|Direct provider||Read||Finbourne||Provided with LUSID|
Note: The LUSID user running the query must have sufficient access control permissions to both use the provider and enumerate target files and folders in Drive. This should automatically be the case if you are the domain owner.
The query returns a table of data consisting of one row and one column per file, in the order multiple files are read (if the case). Note you can use this provider in conjunction with Tools.JsonExpand to read data in from JSON files stored in Drive and parse the JSON into a table of constituent data objects.
Drive.RawText has options that enable you to filter or refine a query.
Note: The --file option is mandatory.
An option takes the form --<option>=<value>, for example --file=meeting.txt. Note no spaces are allowed either side of the = operator.
If an option:
- Takes a boolean value, then specifying that option (for example --addFileName) sets it to True; omitting the option specifies False.
- Takes multiple string values, then specify a comma-separated list.
To see a help screen of available options, their data types, default values, and an explanation for each, run the following query using a suitable tool:
In the following examples, the select * from @x syntax at the end prints the table of data assembled by the query.
Note: For more examples, try the Luminesce Github repo.
Example 1: Extract data from a particular text file
Example 2: Extract data from a matching text file
In this example, @@today is a scalar variable that must resolve to exactly one column and one row of data.
Example 3: Extract data from multiple text files matched using a regular expression
If --file is a folder in Drive, you must specify the --folderFilter option with a regular expression to nominate one or more files to read.
In this example, data is extracted from three files meeting-1.txt, meeting-2.txt and meeting-3.txt, but not from meeting-4.txt. The --addFileName option adds an extra column to the table of results showing the source of each record.
In this example, data is extracted from any file with a Meeting_ prefix, 8 digits, an underscore, and then 6 digits, for example Meeting_01072021_123456.txt.
Example 4: Extract data from multiple files stored in a ZIP archive
In this example, meetings.zip is stored in the root Drive folder; data is extracted from any .txt file within it that just has alphabetic characters in its file name.