Module to handle the connection to a Mosaiq SQL database and execute SQL queries.


Connect and Query the Mosaiq Database#

pymedphys.mosaiq.connect(hostname: str, port: int = 1433, database: str = 'MOSAIQ', alias: Optional[str] = None, username: Optional[str] = None, password: Optional[str] = None) Connection[source]#

Connect to a Mosaiq SQL server.

The first time running this function on a system will result in a prompt to login to the Mosaiq SQL server. The provided credentials will be stored within the operating system’s password storage facilities. Subsequent calls to this function will pull from that password storage in order to connect.

Can optionally be called as a context manager. This will close the database connection once leaving the context manager.

  • hostname (str) – The IP address or hostname of the SQL server.

  • port (int, optional) – The port at which the SQL server is hosted, by default 1433

  • database (str, optional) – The MSSQL database name, by default "MOSAIQ"

  • alias (Optional[str], optional) – A human readable representation of the server, this is the name of the server presented to the user should there not be credentials already on the machine, by default "hostname:port/database"

  • username (Optional[str], optional) – Provide a username to login to the database with, by default the username is either pulled from the system’s credential storage, or an interactive prompt is used.

  • password (Optional[str], optional) – Provide a password to login to the database with, by default the password is either pulled from the system’s credential storage, or an interactive prompt is used.


connection – A database connection. This connection can be passed to pymedphys.mosaiq.execute() to be able to run queries.

The method close() can be called on this object to close the database connection.

Return type:



See pymedphys.mosaiq.execute() for examples of usage.

pymedphys.mosaiq.execute(connection: Connection, query: str, parameters: Optional[Dict] = None) List[Tuple[str, ...]][source]#

Execute SQL queries on a Mosaiq database.

  • connection (pymedphys.mosaiq.Connection) – A database connection. This can be retrieved by calling pymedphys.mosaiq.connect

  • query (str) – The SQL query to execute. Do not parse Python variables directly into this string. Instead create this string as if you are going to call format on it ( and then utilise the parameters optional argument to this function. That way, the underlying library pymssql will sanitise the parameters to protect against malicious inputs.

  • parameters (Dict, optional) – Parameters to be included within the query. These are sanitised by the underlying pymssql library before being included within the query string, by default None


results – The results from the database query organised so that each row is an item within the returned list.

Return type:

List[Tuple[str, …]]


Directly calling the connection object and listing all patients that have the last name of "PHANTOM".

>>> import pymedphys.mosaiq
>>> connection = pymedphys.mosaiq.connect('msqsql')  
>>> pymedphys.mosaiq.execute(
...     connection,
...     '''
...     SELECT
...         Ident.IDA,
...         Patient.Last_Name,
...         Patient.First_Name
...     FROM Ident, Patient
...     WHERE
...         Patient.Pat_ID1 = Ident.Pat_ID1 AND
...         Patient.Last_Name = %(last_name)s
...     ''',
...     {"last_name": "PHANTOM"},
... )  
[('654324', 'PHANTOM', 'CATPHAN'),
 ('944444', 'PHANTOM', 'DELTA4'),
 ('654321', 'PHANTOM', 'PELVIS'),
 ('012534', 'PHANTOM', 'QUASAR4D'),
 ('987654', 'PHANTOM', 'RESPIRATORY'),
 ('654325', 'PHANTOM', 'RW3')]

Connecting via a context manager and using pandas to present the results as a table.

>>> import pandas as pd
>>> import pymedphys.mosaiq
>>> with pymedphys.mosaiq.connect('msqsql') as connection:  
...     results = pymedphys.mosaiq.execute(
...         connection,
...         '''
...         SELECT
...             Ident.IDA,
...             Chklist.Due_DtTm
...         FROM Chklist, Staff, Ident
...         WHERE
...             Chklist.Pat_ID1 = Ident.Pat_ID1 AND
...             Staff.Staff_ID = Chklist.Rsp_Staff_ID AND
...             Staff.Last_Name = %(qcl_location)s AND
...             Chklist.Complete = 0
...         ''',
...         {"qcl_location": "Physics_Check"},
...     )
>>> pd.DataFrame(  
...     data=results,
...     columns=[
...         "patient_id",
...         "due",
...     ],
... )
  patient_id                 due
0     000000 2021-02-01 23:59:59
1     000001 2021-02-01 23:59:59
2     000002 2021-02-01 23:59:59
3     000003 2021-03-08 23:59:59