1.7.8: removal of threaded request timeouts, #77

Author: Andrew Schonfeld

.circleci/config.yml

@@ -5,7 +5,7 @@ defaults: &defaults
       CIRCLE_ARTIFACTS: /tmp/circleci-artifacts
       CIRCLE_TEST_REPORTS: /tmp/circleci-test-results
       CODECOV_TOKEN: b0d35139-0a75-427a-907b-2c78a762f8f0
-      VERSION: 1.7.7
+      VERSION: 1.7.8
       PANDOC_RELEASES_URL: https://github.com/jgm/pandoc/releases
     steps:
     - checkout

CHANGES.md

@@ -1,11 +1,14 @@
 ## Changelog
 
+### 1.7.8 (2020-2-22)
+ * [#77](https://github.com/man-group/dtale/issues/77), removal of multiprocessed timeouts
+
 ### 1.7.7 (2020-2-22)
- * centralized global state, #77
+ * centralized global state
 
 ### 1.7.6 (2020-2-21)
  * allowing the usage of context variables within filters
- * #64, handling for loading duplicate data to dtale.show
+ * [#64](https://github.com/man-group/dtale/issues/64), handling for loading duplicate data to dtale.show
  * updated dtale.instances() to print urls rather than show all instances
  * removal of Dash "Export to png" function
  * passing data grid queries to chart page as default

README.md

@@ -19,7 +19,7 @@ D-Tale is the combination of a Flask back-end and a React front-end to bring you
 D-Tale was the product of a SAS to Python conversion.  What was originally a perl script wrapper on top of SAS's `insight` function is now a lightweight web client on top of Pandas data structures.
 
 ## In The News
- - [Man Institute](https://www.man.com/maninstitute/d-tale)
+ - [Man Institute](https://www.man.com/maninstitute/d-tale) (warning: contains deprecated functionality)
  - [Python Bytes](https://pythonbytes.fm/episodes/show/169/jupyter-notebooks-natively-on-your-ipad)
 
 ## Contents
@@ -102,7 +102,7 @@ d._url  # the url to access the process
 
 d2 = dtale.get_instance(d._data_id)  # returns a new reference to the instance running at that data_id
 
-dtale.instances()  # returns a dictionary of all instances available, this would be { 1: ... }
+dtale.instances()  # prints a list of all ids & urls of running D-Tale sessions
 
 ```
 
@@ -321,6 +321,13 @@ With a bar chart that only has a single Y-Axis you have the ability to sort the
 
 This is a very powerful feature with many more features that could be offered (linked subplots, different statistical aggregations, etc...) so please submit issues :)
 
+**Disclaimer: Long Running Chart Requests**
+
+If you choose to build a chart that requires a lot of computational resources then it will take some time to run.  Based on the way Flask & plotly/dash interact this will block you from performing any other request until it completes.  There are two courses of action in this situation:
+
+1) Restart your jupyter notebook kernel or python console
+2) Open a new D-Tale session on a different port than the current session.  You can do that with the following command: `dtale.show(df, port=[any open port], force=True)`
+
 If you miss the legacy (non-plotly/dash) charts, not to worry!  They are still available from the link in the upper-right corner, but on for a limited time...
 Here is the documentation for those: [Legacy Charts](https://github.com/man-group/dtale/blob/master/docs/LEGACY_CHARTS.md)
 
@@ -676,14 +683,15 @@ Original concept and implementation: [Andrew Schonfeld](https://github.com/ascho
 
 Contributors:
 
- * [Wilfred Hughes](https://github.com/Wilfred)
+ * [Phillip Dupuis](https://github.com/phillipdupuis)
  * [Dominik Christ](https://github.com/DominikMChrist)
  * [Chris Boddy](https://github.com/cboddy)
  * [Jason Holden](https://github.com/jasonkholden)
  * [Tom Taylor](https://github.com/TomTaylorLondon)
- * [Vincent Riemer](https://github.com/vincentriemer)
  * [Fernando Saravia Rajal](https://github.com/fersarr)
+ * [Wilfred Hughes](https://github.com/Wilfred)
  * Mike Kelly
+ * [Vincent Riemer](https://github.com/vincentriemer)
  * [Youssef Habchi](http://youssef-habchi.com/) - title font
  * ... and many others ...
 

docker/2_7/Dockerfile

@@ -44,4 +44,4 @@ WORKDIR /app
 
 RUN set -eux \
   ; . /root/.bashrc \
-  ; easy_install dtale-1.7.7-py2.7.egg
+  ; easy_install dtale-1.7.8-py2.7.egg

docker/3_6/Dockerfile

@@ -44,4 +44,4 @@ WORKDIR /app
 
 RUN set -eux \
   ; . /root/.bashrc \
-  ; easy_install dtale-1.7.7-py3.7.egg
+  ; easy_install dtale-1.7.8-py3.7.egg

docs/source/conf.py

@@ -64,9 +64,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = u'1.7.7'
+version = u'1.7.8'
 # The full version, including alpha/beta/rc tags.
-release = u'1.7.7'
+release = u'1.7.8'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

dtale/app.py

@@ -533,8 +533,12 @@ def instances():
     Prints all urls to the current pieces of data being viewed
     """
     curr_data = global_state.get_data()
+
     if len(curr_data):
-        print('\n'.join([DtaleData(data_id, build_url(ACTIVE_PORT, ACTIVE_HOST)).main_url() for data_id in curr_data]))
+        def _instance_msg(data_id):
+            url = DtaleData(data_id, build_url(ACTIVE_PORT, ACTIVE_HOST)).main_url()
+            return '{}:\t{}'.format(data_id, url)
+        print('\n'.join(['ID\tURL'] + [_instance_msg(data_id) for data_id in curr_data]))
     else:
         print('currently no running instances...')
 

dtale/dash_application/charts.py

@@ -20,8 +20,7 @@
 from dtale.dash_application.layout import (AGGS, build_error,
                                            update_label_for_freq)
 from dtale.utils import (classify_type, dict_merge, divide_chunks,
-                         flatten_lists, get_dtypes, make_list,
-                         make_timeout_request, run_query)
+                         flatten_lists, get_dtypes, make_list, run_query)
 from dtale.views import build_chart as build_chart_data
 
 
@@ -736,14 +735,6 @@ def build_figure_data(data_id, chart_type=None, query=None, x=None, y=None, z=No
         return dict(error=str(e), traceback=str(traceback.format_exc()))
 
 
-def threaded_build_figure_data(data_id=None, result_store=None, **inputs):
-    result_store.append(build_figure_data(data_id, **inputs))
-
-
-def threaded_heatmap_builder(data_id=None, result_store=None, **inputs):
-    result_store.append(heatmap_builder(data_id, **inputs))
-
-
 def build_chart(data_id=None, **inputs):
     """
     Factory method that forks off into the different chart building methods (heatmaps are handled separately)
@@ -767,12 +758,10 @@ def build_chart(data_id=None, **inputs):
     """
     try:
         if inputs.get('chart_type') == 'heatmap':
-            data = make_timeout_request(threaded_heatmap_builder, kwargs=dict_merge(dict(data_id=data_id), inputs))
-            data = data.pop()
+            data = heatmap_builder(data_id, **inputs)
             return data, None
 
-        data = make_timeout_request(threaded_build_figure_data, kwargs=dict_merge(dict(data_id=data_id), inputs))
-        data = data.pop()
+        data = build_figure_data(data_id, **inputs)
         if data is None:
             return None, None
 

dtale/utils.py

@@ -8,7 +8,6 @@
 import time
 from builtins import map, object
 from logging import getLogger
-from multiprocessing import Manager, Process
 
 from flask import jsonify as _jsonify
 
@@ -732,35 +731,6 @@ def divide_chunks(l, n):
         yield l[i:i + n]
 
 
-def make_timeout_request(target, args=None, kwargs=None, timeout=60):
-    """
-    Helper function to wrap 'target' method in a timeout.  This will guard against long requests making the app
-    unusable.
-
-    :param target: function to be wrapped in timeout
-    :type target: func
-    :param kwargs: positional arguments to the function
-    :type kwargs: iterable, optional
-    :param kwargs: keyword arguments to the function
-    :type kwargs: dict, optional
-    :param timeout: seconds before a timeout exception is thrown, default is 60
-    :type timeout: int, optional
-    :return: output from target function otherwise throw a timeout exception
-    """
-    manager = Manager()
-    results = manager.list()
-    worker = Process(target=target, args=args or (), kwargs=dict_merge(kwargs or {}, dict(result_store=results)))
-    worker.start()
-    worker.join(timeout)
-    if worker.is_alive():
-        worker.terminate()
-        worker.join()
-        raise Exception(
-            'Request took longer than {} seconds. Please try adding additional filtering...'.format(timeout)
-        )
-    return results
-
-
 def run_query(df, query, context_vars):
     """
     Utility function for running :func:`pandas:pandas.DataFrame.query` . This function contains extra logic to

package.json

@@ -1,6 +1,6 @@
 {
   "name": "dtale",
-  "version": "1.7.7",
+  "version": "1.7.8",
   "description": "Visualizer for Pandas Data Structures",
   "main": "main.js",
   "directories": {