Session: configuring OneTick databases and ACL

onetick-py provides flexible tools for managing sessions and importing both existing and temporary databases.

Creating session

Session could be created via otp.Session class object.

session = otp.Session()
# make required queries
session.close()

If you want override default temporary config, you can either pass path to config file or otp.Config object as otp.Session config constructor parameter.

config = otp.Config()
session = otp.Session(config)

To avoid manually closing session, you can create it using context manager.

with otp.Session(config) as session:
    # make required queries

Setting up ACL

By default, a temporary generated otp.session.ACL object is created for every otp.Config and respectively for each session.

However you could pass path to ACL configuration file if you need to load custom ACL.

acl = otp.session.ACL('path/to/acl/config')
config = otp.Config(acl=acl)
session = otp.Session(config)

You can also add entities to the ACL by using otp.session.ACL.add method or remove entities using otp.session.ACL.remove.

session.acl.add(otp.session.ACL.User('new_user'))
session.acl.remove(otp.session.ACL.User('old_user'))

Creating temporary database

To create and add a temporary database to the locator, just create an otp.DB object and pass it to the otp.Session.use method.

>>> db = otp.DB('DB_NAME')
>>> session.use(db)  

To add data to temporary database use otp.DB.add method:

>>> db.add(otp.Ticks(A=[1, 2, 3]), date=otp.dt(2003, 1, 1), symbol='SYM', tick_type='TT')

Alternatively, if you already have the data you want to add to the database, you could pass onetick.py.Source object as onetick.py.DB constructor second parameter:

>>> data = otp.Ticks(A=[1, 2, 3])
>>> db = otp.DB('DB_NAME', data)
>>> session.use(db)  

In fact, this is the only way to initialize temporary database with a raw Pandas dataframe.

Working with existing databases

Adding an existing database to the locator almost the same, as for temporary database. However, you need to specify locations to load database from via db_locations parameter.

>>> db = otp.DB('NYSE_TAQ', db_locations=[{'location': '/home/user/data/NYSE_TAQ'}])
>>> session.use(db)  

Additional locator configuration variables could be set via db_locations and db_properties parameters, for location and db sections of database description in a locator configuration file correspondingly.

>>> db = otp.DB(
...     'TEST_DB',
...     db_properties={
...         'symbology': 'SYM',
...         'tick_timestamp_type': 'NANOS',
...     },
...     db_locations=[{
...         'access_method': otp.core.db_constants.access_method.FILE,
...         'location': '/path/to/test_db/',
...         'start_time': datetime(year=2003, month=1, day=1),
...         'end_time': datetime(year=2023, month=1, day=1),
...     }],
... )

See OneTick Locator Variables OneTick documentation for available locator configuration variables.

Derived databases

Derived databases could be added to the locator like a regular database. Of course, a parent database must be added to create a derived database.

>>> db = otp.DB('SOME_DB')
>>> session.use(db)  
>>> derived_db = otp.DB('SOME_DB//DERIVED_LABEL')
>>> session.use(derived_db)  

You can also add data to derived database.

>>> data = otp.Ticks(A=[1, 2, 3])
>>> derived_db = otp.DB('SOME_DB//DERIVED_LABEL')
>>> session.use(derived_db)  
>>> derived_db.add(data)  

See Derived Databases OneTick documentation for more info about derived databases.

Useful types of sessions

There are some other types of session classes, that are inherited from base otp.Session class, but provide some additional functionality.

otp.TestSession

otp.TestSession sets up some default onetick.py configuration values and is useful for the purposes of quickly setting up environment to test some simple queries.