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/var/log/nginx/error.log
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/var/log/eb-docker/containers/eb-current-app/eb-1eaf092b5934-stdouterr.log
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2021-11-04 05:38:54,216 INFO util.files :: Extract file /modules/sqlite.metabase-driver.jar -> /plugins/sqlite.metabase-driver.jar
2021-11-04 05:38:54,236 INFO util.files :: Extract file /modules/vertica.metabase-driver.jar -> /plugins/vertica.metabase-driver.jar

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Warning: environ value jdk-11.0.11+9 for key :java-version has been overwritten with 11.0.11
2021-11-03 05:00:36,948 INFO metabase.util :: Maximum memory available to JVM: 481.4 MB
2021-11-03 05:00:52,347 INFO util.encryption :: Saved credentials encryption is DISABLED for this Metabase instance. 🔓
 For more information, see https://metabase.com/docs/latest/operations-guide/encrypting-database-details-at-rest.html
2021-11-03 05:01:01,377 INFO metabase.core ::
Metabase v0.40.0 (961caed master)

Copyright © 2021 Metabase, Inc.

Metabase Enterprise Edition extensions are NOT PRESENT.

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Warning: environ value jdk-11.0.12+7 for key :java-version has been overwritten with 11.0.12
WARNING: sun.reflect.Reflection.getCallerClass is not supported. This will impact performance.
2021-11-03 04:38:57,677 INFO metabase.util :: Maximum memory available to JVM: 481.4 MB
2021-11-03 04:39:13,917 INFO util.encryption :: Saved credentials encryption is DISABLED for this Metabase instance. 🔓
 For more information, see https://metabase.com/docs/latest/operations-guide/encrypting-database-details-at-rest.html
2021-11-03 04:39:19,378 INFO driver.impl :: Registered abstract driver :sql  🚚
 ↙ Load driver :sql took 921.5 ms
2021-11-03 04:39:19,399 INFO driver.impl :: Registered abstract driver :sql-jdbc (parents: [:sql]) 🚚
Load driver :sql-jdbc took 958.2 ms
2021-11-03 04:39:19,410 INFO driver.impl :: Registered driver :h2 (parents: [:sql-jdbc]) 🚚

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-- GENRES (Helper Table)
create table genres (
	genre varchar(20)
);

insert into genres 
values ('Action'),('Adventure'),('Animation'),('Biography'),('Comedy'),('Crime'),('Drama')
	,('Family'),('Fantasy'),('Film-Noir'),('History'),('Horror'),('Music'),('Musical')
	,('Mystery'),('Romance'),('Sci-Fi'),('Sport'),('Thriller'),('War'),('Western')

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-- Seasons Rating (AVG)
select "Season", avg("Rating") "Rating Average"
from episodes
where 1 = 1
[[ and {{primary_title}} ]]
[[ and "# Votes" > {{num_votes}} ]]
group by "Season"

-- Episodes Rating
select 

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select a.id, title_type,
  case when title_type in ('movie', 'tvMovie') then 'Movie'
       when title_type in ('tvSeries', 'tvMiniSeries') then 'Series'
  end as item_type,
  original_title, primary_title, start_year, runtime_minutes,
  genres, avg_rating, num_votes
into movies_series
from source_basics a join source_ratings b on a.id = b.id
where title_type in ('movie', 'tvMovie', 'tvSeries', 'tvMiniSeries');

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import psycopg2
connection = psycopg2.connect(user="USER"
                            , password="PASSWORD"
                            , port="5432"
                            , database="DB_NAME"
                            , host="HOST")
cursor = connection.cursor()

with open('ratings.tsv') as f:
  f.readline()

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hashtag_list = ['travelblog', 'travelblogger', 'traveler']

# prev_user_list = [] - if it's the first time you run it, use this line and comment the two below
prev_user_list = pd.read_csv('20181203-224633_users_followed_list.csv', delimiter=',').iloc[:,1:2] # useful to build a user log
prev_user_list = list(prev_user_list['0'])

new_followed = []
tag = -1
followed = 0
likes = 0