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Table of Contents

notes and questions

Notes:

  • probably will need a class that is an Article_Data container - reference to Article_Data, and then all the logic to process the entities and relations contained within.

Questions:

  • Do we want an Identifier Type separate from Entity and Relation identifiers? I think we do, so we can specify the entity type(s) a given identifier should be used on.

    • Created abstract one, and created a concrete entity identifier type. Will create one for relation identifiers if needed.

Setup





In [1]:



    


me = "sourcenet-to-context"

Setup - Debug





In [2]:



    


debug_flag = False

Setup - Imports





In [15]:



    


import datetime
from django.db.models import Avg, Max, Min
from django.utils.text import slugify
import gc
import json
import logging
import six

Setup - working folder paths





In [4]:



    


%pwd



    


















    
Out[4]:








'/home/jonathanmorgan/work/django/research/work/phd_work/analysis'

















In [5]:



    


# current working folder
current_working_folder = "/home/jonathanmorgan/work/django/research/work/phd_work/analysis"
current_datetime = datetime.datetime.now()
current_date_string = current_datetime.strftime( "%Y-%m-%d-%H-%M-%S" )

Setup - logging

configure logging for this notebook's kernel (If you do not run this cell, you'll get the django application's logging configuration.





In [6]:



    


logging_file_name = "{}/logs/{}-{}.log.txt".format( current_working_folder, me, current_date_string )
logging.basicConfig(
    level = logging.INFO,
    format = '%(asctime)s - %(levelname)s - %(name)s - %(message)s',
    filename = logging_file_name,
    filemode = 'w' # set to 'a' if you want to append, rather than overwrite each time.
)
print( "Logging initialized, to {}".format( logging_file_name ) )



    


















    






Logging initialized, to /home/jonathanmorgan/work/django/research/work/phd_work/analysis/sourcenet-to-context-2019-11-29-01-56-55.log.txt

Setup - virtualenv jupyter kernel

If you are using a virtualenv, make sure that you:

  • have installed your virtualenv as a kernel.
  • choose the kernel for your virtualenv as the kernel for your notebook (Kernel --> Change kernel).

Since I use a virtualenv, need to get that activated somehow inside this notebook. One option is to run ../dev/wsgi.py in this notebook, to configure the python environment manually as if you had activated the sourcenet virtualenv. To do this, you'd make a code cell that contains:

%run ../dev/wsgi.py

This is sketchy, however, because of the changes it makes to your Python environment within the context of whatever your current kernel is. I'd worry about collisions with the actual Python 3 kernel. Better, one can install their virtualenv as a separate kernel. Steps:

  • activate your virtualenv:

      workon research

  • in your virtualenv, install the package ipykernel.

      pip install ipykernel

  • use the ipykernel python program to install the current environment as a kernel:

      python -m ipykernel install --user --name <env_name> --display-name "<display_name>"

    sourcenet example:

      python -m ipykernel install --user --name sourcenet --display-name "research (Python 3)"

More details: http://ipython.readthedocs.io/en/stable/install/kernel_install.html

Setup - Initialize Django

First, initialize my dev django project, so I can run code in this notebook that references my django models and can talk to the database using my project's settings.





In [7]:



    


# init django
django_init_folder = "/home/jonathanmorgan/work/django/research/work/phd_work"
django_init_path = "django_init.py"
if( ( django_init_folder is not None ) and ( django_init_folder != "" ) ):
    
    # add folder to front of path.
    django_init_path = "{}/{}".format( django_init_folder, django_init_path )
    
#-- END check to see if django_init folder. --#



    











In [8]:



    


%run $django_init_path



    


















    






django initialized at 2019-11-29 01:57:00.635825

















In [9]:



    


# context imports
from context.models import Entity
from context.models import Entity_Identifier_Type
from context.models import Entity_Identifier
from context.models import Entity_Type

# context_text imports
from context_text.article_coding.article_coding import ArticleCoder
from context_text.article_coding.article_coding import ArticleCoding
from context_text.article_coding.open_calais_v2.open_calais_v2_article_coder import OpenCalaisV2ArticleCoder
from context_text.collectors.newsbank.newspapers.GRPB import GRPB
from context_text.collectors.newsbank.newspapers.DTNB import DTNB
from context_text.export.to_context_base.export_to_context import ExportToContext
from context_text.models import Article
from context_text.models import Article_Subject
from context_text.models import Newspaper
from context_text.shared.context_text_base import ContextTextBase

Setup - ExportToContext instance

Make instance, set instance variables.





In [10]:



    


my_exporter = ExportToContext()

# no variables to set, yet...
my_exporter.set_article_uuid_id_type_name( ExportToContext.ENTITY_ID_TYPE_ARTICLE_NEWSBANK_ID )



    


















    
Out[10]:








<Entity_Identifier_Type: 4 - article_newsbank_id - Newsbank - ( article )>

Setup - Initialize LoggingHelper

Create a LoggingHelper instance to use to log debug and also print at the same time.

Preconditions: Must be run after Django is initialized, since python_utilities is in the django path.





In [11]:



    


# python_utilities
from python_utilities.logging.logging_helper import LoggingHelper

# init
my_logging_helper = LoggingHelper()
my_logging_helper.set_logger_name( me )
log_message = None

load sourcenet data into context

logic:

  • get all Article_Data created by automated coder, open calais coder type.

  • for each:

    • Article processing:

      • look for article entity in context. If not created, create one of type "article". Store the sourcenet ID as identifier of type "article_sourcenet_id".
      • Store the ID and entity reference for the Article (in object? Should I make a place for the article to hold an Entity ID?).
      • check to see if the newspaper has an entity (using its sourcenet ID as the lookup identifier). If not, create one.

    • Person processing:

      • Add all people who are either reporters/authors or subjects to context as entities of type "person", with identifier of type person_sourcenet_id set to their internal django/database "id", and with identifier of type person_open_calais_uuid set to their OpenCalais ID, if they have one. If they have any other types of IDs, add them too, untyped. Once entity is created, store ForeignKey of entity in Person record.

      • Author/Reporter processing:

        • look for each author's person entity. If not found, create one.

      • Subject/Source processing:

        • look for a person entity for each subject/source. If not found, create one.

    • Relations - create the following:

      • from newspaper

        • newspaper_reporter - Reporter at a newspaper, evidence of which is byline on an article in that newspaper. FROM newspaper TO person (reporter) THROUGH article.
        • newspaper_source - Person quoted in an article published by a newspaper. FROM newspaper TO person (source) THROUGH article.
        • newspaper_subject - Subject of an article published in a given newspaper. FROM newspaper TO person (subject, including sources) THROUGH article.
        • newspaper_article - Article published in a particular newspaper. FROM newspaper TO article.

      • from article

        • author - Author/Reporter of an article - FROM article TO reporter.
        • subject - Subject of a story. FROM article TO subject person.
        • source - Source quoted in an article - FROM article TO source person.

      • through article

        • article_container - Parent for relations based on entities being mentioned in the same article. To start, just people, but eventually, for example, could also include location.
        • mentioned - Mentioned in an article. FROM reporter/author TO subject THROUGH article.
        • quoted - The "from" person quoted the "to" person in a publication. FROM reporter TO source THROUGH article.
        • same_article_sources - Sources in the same article, FROM source person TO source person THROUGH article.
        • same_article_subjects - Two people who are in a particular article together (includes subjects and sources).
        • shared_byline - Shared Byline on an article - joint authors - FROM author TO author THROUGH article.

Relations broken out by person type:

  • For all reporters/authors:

    • create a relation of type "author" between the article's entity (FROM) and the entity of the person (TO) for each author.
    • if multiple authors, for each pair of authors, create a relation of type "shared_byline" between the two (it is undirected), THROUGH the article.

  • For all subjects, including sources:

    • create a relation of type "subject" between the article's entity (FROM) and the entity of the subject person (TO).
    • if multiple subjects, for each pair of subjects, create a relation of type "same_article_subjects" between the two (it is undirected), THROUGH the article.
    • create a relation of type "mentioned" between each of the article's authors (FROM) and the subject (TO), THROUGH the article.

  • For all sources

    • create a relation of type "source" between the article's entity and the entity for the source person.
    • if multiple sources, for each pair of sources, create a relation of type "same_article_sources" between the two (it is undirected), THROUGH the article.
    • create a relation of type "quoted" between each of the article's authors (FROM) and the source (TO), THROUGH the article.

Convenience methods:

  • method to find entity - based on type and identifier (accept all the fields that make sense, including optional identifier type instance).
  • method to find relation - based on type, etc.

Notes:

  • all ties are undirected.
  • relations can have three foreign keys into Entity - FROM, TO, and THROUGH (for a containing relationship, like the article that included two sources that we are relating).

Retrieve Article instances

Before we do anything else, need to be able to pull back all the articles whose data we want to load into the context store.





In [12]:



    


# look for publications that have article data:
# - coded by automated coder
# - with coder type of "OpenCalais_REST_API_v2"

# get automated coder
automated_coder_user = ContextTextBase.get_automated_coding_user()

log_message = "{} - Loaded automated user: {}, id = {}".format( datetime.datetime.now(), automated_coder_user, automated_coder_user.id )
my_logging_helper.output_message( log_message, do_print_IN = True, log_level_code_IN = logging.INFO )



    


















    






2019-11-29 01:57:07.200553 - Loaded automated user: automated, id = 2

















In [13]:



    


# find articles with Article_Data created by the automated user...
article_qs = Article.objects.filter( article_data__coder = automated_coder_user )

# ...and specifically coded using OpenCalais V2...
article_qs = article_qs.filter( article_data__coder_type = OpenCalaisV2ArticleCoder.CONFIG_APPLICATION )

# ...and finally, we just want the distinct articles by ID.
article_qs = article_qs.order_by( "id" ).distinct( "id" )

# count?
article_count = article_qs.count()
log_message = "Found {} articles".format( article_count )
my_logging_helper.output_message( log_message, do_print_IN = True, log_level_code_IN = logging.INFO )



    


















    






Found 43843 articles

build load code and unit tests

Testing

First, make unit tests to test convenience methods added to the following models, in context/tests/models/:

  • // Entity_Identifier_Type - test_Entity_Identifier_Type_model.py
  • // Entity_Identifier - test_Entity_Identifier_model.py
  • // Entity - test_Entity_model.py

Also, // move instance creation class methods along with their constants over into "TestHelper" from test_Entity_Identifier_model.py, so they can be re-used across test classes.

To run: python manage.py test context.tests

In test data:

  • article 21925:

    • Article_Data: SELECT * FROM context_text_article_data WHERE article_id = 21925;

TODO:

  • test_entity_model.py

    • test_get_entity_for_identifier

  • test_export_to_context.py

    • test_get_article_uuid_id_type
    • test_set_article_uuid_id_type_name

Load data from Article instances

Now, we actually load the data...





In [14]:



    


result = my_exporter.process_articles( article_qs )



    


















    






In create_q_filter_automated_by_coder_type: automated coder user: 2 - automated
----> Processed 100 of 43843 articles at 2019-11-26 16:44:10.194920 ( elapsed: 0:02:04.258806; average: 0:00:01.242588 )
----> Processed 200 of 43843 articles at 2019-11-26 16:46:08.333038 ( elapsed: 0:04:02.396924; average: 0:00:01.211985 )
----> Processed 300 of 43843 articles at 2019-11-26 16:48:03.126190 ( elapsed: 0:05:57.190076; average: 0:00:01.190634 )
----> Processed 400 of 43843 articles at 2019-11-26 16:50:09.831284 ( elapsed: 0:08:03.895170; average: 0:00:01.209738 )
----> Processed 500 of 43843 articles at 2019-11-26 16:52:15.175648 ( elapsed: 0:10:09.239534; average: 0:00:01.218479 )
----> Processed 600 of 43843 articles at 2019-11-26 16:54:02.125858 ( elapsed: 0:11:56.189744; average: 0:00:01.193650 )
----> Processed 700 of 43843 articles at 2019-11-26 16:55:50.575779 ( elapsed: 0:13:44.639665; average: 0:00:01.178057 )
----> Processed 800 of 43843 articles at 2019-11-26 16:57:46.909539 ( elapsed: 0:15:40.973425; average: 0:00:01.176217 )
----> Processed 900 of 43843 articles at 2019-11-26 17:00:16.328511 ( elapsed: 0:18:10.392397; average: 0:00:01.211547 )
----> Processed 1000 of 43843 articles at 2019-11-26 17:02:57.319914 ( elapsed: 0:20:51.383800; average: 0:00:01.251384 )
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----> Processed 10000 of 43843 articles at 2019-11-26 22:21:16.407191 ( elapsed: 5:39:10.471077; average: 0:00:02.035047 )
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----> Processed 19000 of 43843 articles at 2019-11-27 04:24:24.664850 ( elapsed: 11:42:18.728736; average: 0:00:02.217828 )
----> Processed 19100 of 43843 articles at 2019-11-27 04:28:37.008651 ( elapsed: 11:46:31.072537; average: 0:00:02.219428 )
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----> Processed 20600 of 43843 articles at 2019-11-27 05:33:37.457739 ( elapsed: 12:51:31.521625; average: 0:00:02.247161 )
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----> Processed 20900 of 43843 articles at 2019-11-27 05:45:06.855335 ( elapsed: 13:03:00.919221; average: 0:00:02.247891 )
----> Processed 21000 of 43843 articles at 2019-11-27 05:49:21.415407 ( elapsed: 13:07:15.479293; average: 0:00:02.249309 )
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----> Processed 21400 of 43843 articles at 2019-11-27 06:04:12.025584 ( elapsed: 13:22:06.089470; average: 0:00:02.248883 )
----> Processed 21500 of 43843 articles at 2019-11-27 06:08:13.114843 ( elapsed: 13:26:07.178729; average: 0:00:02.249636 )
----> Processed 21600 of 43843 articles at 2019-11-27 06:12:03.038256 ( elapsed: 13:29:57.102142; average: 0:00:02.249866 )
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----> Processed 21900 of 43843 articles at 2019-11-27 06:23:53.873293 ( elapsed: 13:41:47.937179; average: 0:00:02.251504 )
----> Processed 22000 of 43843 articles at 2019-11-27 06:27:58.579119 ( elapsed: 13:45:52.643005; average: 0:00:02.252393 )
----> Processed 22100 of 43843 articles at 2019-11-27 06:32:17.754530 ( elapsed: 13:50:11.818416; average: 0:00:02.253928 )
----> Processed 22200 of 43843 articles at 2019-11-27 06:36:01.559786 ( elapsed: 13:53:55.623672; average: 0:00:02.253857 )
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----> Processed 22400 of 43843 articles at 2019-11-27 06:41:26.021476 ( elapsed: 13:59:20.085362; average: 0:00:02.248218 )
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----> Processed 22900 of 43843 articles at 2019-11-27 07:02:04.023322 ( elapsed: 14:19:58.087208; average: 0:00:02.253192 )
----> Processed 23000 of 43843 articles at 2019-11-27 07:05:12.950269 ( elapsed: 14:23:07.014155; average: 0:00:02.251609 )
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----> Processed 23400 of 43843 articles at 2019-11-27 07:19:20.652794 ( elapsed: 14:37:14.716680; average: 0:00:02.249347 )
----> Processed 23500 of 43843 articles at 2019-11-27 07:22:17.196423 ( elapsed: 14:40:11.260309; average: 0:00:02.247288 )
----> Processed 23600 of 43843 articles at 2019-11-27 07:27:11.519128 ( elapsed: 14:45:05.583014; average: 0:00:02.250237 )
----> Processed 23700 of 43843 articles at 2019-11-27 07:31:07.754683 ( elapsed: 14:49:01.818569; average: 0:00:02.250710 )
----> Processed 23800 of 43843 articles at 2019-11-27 07:34:58.623706 ( elapsed: 14:52:52.687592; average: 0:00:02.250953 )
----> Processed 23900 of 43843 articles at 2019-11-27 07:38:40.303464 ( elapsed: 14:56:34.367350; average: 0:00:02.250810 )
----> Processed 24000 of 43843 articles at 2019-11-27 07:42:27.942899 ( elapsed: 15:00:22.006785; average: 0:00:02.250917 )
----> Processed 24100 of 43843 articles at 2019-11-27 07:46:27.998811 ( elapsed: 15:04:22.062697; average: 0:00:02.251538 )
----> Processed 24200 of 43843 articles at 2019-11-27 07:50:04.374041 ( elapsed: 15:07:58.437927; average: 0:00:02.251175 )
----> Processed 24300 of 43843 articles at 2019-11-27 07:53:33.801056 ( elapsed: 15:11:27.864942; average: 0:00:02.250529 )
----> Processed 24400 of 43843 articles at 2019-11-27 07:56:50.971593 ( elapsed: 15:14:45.035479; average: 0:00:02.249387 )
----> Processed 24500 of 43843 articles at 2019-11-27 08:01:27.671222 ( elapsed: 15:19:21.735108; average: 0:00:02.251499 )
----> Processed 24600 of 43843 articles at 2019-11-27 08:05:36.881437 ( elapsed: 15:23:30.945323; average: 0:00:02.252477 )
----> Processed 24700 of 43843 articles at 2019-11-27 08:09:06.024469 ( elapsed: 15:27:00.088355; average: 0:00:02.251825 )
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----> Processed 28300 of 43843 articles at 2019-11-27 10:42:45.651761 ( elapsed: 18:00:39.715647; average: 0:00:02.291156 )
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----> Processed 28800 of 43843 articles at 2019-11-27 11:02:44.097040 ( elapsed: 18:20:38.160926; average: 0:00:02.292992 )
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----> Processed 34700 of 43843 articles at 2019-11-28 04:40:44.650798 ( elapsed: 1 day, 11:58:38.714684; average: 0:00:03.732528 )
----> Processed 34800 of 43843 articles at 2019-11-28 04:44:39.393107 ( elapsed: 1 day, 12:02:33.456993; average: 0:00:03.728548 )
----> Processed 34900 of 43843 articles at 2019-11-28 04:48:45.776271 ( elapsed: 1 day, 12:06:39.840157; average: 0:00:03.724924 )
----> Processed 35000 of 43843 articles at 2019-11-28 04:54:20.062270 ( elapsed: 1 day, 12:12:14.126156; average: 0:00:03.723832 )
----> Processed 35100 of 43843 articles at 2019-11-28 04:58:09.191835 ( elapsed: 1 day, 12:16:03.255721; average: 0:00:03.719751 )
----> Processed 35200 of 43843 articles at 2019-11-28 05:01:42.879395 ( elapsed: 1 day, 12:19:36.943281; average: 0:00:03.715254 )
----> Processed 35300 of 43843 articles at 2019-11-28 05:05:21.265726 ( elapsed: 1 day, 12:23:15.329612; average: 0:00:03.710916 )
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----> Processed 35500 of 43843 articles at 2019-11-28 05:12:09.740641 ( elapsed: 1 day, 12:30:03.804527; average: 0:00:03.701516 )
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----> Processed 35700 of 43843 articles at 2019-11-28 05:19:18.878518 ( elapsed: 1 day, 12:37:12.942404; average: 0:00:03.692800 )
----> Processed 35800 of 43843 articles at 2019-11-28 05:23:23.408798 ( elapsed: 1 day, 12:41:17.472684; average: 0:00:03.689315 )
----> Processed 35900 of 43843 articles at 2019-11-28 05:27:34.716355 ( elapsed: 1 day, 12:45:28.780241; average: 0:00:03.686038 )
----> Processed 36000 of 43843 articles at 2019-11-28 05:31:38.192090 ( elapsed: 1 day, 12:49:32.255976; average: 0:00:03.682563 )
----> Processed 36100 of 43843 articles at 2019-11-28 05:35:30.481877 ( elapsed: 1 day, 12:53:24.545763; average: 0:00:03.678796 )
----> Processed 36200 of 43843 articles at 2019-11-28 05:38:36.130590 ( elapsed: 1 day, 12:56:30.194476; average: 0:00:03.673762 )
----> Processed 36300 of 43843 articles at 2019-11-28 05:43:07.685630 ( elapsed: 1 day, 13:01:01.749516; average: 0:00:03.671123 )
----> Processed 36400 of 43843 articles at 2019-11-28 05:46:09.482404 ( elapsed: 1 day, 13:04:03.546290; average: 0:00:03.666031 )
----> Processed 36500 of 43843 articles at 2019-11-28 05:49:54.499373 ( elapsed: 1 day, 13:07:48.563259; average: 0:00:03.662152 )
----> Processed 36600 of 43843 articles at 2019-11-28 05:52:52.111700 ( elapsed: 1 day, 13:10:46.175586; average: 0:00:03.656999 )
----> Processed 36700 of 43843 articles at 2019-11-28 05:57:04.509615 ( elapsed: 1 day, 13:14:58.573501; average: 0:00:03.653912 )
----> Processed 36800 of 43843 articles at 2019-11-28 06:00:57.502700 ( elapsed: 1 day, 13:18:51.566586; average: 0:00:03.650314 )
----> Processed 36900 of 43843 articles at 2019-11-28 06:04:59.436075 ( elapsed: 1 day, 13:22:53.499961; average: 0:00:03.646978 )
----> Processed 37000 of 43843 articles at 2019-11-28 06:09:24.884210 ( elapsed: 1 day, 13:27:18.948096; average: 0:00:03.644296 )
----> Processed 37100 of 43843 articles at 2019-11-28 06:14:05.838723 ( elapsed: 1 day, 13:31:59.902609; average: 0:00:03.642046 )
----> Processed 37200 of 43843 articles at 2019-11-28 06:18:35.724023 ( elapsed: 1 day, 13:36:29.787909; average: 0:00:03.639510 )
----> Processed 37300 of 43843 articles at 2019-11-28 06:23:17.061453 ( elapsed: 1 day, 13:41:11.125339; average: 0:00:03.637296 )
----> Processed 37400 of 43843 articles at 2019-11-28 06:27:18.123796 ( elapsed: 1 day, 13:45:12.187682; average: 0:00:03.634016 )
----> Processed 37500 of 43843 articles at 2019-11-28 06:31:18.664400 ( elapsed: 1 day, 13:49:12.728286; average: 0:00:03.630739 )
----> Processed 37600 of 43843 articles at 2019-11-28 06:35:18.760104 ( elapsed: 1 day, 13:53:12.823990; average: 0:00:03.627469 )
----> Processed 37700 of 43843 articles at 2019-11-28 06:39:51.120041 ( elapsed: 1 day, 13:57:45.183927; average: 0:00:03.625071 )
----> Processed 37800 of 43843 articles at 2019-11-28 06:44:12.322462 ( elapsed: 1 day, 14:02:06.386348; average: 0:00:03.622391 )
----> Processed 37900 of 43843 articles at 2019-11-28 06:48:13.892917 ( elapsed: 1 day, 14:06:07.956803; average: 0:00:03.619207 )
----> Processed 38000 of 43843 articles at 2019-11-28 06:52:22.252993 ( elapsed: 1 day, 14:10:16.316879; average: 0:00:03.616219 )
----> Processed 38100 of 43843 articles at 2019-11-28 06:56:41.804399 ( elapsed: 1 day, 14:14:35.868285; average: 0:00:03.613540 )
----> Processed 38200 of 43843 articles at 2019-11-28 07:00:50.398736 ( elapsed: 1 day, 14:18:44.462622; average: 0:00:03.610588 )
----> Processed 38300 of 43843 articles at 2019-11-28 07:05:16.144022 ( elapsed: 1 day, 14:23:10.207908; average: 0:00:03.608099 )
----> Processed 38400 of 43843 articles at 2019-11-28 07:08:49.896132 ( elapsed: 1 day, 14:26:43.960018; average: 0:00:03.604270 )
----> Processed 38500 of 43843 articles at 2019-11-28 07:11:56.811994 ( elapsed: 1 day, 14:29:50.875880; average: 0:00:03.599763 )
----> Processed 38600 of 43843 articles at 2019-11-28 07:15:39.309245 ( elapsed: 1 day, 14:33:33.373131; average: 0:00:03.596201 )
----> Processed 38700 of 43843 articles at 2019-11-28 07:19:21.604200 ( elapsed: 1 day, 14:37:15.668086; average: 0:00:03.592653 )
----> Processed 38800 of 43843 articles at 2019-11-28 07:23:23.446495 ( elapsed: 1 day, 14:41:17.510381; average: 0:00:03.589627 )
----> Processed 38900 of 43843 articles at 2019-11-28 07:26:47.873223 ( elapsed: 1 day, 14:44:41.937109; average: 0:00:03.585654 )
----> Processed 39000 of 43843 articles at 2019-11-28 07:30:20.194072 ( elapsed: 1 day, 14:48:14.257958; average: 0:00:03.581904 )
----> Processed 39100 of 43843 articles at 2019-11-28 07:33:59.777395 ( elapsed: 1 day, 14:51:53.841281; average: 0:00:03.578359 )
----> Processed 39200 of 43843 articles at 2019-11-28 07:38:43.831294 ( elapsed: 1 day, 14:56:37.895180; average: 0:00:03.576477 )
----> Processed 39300 of 43843 articles at 2019-11-28 07:42:45.870673 ( elapsed: 1 day, 15:00:39.934559; average: 0:00:03.573535 )
----> Processed 39400 of 43843 articles at 2019-11-28 07:46:43.623583 ( elapsed: 1 day, 15:04:37.687469; average: 0:00:03.570500 )
----> Processed 39500 of 43843 articles at 2019-11-28 07:50:33.505565 ( elapsed: 1 day, 15:08:27.569451; average: 0:00:03.567280 )
----> Processed 39600 of 43843 articles at 2019-11-28 07:54:37.624303 ( elapsed: 1 day, 15:12:31.688189; average: 0:00:03.564437 )
----> Processed 39700 of 43843 articles at 2019-11-28 07:58:13.488590 ( elapsed: 1 day, 15:16:07.552476; average: 0:00:03.560896 )
----> Processed 39800 of 43843 articles at 2019-11-28 08:02:22.812335 ( elapsed: 1 day, 15:20:16.876221; average: 0:00:03.558213 )
----> Processed 39900 of 43843 articles at 2019-11-28 08:05:58.954811 ( elapsed: 1 day, 15:23:53.018697; average: 0:00:03.554712 )
----> Processed 40000 of 43843 articles at 2019-11-28 08:10:05.119030 ( elapsed: 1 day, 15:27:59.182916; average: 0:00:03.551980 )
----> Processed 40100 of 43843 articles at 2019-11-28 08:13:24.173449 ( elapsed: 1 day, 15:31:18.237335; average: 0:00:03.548086 )
----> Processed 40200 of 43843 articles at 2019-11-28 08:17:30.291790 ( elapsed: 1 day, 15:35:24.355676; average: 0:00:03.545382 )
----> Processed 40300 of 43843 articles at 2019-11-28 08:21:59.255856 ( elapsed: 1 day, 15:39:53.319742; average: 0:00:03.543259 )
----> Processed 40400 of 43843 articles at 2019-11-28 08:25:48.353078 ( elapsed: 1 day, 15:43:42.416964; average: 0:00:03.540159 )
----> Processed 40500 of 43843 articles at 2019-11-28 08:31:17.893266 ( elapsed: 1 day, 15:49:11.957152; average: 0:00:03.539554 )
----> Processed 40600 of 43843 articles at 2019-11-28 08:35:12.589951 ( elapsed: 1 day, 15:53:06.653837; average: 0:00:03.536617 )
----> Processed 40700 of 43843 articles at 2019-11-28 08:39:42.291825 ( elapsed: 1 day, 15:57:36.355711; average: 0:00:03.534554 )
----> Processed 40800 of 43843 articles at 2019-11-28 08:43:06.630839 ( elapsed: 1 day, 16:01:00.694725; average: 0:00:03.530899 )
----> Processed 40900 of 43843 articles at 2019-11-28 08:47:49.998404 ( elapsed: 1 day, 16:05:44.062290; average: 0:00:03.529195 )
----> Processed 41000 of 43843 articles at 2019-11-28 08:51:34.786815 ( elapsed: 1 day, 16:09:28.850701; average: 0:00:03.526070 )
----> Processed 41100 of 43843 articles at 2019-11-28 08:56:01.682207 ( elapsed: 1 day, 16:13:55.746093; average: 0:00:03.523984 )
----> Processed 41200 of 43843 articles at 2019-11-28 08:59:23.462942 ( elapsed: 1 day, 16:17:17.526828; average: 0:00:03.520328 )
----> Processed 41300 of 43843 articles at 2019-11-28 09:03:43.893555 ( elapsed: 1 day, 16:21:37.957441; average: 0:00:03.518110 )
----> Processed 41400 of 43843 articles at 2019-11-28 09:07:16.857813 ( elapsed: 1 day, 16:25:10.921699; average: 0:00:03.514757 )
----> Processed 41500 of 43843 articles at 2019-11-28 09:10:52.224808 ( elapsed: 1 day, 16:28:46.288694; average: 0:00:03.511477 )
----> Processed 41600 of 43843 articles at 2019-11-28 09:14:34.911801 ( elapsed: 1 day, 16:32:28.975687; average: 0:00:03.508389 )
----> Processed 41700 of 43843 articles at 2019-11-28 09:18:27.838289 ( elapsed: 1 day, 16:36:21.902175; average: 0:00:03.505561 )
----> Processed 41800 of 43843 articles at 2019-11-28 09:21:11.917368 ( elapsed: 1 day, 16:39:05.981254; average: 0:00:03.501100 )
----> Processed 41900 of 43843 articles at 2019-11-28 09:24:53.378326 ( elapsed: 1 day, 16:42:47.442212; average: 0:00:03.498030 )
----> Processed 42000 of 43843 articles at 2019-11-28 09:28:16.171095 ( elapsed: 1 day, 16:46:10.234981; average: 0:00:03.494529 )
----> Processed 42100 of 43843 articles at 2019-11-28 09:31:36.739360 ( elapsed: 1 day, 16:49:30.803246; average: 0:00:03.490993 )
----> Processed 42200 of 43843 articles at 2019-11-28 09:35:23.730556 ( elapsed: 1 day, 16:53:17.794442; average: 0:00:03.488099 )
----> Processed 42300 of 43843 articles at 2019-11-28 09:38:34.655112 ( elapsed: 1 day, 16:56:28.718998; average: 0:00:03.484367 )
----> Processed 42400 of 43843 articles at 2019-11-28 09:41:32.674205 ( elapsed: 1 day, 16:59:26.738091; average: 0:00:03.480348 )
----> Processed 42500 of 43843 articles at 2019-11-28 09:45:14.610464 ( elapsed: 1 day, 17:03:08.674350; average: 0:00:03.477381 )
----> Processed 42600 of 43843 articles at 2019-11-28 09:48:49.292631 ( elapsed: 1 day, 17:06:43.356517; average: 0:00:03.474257 )
----> Processed 42700 of 43843 articles at 2019-11-28 09:52:36.991315 ( elapsed: 1 day, 17:10:31.055201; average: 0:00:03.471453 )
----> Processed 42800 of 43843 articles at 2019-11-28 09:56:43.268333 ( elapsed: 1 day, 17:14:37.332219; average: 0:00:03.469097 )
----> Processed 42900 of 43843 articles at 2019-11-28 10:00:14.502182 ( elapsed: 1 day, 17:18:08.566068; average: 0:00:03.465934 )
----> Processed 43000 of 43843 articles at 2019-11-28 10:04:37.711145 ( elapsed: 1 day, 17:22:31.775031; average: 0:00:03.463995 )
----> Processed 43100 of 43843 articles at 2019-11-28 10:12:34.517086 ( elapsed: 1 day, 17:30:28.580972; average: 0:00:03.467020 )
----> Processed 43200 of 43843 articles at 2019-11-28 10:23:46.077587 ( elapsed: 1 day, 17:41:40.141473; average: 0:00:03.474540 )
----> Processed 43300 of 43843 articles at 2019-11-28 10:29:36.832156 ( elapsed: 1 day, 17:47:30.896042; average: 0:00:03.474617 )
----> Processed 43400 of 43843 articles at 2019-11-28 10:47:25.328380 ( elapsed: 1 day, 18:05:19.392266; average: 0:00:03.491230 )
----> Processed 43500 of 43843 articles at 2019-11-28 11:05:01.298312 ( elapsed: 1 day, 18:22:55.362198; average: 0:00:03.507480 )
----> Processed 43600 of 43843 articles at 2019-11-28 11:22:21.368397 ( elapsed: 1 day, 18:40:15.432283; average: 0:00:03.523290 )
----> Processed 43700 of 43843 articles at 2019-11-28 11:45:53.313475 ( elapsed: 1 day, 19:03:47.377361; average: 0:00:03.547537 )
----> Processed 43800 of 43843 articles at 2019-11-28 12:12:08.885784 ( elapsed: 1 day, 19:30:02.949670; average: 0:00:03.575410 )

Summary:
- good count: 43843
- > 1 count: 0
- 0 count: 0
- unexpected count: 0

















In [15]:



    


print( "Result: {}".format( result ) )



    


















    






Result: success: tags = []; messages = ['\nSummary:\n- good count: 43843\n- > 1 count: 0\n- 0 count: 0\n- unexpected count: 0']

















In [14]:



    


# tag all of the articles with export_to_context-YYYYMMDD-HHMMSS
tag_value = ExportToContext.TAG_PREFIX + "20191126-164206"
print( "Tag value: {}".format( tag_value ) )



    


















    






Tag value: export_to_context-20191126-164206

















In [16]:



    


# declare variables
progress_interval = None
article_counter = None
current_time = None
previous_time = None
elapsed_time = None
elapsed_this_period = None
average_time = None
average_this_period = None

# init
progress_interval = 100
article_counter = 0
start_time = datetime.datetime.now()
current_time = start_time

# loop over articles
for current_article in article_qs:
    
    # increment counter
    article_counter += 1
    
    # add tag.
    current_article.tags.add( tag_value )
    
    # output an update every progress_interval articles.
    if ( ( article_counter % progress_interval ) == 0 ):

        previous_time = current_time
        current_time = datetime.datetime.now()
        elapsed_time = current_time - start_time
        elapsed_this_period = current_time - previous_time
        average_time = elapsed_time / article_counter
        average_this_period = elapsed_this_period / progress_interval
        print( "\n----> Processed {} of {} articles at {}".format( article_counter, article_count, current_time ) )
        print( "Total elapsed: {} ( average: {} )".format( elapsed_time, average_time ) )
        print( "Period elapsed: {} ( average: {} )".format( elapsed_this_period, average_this_period ) )

        # also, garbage collect
        #gc.collect()

    #-- END check to see if we output progress update. --#
    
#-- END loop over articles to tag. --#



    


















    






----> Processed 100 of 43843 articles at 2019-11-29 02:02:50.939196
Total elapsed: 0:00:05.715275 ( average: 0:00:00.057153 )
Period elapsed: 0:00:05.715275 ( average: 0:00:00.057153 )

----> Processed 200 of 43843 articles at 2019-11-29 02:02:51.433714
Total elapsed: 0:00:06.209793 ( average: 0:00:00.031049 )
Period elapsed: 0:00:00.494518 ( average: 0:00:00.004945 )

----> Processed 300 of 43843 articles at 2019-11-29 02:02:51.922741
Total elapsed: 0:00:06.698820 ( average: 0:00:00.022329 )
Period elapsed: 0:00:00.489027 ( average: 0:00:00.004890 )

----> Processed 400 of 43843 articles at 2019-11-29 02:02:52.409249
Total elapsed: 0:00:07.185328 ( average: 0:00:00.017963 )
Period elapsed: 0:00:00.486508 ( average: 0:00:00.004865 )

----> Processed 500 of 43843 articles at 2019-11-29 02:02:52.846413
Total elapsed: 0:00:07.622492 ( average: 0:00:00.015245 )
Period elapsed: 0:00:00.437164 ( average: 0:00:00.004372 )

----> Processed 600 of 43843 articles at 2019-11-29 02:02:53.293409
Total elapsed: 0:00:08.069488 ( average: 0:00:00.013449 )
Period elapsed: 0:00:00.446996 ( average: 0:00:00.004470 )

----> Processed 700 of 43843 articles at 2019-11-29 02:02:53.731636
Total elapsed: 0:00:08.507715 ( average: 0:00:00.012154 )
Period elapsed: 0:00:00.438227 ( average: 0:00:00.004382 )

----> Processed 800 of 43843 articles at 2019-11-29 02:02:54.172460
Total elapsed: 0:00:08.948539 ( average: 0:00:00.011186 )
Period elapsed: 0:00:00.440824 ( average: 0:00:00.004408 )

----> Processed 900 of 43843 articles at 2019-11-29 02:02:54.636460
Total elapsed: 0:00:09.412539 ( average: 0:00:00.010458 )
Period elapsed: 0:00:00.464000 ( average: 0:00:00.004640 )

----> Processed 1000 of 43843 articles at 2019-11-29 02:02:55.099781
Total elapsed: 0:00:09.875860 ( average: 0:00:00.009876 )
Period elapsed: 0:00:00.463321 ( average: 0:00:00.004633 )

----> Processed 1100 of 43843 articles at 2019-11-29 02:02:55.560525
Total elapsed: 0:00:10.336604 ( average: 0:00:00.009397 )
Period elapsed: 0:00:00.460744 ( average: 0:00:00.004607 )

----> Processed 1200 of 43843 articles at 2019-11-29 02:02:56.045250
Total elapsed: 0:00:10.821329 ( average: 0:00:00.009018 )
Period elapsed: 0:00:00.484725 ( average: 0:00:00.004847 )

----> Processed 1300 of 43843 articles at 2019-11-29 02:02:56.516290
Total elapsed: 0:00:11.292369 ( average: 0:00:00.008686 )
Period elapsed: 0:00:00.471040 ( average: 0:00:00.004710 )

----> Processed 1400 of 43843 articles at 2019-11-29 02:02:57.052424
Total elapsed: 0:00:11.828503 ( average: 0:00:00.008449 )
Period elapsed: 0:00:00.536134 ( average: 0:00:00.005361 )

----> Processed 1500 of 43843 articles at 2019-11-29 02:02:57.514003
Total elapsed: 0:00:12.290082 ( average: 0:00:00.008193 )
Period elapsed: 0:00:00.461579 ( average: 0:00:00.004616 )

----> Processed 1600 of 43843 articles at 2019-11-29 02:02:57.972291
Total elapsed: 0:00:12.748370 ( average: 0:00:00.007968 )
Period elapsed: 0:00:00.458288 ( average: 0:00:00.004583 )

----> Processed 1700 of 43843 articles at 2019-11-29 02:02:58.408272
Total elapsed: 0:00:13.184351 ( average: 0:00:00.007756 )
Period elapsed: 0:00:00.435981 ( average: 0:00:00.004360 )

----> Processed 1800 of 43843 articles at 2019-11-29 02:02:58.845490
Total elapsed: 0:00:13.621569 ( average: 0:00:00.007568 )
Period elapsed: 0:00:00.437218 ( average: 0:00:00.004372 )

----> Processed 1900 of 43843 articles at 2019-11-29 02:02:59.274355
Total elapsed: 0:00:14.050434 ( average: 0:00:00.007395 )
Period elapsed: 0:00:00.428865 ( average: 0:00:00.004289 )

----> Processed 2000 of 43843 articles at 2019-11-29 02:02:59.714204
Total elapsed: 0:00:14.490283 ( average: 0:00:00.007245 )
Period elapsed: 0:00:00.439849 ( average: 0:00:00.004398 )

----> Processed 2100 of 43843 articles at 2019-11-29 02:03:00.149928
Total elapsed: 0:00:14.926007 ( average: 0:00:00.007108 )
Period elapsed: 0:00:00.435724 ( average: 0:00:00.004357 )

----> Processed 2200 of 43843 articles at 2019-11-29 02:03:00.587324
Total elapsed: 0:00:15.363403 ( average: 0:00:00.006983 )
Period elapsed: 0:00:00.437396 ( average: 0:00:00.004374 )

----> Processed 2300 of 43843 articles at 2019-11-29 02:03:01.098105
Total elapsed: 0:00:15.874184 ( average: 0:00:00.006902 )
Period elapsed: 0:00:00.510781 ( average: 0:00:00.005108 )

----> Processed 2400 of 43843 articles at 2019-11-29 02:03:01.614037
Total elapsed: 0:00:16.390116 ( average: 0:00:00.006829 )
Period elapsed: 0:00:00.515932 ( average: 0:00:00.005159 )

----> Processed 2500 of 43843 articles at 2019-11-29 02:03:02.130700
Total elapsed: 0:00:16.906779 ( average: 0:00:00.006763 )
Period elapsed: 0:00:00.516663 ( average: 0:00:00.005167 )

----> Processed 2600 of 43843 articles at 2019-11-29 02:03:02.636487
Total elapsed: 0:00:17.412566 ( average: 0:00:00.006697 )
Period elapsed: 0:00:00.505787 ( average: 0:00:00.005058 )

----> Processed 2700 of 43843 articles at 2019-11-29 02:03:03.150951
Total elapsed: 0:00:17.927030 ( average: 0:00:00.006640 )
Period elapsed: 0:00:00.514464 ( average: 0:00:00.005145 )

----> Processed 2800 of 43843 articles at 2019-11-29 02:03:03.616499
Total elapsed: 0:00:18.392578 ( average: 0:00:00.006569 )
Period elapsed: 0:00:00.465548 ( average: 0:00:00.004655 )

----> Processed 2900 of 43843 articles at 2019-11-29 02:03:04.065878
Total elapsed: 0:00:18.841957 ( average: 0:00:00.006497 )
Period elapsed: 0:00:00.449379 ( average: 0:00:00.004494 )

----> Processed 3000 of 43843 articles at 2019-11-29 02:03:04.510560
Total elapsed: 0:00:19.286639 ( average: 0:00:00.006429 )
Period elapsed: 0:00:00.444682 ( average: 0:00:00.004447 )

----> Processed 3100 of 43843 articles at 2019-11-29 02:03:04.984313
Total elapsed: 0:00:19.760392 ( average: 0:00:00.006374 )
Period elapsed: 0:00:00.473753 ( average: 0:00:00.004738 )

----> Processed 3200 of 43843 articles at 2019-11-29 02:03:05.506893
Total elapsed: 0:00:20.282972 ( average: 0:00:00.006338 )
Period elapsed: 0:00:00.522580 ( average: 0:00:00.005226 )

----> Processed 3300 of 43843 articles at 2019-11-29 02:03:06.006713
Total elapsed: 0:00:20.782792 ( average: 0:00:00.006298 )
Period elapsed: 0:00:00.499820 ( average: 0:00:00.004998 )

----> Processed 3400 of 43843 articles at 2019-11-29 02:03:06.495744
Total elapsed: 0:00:21.271823 ( average: 0:00:00.006256 )
Period elapsed: 0:00:00.489031 ( average: 0:00:00.004890 )

----> Processed 3500 of 43843 articles at 2019-11-29 02:03:06.972706
Total elapsed: 0:00:21.748785 ( average: 0:00:00.006214 )
Period elapsed: 0:00:00.476962 ( average: 0:00:00.004770 )

----> Processed 3600 of 43843 articles at 2019-11-29 02:03:07.450501
Total elapsed: 0:00:22.226580 ( average: 0:00:00.006174 )
Period elapsed: 0:00:00.477795 ( average: 0:00:00.004778 )

----> Processed 3700 of 43843 articles at 2019-11-29 02:03:07.915614
Total elapsed: 0:00:22.691693 ( average: 0:00:00.006133 )
Period elapsed: 0:00:00.465113 ( average: 0:00:00.004651 )

----> Processed 3800 of 43843 articles at 2019-11-29 02:03:08.386648
Total elapsed: 0:00:23.162727 ( average: 0:00:00.006095 )
Period elapsed: 0:00:00.471034 ( average: 0:00:00.004710 )

----> Processed 3900 of 43843 articles at 2019-11-29 02:03:08.844280
Total elapsed: 0:00:23.620359 ( average: 0:00:00.006057 )
Period elapsed: 0:00:00.457632 ( average: 0:00:00.004576 )

----> Processed 4000 of 43843 articles at 2019-11-29 02:03:09.323376
Total elapsed: 0:00:24.099455 ( average: 0:00:00.006025 )
Period elapsed: 0:00:00.479096 ( average: 0:00:00.004791 )

----> Processed 4100 of 43843 articles at 2019-11-29 02:03:09.794942
Total elapsed: 0:00:24.571021 ( average: 0:00:00.005993 )
Period elapsed: 0:00:00.471566 ( average: 0:00:00.004716 )

----> Processed 4200 of 43843 articles at 2019-11-29 02:03:10.257552
Total elapsed: 0:00:25.033631 ( average: 0:00:00.005960 )
Period elapsed: 0:00:00.462610 ( average: 0:00:00.004626 )

----> Processed 4300 of 43843 articles at 2019-11-29 02:03:10.729646
Total elapsed: 0:00:25.505725 ( average: 0:00:00.005932 )
Period elapsed: 0:00:00.472094 ( average: 0:00:00.004721 )

----> Processed 4400 of 43843 articles at 2019-11-29 02:03:11.210226
Total elapsed: 0:00:25.986305 ( average: 0:00:00.005906 )
Period elapsed: 0:00:00.480580 ( average: 0:00:00.004806 )

----> Processed 4500 of 43843 articles at 2019-11-29 02:03:11.693440
Total elapsed: 0:00:26.469519 ( average: 0:00:00.005882 )
Period elapsed: 0:00:00.483214 ( average: 0:00:00.004832 )

----> Processed 4600 of 43843 articles at 2019-11-29 02:03:12.139540
Total elapsed: 0:00:26.915619 ( average: 0:00:00.005851 )
Period elapsed: 0:00:00.446100 ( average: 0:00:00.004461 )

----> Processed 4700 of 43843 articles at 2019-11-29 02:03:12.609203
Total elapsed: 0:00:27.385282 ( average: 0:00:00.005827 )
Period elapsed: 0:00:00.469663 ( average: 0:00:00.004697 )

----> Processed 4800 of 43843 articles at 2019-11-29 02:03:13.060521
Total elapsed: 0:00:27.836600 ( average: 0:00:00.005799 )
Period elapsed: 0:00:00.451318 ( average: 0:00:00.004513 )

----> Processed 4900 of 43843 articles at 2019-11-29 02:03:13.494443
Total elapsed: 0:00:28.270522 ( average: 0:00:00.005769 )
Period elapsed: 0:00:00.433922 ( average: 0:00:00.004339 )

----> Processed 5000 of 43843 articles at 2019-11-29 02:03:13.926629
Total elapsed: 0:00:28.702708 ( average: 0:00:00.005741 )
Period elapsed: 0:00:00.432186 ( average: 0:00:00.004322 )

----> Processed 5100 of 43843 articles at 2019-11-29 02:03:14.363984
Total elapsed: 0:00:29.140063 ( average: 0:00:00.005714 )
Period elapsed: 0:00:00.437355 ( average: 0:00:00.004374 )

----> Processed 5200 of 43843 articles at 2019-11-29 02:03:14.853690
Total elapsed: 0:00:29.629769 ( average: 0:00:00.005698 )
Period elapsed: 0:00:00.489706 ( average: 0:00:00.004897 )

----> Processed 5300 of 43843 articles at 2019-11-29 02:03:15.339459
Total elapsed: 0:00:30.115538 ( average: 0:00:00.005682 )
Period elapsed: 0:00:00.485769 ( average: 0:00:00.004858 )

----> Processed 5400 of 43843 articles at 2019-11-29 02:03:15.806459
Total elapsed: 0:00:30.582538 ( average: 0:00:00.005663 )
Period elapsed: 0:00:00.467000 ( average: 0:00:00.004670 )

----> Processed 5500 of 43843 articles at 2019-11-29 02:03:16.275151
Total elapsed: 0:00:31.051230 ( average: 0:00:00.005646 )
Period elapsed: 0:00:00.468692 ( average: 0:00:00.004687 )

----> Processed 5600 of 43843 articles at 2019-11-29 02:03:16.784837
Total elapsed: 0:00:31.560916 ( average: 0:00:00.005636 )
Period elapsed: 0:00:00.509686 ( average: 0:00:00.005097 )

----> Processed 5700 of 43843 articles at 2019-11-29 02:03:17.278806
Total elapsed: 0:00:32.054885 ( average: 0:00:00.005624 )
Period elapsed: 0:00:00.493969 ( average: 0:00:00.004940 )

----> Processed 5800 of 43843 articles at 2019-11-29 02:03:17.777661
Total elapsed: 0:00:32.553740 ( average: 0:00:00.005613 )
Period elapsed: 0:00:00.498855 ( average: 0:00:00.004989 )

----> Processed 5900 of 43843 articles at 2019-11-29 02:03:18.272699
Total elapsed: 0:00:33.048778 ( average: 0:00:00.005601 )
Period elapsed: 0:00:00.495038 ( average: 0:00:00.004950 )

----> Processed 6000 of 43843 articles at 2019-11-29 02:03:18.735437
Total elapsed: 0:00:33.511516 ( average: 0:00:00.005585 )
Period elapsed: 0:00:00.462738 ( average: 0:00:00.004627 )

----> Processed 6100 of 43843 articles at 2019-11-29 02:03:19.169266
Total elapsed: 0:00:33.945345 ( average: 0:00:00.005565 )
Period elapsed: 0:00:00.433829 ( average: 0:00:00.004338 )

----> Processed 6200 of 43843 articles at 2019-11-29 02:03:19.670018
Total elapsed: 0:00:34.446097 ( average: 0:00:00.005556 )
Period elapsed: 0:00:00.500752 ( average: 0:00:00.005008 )

----> Processed 6300 of 43843 articles at 2019-11-29 02:03:20.185113
Total elapsed: 0:00:34.961192 ( average: 0:00:00.005549 )
Period elapsed: 0:00:00.515095 ( average: 0:00:00.005151 )

----> Processed 6400 of 43843 articles at 2019-11-29 02:03:20.658398
Total elapsed: 0:00:35.434477 ( average: 0:00:00.005537 )
Period elapsed: 0:00:00.473285 ( average: 0:00:00.004733 )

----> Processed 6500 of 43843 articles at 2019-11-29 02:03:21.129871
Total elapsed: 0:00:35.905950 ( average: 0:00:00.005524 )
Period elapsed: 0:00:00.471473 ( average: 0:00:00.004715 )

----> Processed 6600 of 43843 articles at 2019-11-29 02:03:21.603567
Total elapsed: 0:00:36.379646 ( average: 0:00:00.005512 )
Period elapsed: 0:00:00.473696 ( average: 0:00:00.004737 )

----> Processed 6700 of 43843 articles at 2019-11-29 02:03:22.057225
Total elapsed: 0:00:36.833304 ( average: 0:00:00.005498 )
Period elapsed: 0:00:00.453658 ( average: 0:00:00.004537 )

----> Processed 6800 of 43843 articles at 2019-11-29 02:03:22.508470
Total elapsed: 0:00:37.284549 ( average: 0:00:00.005483 )
Period elapsed: 0:00:00.451245 ( average: 0:00:00.004512 )

----> Processed 6900 of 43843 articles at 2019-11-29 02:03:22.942347
Total elapsed: 0:00:37.718426 ( average: 0:00:00.005466 )
Period elapsed: 0:00:00.433877 ( average: 0:00:00.004339 )

----> Processed 7000 of 43843 articles at 2019-11-29 02:03:23.380576
Total elapsed: 0:00:38.156655 ( average: 0:00:00.005451 )
Period elapsed: 0:00:00.438229 ( average: 0:00:00.004382 )

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In [20]:



    


# Count number of articles with tag name starting with
#     ExportToContext.TAG_PREFIX
tag_test_qs = Article.objects.filter( tags__name__istartswith = ExportToContext.TAG_PREFIX )
tag_test_count = tag_test_qs.count()
article_count = article_qs.count()

# did all the articles get tagged?
test_value = tag_test_count
should_be = article_count
error_string = "Count of tagged articles: {}, should be {}.".format( test_value, should_be )
assert test_value == should_be, error_string

print( "Found {} Articles with tag starting with {}.".format( tag_test_count, ExportToContext.TAG_PREFIX ) )



    


















    






Found 43843 Articles with tag starting with export_to_context-.

Content source: jonathanmorgan/msu_phd_work

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