Easy-to-use Python interface for Seeq
The seeq-spy Python module is the recommended programming interface for interacting with the Seeq Server.
Use of this module requires a Seeq Data Lab license.
Documentation can be found at https://python-docs.seeq.com.
The Seeq SPy module is a friendly set of functions that are optimized for use with Jupyter, Pandas and NumPy.
The SPy module is the best choice if you're trying to do any of the following:
Use of the SPy module requires Python 3.7 or later.
SPy version 187 and higher is compatible with Pandas 2.x.
To start exploring the SPy module, execute the following lines of code in Jupyter:
from seeq import spy
spy.docs.copy()
Your Jupyter folder will now contain a SPy Documentation
folder that has a Tutorial and Command Reference
notebook that will walk you through common activities.
For more advanced tasks, you may need to use the seeq.sdk
module directly as described at
https://pypi.org/project/seeq.
The seeq-spy
module can/should be upgraded separately from the main seeq
module by doing pip install -U seeq-spy
. It is written to be compatible with Seeq Server version R60 and later.
In SPy v183 and later, the DataFrame metadata that is described in the Properties stored in the output DataFrame
section of the spy.search.ipynb documentation notebook has been moved into a top-level spy
namespace on the
DataFrame (as opposed to each variable being at the top level). For example, in order to access the function name that
was used to produce the DataFrame, you would use search_df.spy.func
instead of just search_df.func
. This change was
made to avoid collisions with native DataFrame properties and functions.
In SPy v183 and later, spy.assets.build()
conducts the build process in two passes instead of one. This generally
has no repercussions for your Asset- or Mixin-derived classes, but you will notice that
@Asset.Component
-decorated functions are called twice per asset. In the first pass, the framework is expecting the
component asset classes to be instantiated, and in the second pass it is expecting all attributes to be evaluated and
built. This new behavior generally does not require you to make any changes to your classes, with one exception: If you
were using @Asset.Component
as a means by which you could generate multiple signals/conditions/scalars/metrics from a
single function, you should instead use @Asset.Attribute
to achieve that.
In Seeq Server R22.0.49.00, the ability to schedule the update of an Organizer Topic was added. As a result, much of the internals of how Organizer Topic embedded content and date ranges are represented changed.
If you have used spy.workbooks.save()
in R22.0.48.XX and earlier to save a set of Organizer Topic workbooks to disk,
you will not be able to use those files in R22.0.49.00 and later.
Live Docs must now be specified by a schedule
on the TopicDocument
object. The @Asset.DateRange
decorator no longer honors the Auto Refresh Rate
property. To specify a Live Doc, you must specify a
schedule
dict for a TopicDocument by setting document.schedule['Background'] = False
and then specifying a Cron
expression like schedule['Cron Schedule'] = ['*/30 * * * * *']
(every thirty seconds). Alternatively, you can specify
a Scheduled Doc by setting document.schedule['Background'] = True
.