README.md

@@ -3,4 +3,4 @@
 
 Wutta Framework for data import/export and real-time sync
 
-See docs at https://docs.wuttaproject.org/wuttasync/
+See docs at https://rattailproject.org/docs/wuttasync/

docs/conf.py

@@ -30,7 +30,6 @@ exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
 
 intersphinx_mapping = {
     'python': ('https://docs.python.org/3/', None),
-    'rattail-manual': ('https://docs.wuttaproject.org/rattail-manual/', None),
     'wuttjamaican': ('https://docs.wuttaproject.org/wuttjamaican/', None),
 }
 

docs/index.rst

@@ -2,51 +2,22 @@
 WuttaSync
 =========
 
-This provides a "batteries included" way to handle data sync between
+This package adds data import/export and real-time sync utilities for
-arbitrary source and target.
+the `Wutta Framework <https://wuttaproject.org>`_.
 
-This builds / depends on :doc:`WuttJamaican <wuttjamaican:index>`, for
+*(NB. the real-time sync has not been added yet.)*
-sake of a common :term:`config object` and :term:`handler` interface.
-It was originally designed for import to / export from the :term:`app
-database` but **both** the source and target can be "anything" -
-e.g. CSV or Excel file, cloud API, another DB.
 
-The basic idea is as follows:
+The primary use cases in mind are:
 
-* read a data set from "source"
+* keep operational data in sync between various business systems
-* read corresonding data from "target"
+* import data from user-specified file
-* compare the two data sets
+* export to file
-* where they differ, create/update/delete records on the target
 
-Although in some cases (e.g. export to CSV) the target has no
+This isn't really meant to replace typical ETL tools; it is smaller
-meaningful data so all source records are "created" on / written to
+scale and (hopefully) more flexible.
-the target.
 
-.. note::
+While it of course supports import/export to/from the Wutta :term:`app
-
+database`, it may be used for any "source → target" data flow.
-   You may already have guessed, that this approach may not work for
-   "big data" - and indeed, it is designed for "small" data sets,
-   ideally 500K records or smaller.  It reads both (source/target)
-   data sets into memory so that is the limiting factor.
-
-   You can work around this to some extent, by limiting the data sets
-   to a particular date range (or other "partitionable" aspect of the
-   data), and only syncing that portion.
-
-   However this is not meant to be an ETL engine involving a data
-   lake/warehouse.  It is for more "practical" concerns where some
-   disparate "systems" must be kept in sync, or basic import from /
-   export to file.
-
-The general "source → target" concept can be used for both import and
-export, since "everything is an import" from the target's perspective.
-
-In addition to the import/export framework proper, a CLI framework is
-also provided.
-
-A "real-time sync" framework is also (eventually) planned, similar to
-the one developed in the Rattail Project;
-cf. :doc:`rattail-manual:data/sync/index`.
 
 
 .. toctree::

src/wuttasync/importing/base.py

@@ -563,7 +563,6 @@ class Importer:
 
         :returns: List of target records which were deleted.
         """
-        model_title = self.get_model_title()
         deleted = []
         changes = changes or 0
 
@@ -578,7 +577,6 @@ class Importer:
             obj = cached['object']
 
             # delete target object
-            log.debug("deleting %s %s: %s", model_title, key, obj)
             if self.delete_target_object(obj):
                 deleted.append((obj, cached['data']))