metadata by user_id or by username
Parameters: - user_id (str) – id (uuid) of a user
- user_name (str) – username of a user
Returns: user metadata
Return type: dict
Todo
Return list of User class object
Raises: ValueError
– User ID/name cannot be empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_metadata(username="nasir_ali") >>> {"study_name":"mperf"........}
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get_user_name
(user_id: str) → str[source]¶ Get the user name linked to a user id.
Parameters: user_name (str) – username of a user Returns: user_id associated to username Return type: bool Raises: ValueError
– User ID is a required field.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_username("76cc444c-4fb8-776e-2872-9472b4e66b16") >>> 'nasir_ali'
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get_user_settings
(username: str = None, auth_token: str = None) → dict[source]¶ Get user settings by auth-token or by username. These are user’s mCerebrum settings
Parameters: - username (str) – username of a user
- auth_token (str) – auth-token
Returns: List of dictionaries of user metadata
Return type: list[dict]
Todo
Return list of User class object
Raises: ValueError
– User ID/name cannot be empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.get_user_settings(username="nasir_ali") >>> [{"mcerebrum":"some-conf"........}]
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is_auth_token_valid
(username: str, auth_token: str, checktime: bool = False) → bool[source]¶ Validate whether a token is valid or expired based on the token expiry datetime stored in SQL
Parameters: - username (str) – username of a user
- auth_token (str) – token generated by API-Server
- checktime (bool) – setting this to False will only check if the token is available in system. Setting this to true will check if the token is expired based on the token expiry date.
Raises: ValueError
– Auth token and auth-token expiry time cannot be null/empty.Returns: returns True if token is valid or False otherwise.
Return type: bool
-
is_stream
(stream_name: str) → bool[source]¶ Returns true if provided stream exists.
Parameters: stream_name (str) – name of a stream Returns: True if stream_name exist False otherwise Return type: bool Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.is_stream("ACCELEROMETER--org.md2k.motionsense--MOTION_SENSE_HRV--RIGHT_WRIST") >>> True
-
is_user
(user_id: str = None, user_name: str = None) → bool[source]¶ Checks whether a user exists in the system. One of both parameters could be set to verify whether user exist.
Parameters: - user_id (str) – id (uuid) of a user
- user_name (str) – username of a user
Returns: True if a user exists in the system or False otherwise.
Return type: bool
Raises: ValueError
– Both user_id and user_name cannot be None or empty.Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.is_user(user_id="76cc444c-4fb8-776e-2872-9472b4e66b16") >>> True
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list_streams
() → List[str][source]¶ Get all the available stream names with metadata
Returns: list of available streams metadata Return type: List[str] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.list_streams()
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list_users
() → List[dict][source]¶ Get a list of all users part of a study.
Parameters: study_name (str) – name of a study. If no study_name is provided then all users’ list will be returned Raises: ValueError
– Study name is a requied field.Returns: Returns empty list if there is no user associated to the study_name and/or study_name does not exist. Return type: list[dict] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.list_users() >>> [{"76cc444c-4fb8-776e-2872-9472b4e66b16": "nasir_ali"}] # [{user_id, user_name}]
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read_csv
(file_path, stream_name: str, header: bool = False, delimiter: str = ', ', column_names: list = [], timestamp_column_index: int = 0, timein: str = 'milliseconds', metadata: cerebralcortex.core.metadata_manager.stream.metadata.Metadata = None) → cerebralcortex.core.datatypes.datastream.DataStream[source]¶ Reads a csv file (compressed or uncompressed), parse it, convert it into CC DataStream object format and returns it
Parameters: - file_path (str) – path of the file
- stream_name (str) – name of the stream
- header (bool) – set it to True if csv contains header column
- delimiter (str) – seprator used in csv file. Default is comma
- column_names (list[str]) – list of column names
- timestamp_column_index (int) – index of the timestamp column name
- timein (str) – if timestamp is epoch time, provide whether it is in milliseconds or seconds
- metadata (Metadata) – metadata object for the csv file
Returns: DataStream object
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save_stream
(datastream: cerebralcortex.core.datatypes.datastream.DataStream, overwrite=False) → bool[source]¶ Saves datastream raw data in selected NoSQL storage and metadata in MySQL.
Parameters: - datastream (DataStream) – a DataStream object
- overwrite (bool) – if set to true, whole existing datastream data will be overwritten by new data
Returns: True if stream is successfully stored or throws an exception
Return type: bool
Raises: Exception
– log or throws exception if stream is not storedTodo
Add functionality to store data in influxdb.
Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> ds = DataStream(dataframe, MetaData) >>> CC.save_stream(ds)
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search_stream
(stream_name)[source]¶ Find all the stream names similar to stream_name arg. For example, passing “location” argument will return all stream names that contain the word location
Returns: list of stream names similar to stream_name arg Return type: List[str] Examples
>>> CC = Kernel("/directory/path/of/configs/", study_name="default") >>> CC.search_stream("battery") >>> ["BATTERY--org.md2k.motionsense--MOTION_SENSE_HRV--LEFT_WRIST", "BATTERY--org.md2k.phonesensor--PHONE".....]
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update_auth_token
(username: str, auth_token: str, auth_token_issued_time: datetime.datetime, auth_token_expiry_time: datetime.datetime) → bool[source]¶ Update an auth token in SQL database to keep user stay logged in. Auth token valid duration can be changed in configuration files.
Notes
This method is used by API-server to store newly created auth-token
Parameters: - username (str) – username of a user
- auth_token (str) – issued new auth token
- auth_token_issued_time (datetime) – datetime when the old auth token was issue
- auth_token_expiry_time (datetime) – datetime when the token will get expired
Raises: ValueError
– Auth token and auth-token issue/expiry time cannot be None/empty.Returns: Returns True if the new auth token is set or False otherwise.
Return type: bool
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