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https://issues.apache.org/jira/browse/BEAM-7926?focusedWorklogId=332774&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-332774
]
ASF GitHub Bot logged work on BEAM-7926:
----------------------------------------
Author: ASF GitHub Bot
Created on: 23/Oct/19 18:32
Start Date: 23/Oct/19 18:32
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #9741: [BEAM-7926]
Visualize PCollection
URL: https://github.com/apache/beam/pull/9741#discussion_r338210890
##########
File path:
sdks/python/apache_beam/runners/interactive/display/pcoll_visualization.py
##########
@@ -0,0 +1,279 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""Module visualizes PCollection data.
+
+For internal use only; no backwards-compatibility guarantees.
+Only works with Python 3.5+.
+"""
+from __future__ import absolute_import
+
+import base64
+import logging
+from datetime import timedelta
+
+from pandas.io.json import json_normalize
+
+from apache_beam import pvalue
+from apache_beam.runners.interactive import interactive_environment as ie
+from apache_beam.runners.interactive import pipeline_instrument as instr
+
+# jsons doesn't support < Python 3.5. Work around with json for legacy tests.
+# TODO(BEAM-8288): clean up once Py2 is deprecated from Beam.
+try:
+ import jsons
+ _pv_jsons_load = jsons.load
+ _pv_jsons_dump = jsons.dump
+except ImportError:
+ import json
+ _pv_jsons_load = json.load
+ _pv_jsons_dump = json.dump
+
+try:
+ from facets_overview.generic_feature_statistics_generator import
GenericFeatureStatisticsGenerator
+ _facets_gfsg_ready = True
+except ImportError:
+ _facets_gfsg_ready = False
+
+try:
+ from IPython.core.display import HTML
+ from IPython.core.display import Javascript
+ from IPython.core.display import display
+ from IPython.core.display import display_javascript
+ from IPython.core.display import update_display
+ _ipython_ready = True
+except ImportError:
+ _ipython_ready = False
+
+try:
+ from timeloop import Timeloop
+ _tl_ready = True
+except ImportError:
+ _tl_ready = False
+
+# 1-d types that need additional normalization to be compatible with DataFrame.
+_one_dimension_types = (int, float, str, bool, list, tuple)
+
+_DIVE_SCRIPT_TEMPLATE = """
+ document.querySelector("#{display_id}").data = {jsonstr};"""
+_DIVE_HTML_TEMPLATE = """
+ <script
src="https://cdnjs.cloudflare.com/ajax/libs/webcomponentsjs/1.3.3/webcomponents-lite.js";></script>
Review comment:
The `facets` templates originate from examples in notebooks shared among the
OSS community.
The `jquery` template simply uses a jquery DataTable widget.
For unittest, the logic of each template is too simple that there is nothing
really to be tested.
The logic I've added to set display_id and update existing widgets have been
unittested.
We'll have some integration test later to execute notebook and verify output
area. Such integration test framework is being developed by some other team.
We'll merge our efforts there.
For manual test, I've manually tested them from notebook. I can attach png
and gif if needed.
Off the topic:
In future PRs, we might have `%%javascript` magic involved in the python
code. Then we can have some library such as `js2py` for javascript unittests in
Python.
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Issue Time Tracking
-------------------
Worklog Id: (was: 332774)
Time Spent: 11.5h (was: 11h 20m)
> Visualize PCollection with Interactive Beam
> -------------------------------------------
>
> Key: BEAM-7926
> URL: https://issues.apache.org/jira/browse/BEAM-7926
> Project: Beam
> Issue Type: New Feature
> Components: runner-py-interactive
> Reporter: Ning Kang
> Assignee: Ning Kang
> Priority: Major
> Time Spent: 11.5h
> Remaining Estimate: 0h
>
> Support auto plotting / charting of materialized data of a given PCollection
> with Interactive Beam.
> Say an Interactive Beam pipeline defined as
> p = create_pipeline()
> pcoll = p | 'Transform' >> transform()
> The use can call a single function and get auto-magical charting of the data
> as materialized pcoll.
> e.g., visualize(pcoll)
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