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  1. .config/.last_opt_in_prompt.yaml +1 -0
  2. .config/.last_survey_prompt.yaml +1 -0
  3. .config/.last_update_check.json +1 -0
  4. .config/active_config +1 -0
  5. .config/config_sentinel +0 -0
  6. .config/configurations/config_default +6 -0
  7. .config/default_configs.db +0 -0
  8. .config/gce +1 -0
  9. .config/hidden_gcloud_config_universe_descriptor_data_cache_configs.db +0 -0
  10. .config/logs/2024.08.09/13.21.31.474641.log +764 -0
  11. .config/logs/2024.08.09/13.21.52.633196.log +5 -0
  12. .config/logs/2024.08.09/13.22.02.230892.log +123 -0
  13. .config/logs/2024.08.09/13.22.03.330412.log +5 -0
  14. .config/logs/2024.08.09/13.22.12.955173.log +8 -0
  15. .config/logs/2024.08.09/13.22.13.565225.log +8 -0
  16. .gitattributes +2 -0
  17. README.md +1 -7
  18. environment_model.pkl +3 -0
  19. sample_data/README.md +19 -0
  20. sample_data/anscombe.json +49 -0
  21. sample_data/california_housing_test.csv +0 -0
  22. sample_data/california_housing_train.csv +0 -0
  23. sample_data/mnist_test.csv +3 -0
  24. sample_data/mnist_train_small.csv +3 -0
  25. t1.py +327 -0
  26. tweets_kuru.csv +17 -0
.config/.last_opt_in_prompt.yaml ADDED
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+ {}
.config/.last_survey_prompt.yaml ADDED
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+ last_prompt_time: 1723209721.6763928
.config/.last_update_check.json ADDED
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+ {"last_update_check_time": 1723209722.8759415, "last_update_check_revision": 20240806142304, "notifications": [], "last_nag_times": {}}
.config/active_config ADDED
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+ default
.config/config_sentinel ADDED
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.config/configurations/config_default ADDED
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+ [component_manager]
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+ disable_update_check = true
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+
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+ [compute]
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+ gce_metadata_read_timeout_sec = 0
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+
.config/default_configs.db ADDED
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.config/gce ADDED
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.config/hidden_gcloud_config_universe_descriptor_data_cache_configs.db ADDED
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.config/logs/2024.08.09/13.21.31.474641.log ADDED
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+ 2024-08-09 13:21:44,143 INFO ___FILE_ONLY___ ╠═ Downloading: Bundled Python 3.11 (Platform Specific) ═╣
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481
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540
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541
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542
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543
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544
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545
+ 2024-08-09 13:21:45,744 INFO ___FILE_ONLY___ ═
546
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547
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548
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549
+ 2024-08-09 13:21:45,753 INFO ___FILE_ONLY___ ═
550
+ 2024-08-09 13:21:45,753 INFO ___FILE_ONLY___ ╝
551
+
552
+ 2024-08-09 13:21:45,765 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
553
+
554
+ 2024-08-09 13:21:45,765 INFO ___FILE_ONLY___ ╠═ Installing: BigQuery Command Line Tool (Platform Spec... ═╣
555
+
556
+ 2024-08-09 13:21:45,765 INFO ___FILE_ONLY___ ╚
557
+ 2024-08-09 13:21:45,766 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
558
+ 2024-08-09 13:21:45,766 INFO ___FILE_ONLY___ ╝
559
+
560
+ 2024-08-09 13:21:45,772 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
561
+
562
+ 2024-08-09 13:21:45,772 INFO ___FILE_ONLY___ ╠═ Installing: Bundled Python 3.11 ═╣
563
+
564
+ 2024-08-09 13:21:45,772 INFO ___FILE_ONLY___ ╚
565
+ 2024-08-09 13:21:45,776 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
566
+ 2024-08-09 13:21:45,776 INFO ___FILE_ONLY___ ╝
567
+
568
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569
+
570
+ 2024-08-09 13:21:45,778 INFO ___FILE_ONLY___ ╠═ Installing: Bundled Python 3.11 (Platform Specific) ═╣
571
+
572
+ 2024-08-09 13:21:45,778 INFO ___FILE_ONLY___ ╚
573
+ 2024-08-09 13:21:47,941 INFO ___FILE_ONLY___ ═
574
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575
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576
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577
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578
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579
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580
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583
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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599
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
+ 2024-08-09 13:21:50,491 INFO ___FILE_ONLY___ ╝
634
+
635
+ 2024-08-09 13:21:50,569 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
636
+
637
+ 2024-08-09 13:21:50,569 INFO ___FILE_ONLY___ ╠═ Installing: Cloud Storage Command Line Tool ═╣
638
+
639
+ 2024-08-09 13:21:50,569 INFO ___FILE_ONLY___ ╚
640
+ 2024-08-09 13:21:51,241 INFO ___FILE_ONLY___ ═
641
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642
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643
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656
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657
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658
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659
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660
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662
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663
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665
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
+ 2024-08-09 13:21:51,962 INFO ___FILE_ONLY___ ═
697
+ 2024-08-09 13:21:51,982 INFO ___FILE_ONLY___ ═
698
+ 2024-08-09 13:21:51,998 INFO ___FILE_ONLY___ ═
699
+ 2024-08-09 13:21:52,015 INFO ___FILE_ONLY___ ═
700
+ 2024-08-09 13:21:52,016 INFO ___FILE_ONLY___ ╝
701
+
702
+ 2024-08-09 13:21:52,067 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
703
+
704
+ 2024-08-09 13:21:52,067 INFO ___FILE_ONLY___ ╠═ Installing: Cloud Storage Command Line Tool (Platform... ═╣
705
+
706
+ 2024-08-09 13:21:52,067 INFO ___FILE_ONLY___ ╚
707
+ 2024-08-09 13:21:52,068 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
708
+ 2024-08-09 13:21:52,068 INFO ___FILE_ONLY___ ╝
709
+
710
+ 2024-08-09 13:21:52,074 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
711
+
712
+ 2024-08-09 13:21:52,074 INFO ___FILE_ONLY___ ╠═ Installing: Default set of gcloud commands ═╣
713
+
714
+ 2024-08-09 13:21:52,074 INFO ___FILE_ONLY___ ╚
715
+ 2024-08-09 13:21:52,078 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
716
+ 2024-08-09 13:21:52,078 INFO ___FILE_ONLY___ ╝
717
+
718
+ 2024-08-09 13:21:52,079 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
719
+
720
+ 2024-08-09 13:21:52,080 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CLI Core Libraries (Platform... ═╣
721
+
722
+ 2024-08-09 13:21:52,080 INFO ___FILE_ONLY___ ╚
723
+ 2024-08-09 13:21:52,081 INFO ___FILE_ONLY___ ══════════════════════════════
724
+ 2024-08-09 13:21:52,081 INFO ___FILE_ONLY___ ══════════════════════════════
725
+ 2024-08-09 13:21:52,081 INFO ___FILE_ONLY___ ╝
726
+
727
+ 2024-08-09 13:21:52,087 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
728
+
729
+ 2024-08-09 13:21:52,087 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CRC32C Hash Tool ═╣
730
+
731
+ 2024-08-09 13:21:52,087 INFO ___FILE_ONLY___ ╚
732
+ 2024-08-09 13:21:52,091 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
733
+ 2024-08-09 13:21:52,091 INFO ___FILE_ONLY___ ╝
734
+
735
+ 2024-08-09 13:21:52,092 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
736
+
737
+ 2024-08-09 13:21:52,092 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CRC32C Hash Tool (Platform S... ═╣
738
+
739
+ 2024-08-09 13:21:52,092 INFO ___FILE_ONLY___ ╚
740
+ 2024-08-09 13:21:52,127 INFO ___FILE_ONLY___ ══════════════════════════════
741
+ 2024-08-09 13:21:52,128 INFO ___FILE_ONLY___ ══════════════════════════════
742
+ 2024-08-09 13:21:52,128 INFO ___FILE_ONLY___ ╝
743
+
744
+ 2024-08-09 13:21:52,134 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
745
+
746
+ 2024-08-09 13:21:52,134 INFO ___FILE_ONLY___ ╠═ Installing: gcloud cli dependencies (Platform Specific) ═╣
747
+
748
+ 2024-08-09 13:21:52,134 INFO ___FILE_ONLY___ ╚
749
+ 2024-08-09 13:21:52,134 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
750
+ 2024-08-09 13:21:52,134 INFO ___FILE_ONLY___ ╝
751
+
752
+ 2024-08-09 13:21:52,141 DEBUG root Updating notification cache...
753
+ 2024-08-09 13:21:52,142 INFO ___FILE_ONLY___
754
+
755
+ 2024-08-09 13:21:52,143 INFO ___FILE_ONLY___ Performing post processing steps...
756
+ 2024-08-09 13:21:52,144 DEBUG root Executing command: ['/tools/google-cloud-sdk/bin/gcloud', 'components', 'post-process']
757
+ 2024-08-09 13:22:01,651 DEBUG ___FILE_ONLY___
758
+ 2024-08-09 13:22:01,651 DEBUG ___FILE_ONLY___
759
+ 2024-08-09 13:22:01,672 INFO ___FILE_ONLY___
760
+ Update done!
761
+
762
+
763
+ 2024-08-09 13:22:01,675 DEBUG root Chosen display Format:none
764
+ 2024-08-09 13:22:01,675 INFO root Display format: "none"
.config/logs/2024.08.09/13.21.52.633196.log ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ 2024-08-09 13:21:52,634 DEBUG root Loaded Command Group: ['gcloud', 'components']
2
+ 2024-08-09 13:21:52,636 DEBUG root Loaded Command Group: ['gcloud', 'components', 'post_process']
3
+ 2024-08-09 13:21:52,638 DEBUG root Running [gcloud.components.post-process] with arguments: []
4
+ 2024-08-09 13:22:01,559 DEBUG root Chosen display Format:none
5
+ 2024-08-09 13:22:01,560 INFO root Display format: "none"
.config/logs/2024.08.09/13.22.02.230892.log ADDED
@@ -0,0 +1,123 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2024-08-09 13:22:02,231 DEBUG root Loaded Command Group: ['gcloud', 'components']
2
+ 2024-08-09 13:22:02,234 DEBUG root Loaded Command Group: ['gcloud', 'components', 'update']
3
+ 2024-08-09 13:22:02,236 DEBUG root Running [gcloud.components.update] with arguments: [--quiet: "True", COMPONENT-IDS:8: "['gcloud', 'core', 'bq', 'gsutil', 'compute', 'preview', 'alpha', 'beta']"]
4
+ 2024-08-09 13:22:02,237 INFO ___FILE_ONLY___ Beginning update. This process may take several minutes.
5
+
6
+ 2024-08-09 13:22:02,247 DEBUG urllib3.connectionpool Starting new HTTPS connection (1): dl.google.com:443
7
+ 2024-08-09 13:22:02,329 DEBUG urllib3.connectionpool https://dl.google.com:443 "GET /dl/cloudsdk/channels/rapid/components-2.json HTTP/1.1" 200 223380
8
+ 2024-08-09 13:22:02,345 WARNING root Component [compute] no longer exists.
9
+ 2024-08-09 13:22:02,345 WARNING root Component [preview] no longer exists.
10
+ 2024-08-09 13:22:02,346 INFO ___FILE_ONLY___
11
+
12
+ 2024-08-09 13:22:02,346 INFO ___FILE_ONLY___
13
+ Your current Google Cloud CLI version is: 487.0.0
14
+
15
+ 2024-08-09 13:22:02,346 INFO ___FILE_ONLY___ Installing components from version: 487.0.0
16
+
17
+ 2024-08-09 13:22:02,346 INFO ___FILE_ONLY___
18
+
19
+ 2024-08-09 13:22:02,347 DEBUG root Chosen display Format:table[box,title="These components will be removed."](details.display_name:label=Name:align=left,version.version_string:label=Version:align=right,data.size.size(zero="",min=1048576):label=Size:align=right)
20
+ 2024-08-09 13:22:02,347 DEBUG root Chosen display Format:table[box,title="These components will be updated."](details.display_name:label=Name:align=left,version.version_string:label=Version:align=right,data.size.size(zero="",min=1048576):label=Size:align=right)
21
+ 2024-08-09 13:22:02,348 DEBUG root Chosen display Format:table[box,title="These components will be installed."](details.display_name:label=Name:align=left,version.version_string:label=Version:align=right,data.size.size(zero="",min=1048576):label=Size:align=right)
22
+ 2024-08-09 13:22:02,365 INFO ___FILE_ONLY___ ┌──────────────────────────────────────────────┐
23
+ 2024-08-09 13:22:02,365 INFO ___FILE_ONLY___
24
+
25
+ 2024-08-09 13:22:02,365 INFO ___FILE_ONLY___ │ These components will be installed. │
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  ---
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1
+ This directory includes a few sample datasets to get you started.
2
+
3
+ * `california_housing_data*.csv` is California housing data from the 1990 US
4
+ Census; more information is available at:
5
+ https://developers.google.com/machine-learning/crash-course/california-housing-data-description
6
+
7
+ * `mnist_*.csv` is a small sample of the
8
+ [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is
9
+ described at: http://yann.lecun.com/exdb/mnist/
10
+
11
+ * `anscombe.json` contains a copy of
12
+ [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it
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+ was originally described in
14
+
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+ Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American
16
+ Statistician. 27 (1): 17-21. JSTOR 2682899.
17
+
18
+ and our copy was prepared by the
19
+ [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json).
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1
+ import numpy as np
2
+ import pandas as pd
3
+ from sklearn.model_selection import train_test_split
4
+ from sklearn.ensemble import RandomForestClassifier
5
+ from sklearn.metrics import accuracy_score
6
+ import joblib
7
+ import cv2
8
+ from deepface import DeepFace
9
+ import random
10
+ import gradio as gr
11
+ import matplotlib.pyplot as plt
12
+ from transformers import pipeline
13
+ from PIL import Image
14
+ from ntscraper import Nitter
15
+ import csv
16
+
17
+
18
+ # Scraper function
19
+ def scrape_tweets(hashtag, mode, num_of_tweets, since_date, until_date):
20
+ import httpx
21
+ httpx._config.DEFAULT_TIMEOUT = httpx.Timeout(3.0)
22
+
23
+ scraper = Nitter()
24
+ tweets = scraper.get_tweets(
25
+ hashtag,
26
+ mode='hashtag',
27
+ number=num_of_tweets,
28
+ since=since_date,
29
+ until=until_date
30
+ )
31
+
32
+ final_tweets = []
33
+
34
+ with open('tweets_kuru.csv', 'w', encoding='utf-8') as file:
35
+ writer = csv.writer(file)
36
+ writer.writerow([f'Scraping Tweets for #{hashtag}'])
37
+ writer.writerow(['User', 'Username', 'Tweet', 'Date'])
38
+
39
+ for tweet in tweets['tweets']:
40
+ tweet_details = [tweet['user']['name'], tweet['user']['username'], tweet['text'], tweet['date']]
41
+ writer.writerow([tweet['user']['name'], tweet['user']['username'], tweet['text'], tweet['date']])
42
+ final_tweets.append(tweet_details)
43
+
44
+ tweet_df = pd.DataFrame(final_tweets, columns=['User', 'Username', 'Tweet', 'Date'])
45
+ return tweet_df
46
+
47
+
48
+ # Sensor Simulate Data
49
+ np.random.seed(42)
50
+ data_size = 1000
51
+ aqi_values = np.random.randint(0, 500, size=data_size)
52
+ noise_levels = np.random.randint(30, 110, size=data_size)
53
+ temperatures = np.random.randint(-10, 40, size=data_size)
54
+ humidity_levels = np.random.randint(10, 90, size=data_size)
55
+ pm25_values = np.random.randint(0, 500, size=data_size)
56
+ co2_levels = np.random.randint(250, 6000, size=data_size)
57
+
58
+
59
+ def classify_environment(aqi, noise, temp, humidity, pm25, co2):
60
+ if aqi > 150 or noise > 80 or temp > 35 or humidity > 80 or pm25 > 55 or co2 > 2000:
61
+ return "Bad"
62
+ elif aqi > 100 or noise > 60 or temp > 30 or humidity > 60 or pm25 > 35 or co2 > 1000:
63
+ return "Moderate"
64
+ else:
65
+ return "Good"
66
+
67
+
68
+ labels = [classify_environment(aqi, noise, temp, humidity, pm25, co2)
69
+ for aqi, noise, temp, humidity, pm25, co2 in
70
+ zip(aqi_values, noise_levels, temperatures, humidity_levels, pm25_values, co2_levels)]
71
+
72
+ data = pd.DataFrame({
73
+ 'AQI': aqi_values,
74
+ 'Noise': noise_levels,
75
+ 'Temperature': temperatures,
76
+ 'Humidity': humidity_levels,
77
+ 'PM2.5': pm25_values,
78
+ 'CO2': co2_levels,
79
+ 'Label': labels
80
+ })
81
+
82
+ # Train a Simple Classification Model
83
+ X = data[['AQI', 'Noise', 'Temperature', 'Humidity', 'PM2.5', 'CO2']]
84
+ y = data['Label']
85
+
86
+ X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
87
+
88
+ model = RandomForestClassifier()
89
+ model.fit(X_train, y_train)
90
+
91
+ predictions = model.predict(X_test)
92
+ print("Accuracy:", accuracy_score(y_test, predictions))
93
+
94
+ # Save the model
95
+ joblib.dump(model, 'environment_model.pkl')
96
+
97
+
98
+ # Function to analyze video sentiment
99
+ def analyze_video_sentiment(video_path, num_frames=10, detector_backend='retinaface'):
100
+ cap = cv2.VideoCapture(video_path)
101
+ total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
102
+
103
+ # Select num_frames random frame indices
104
+ frame_indices = random.sample(range(total_frames), num_frames)
105
+ emotions = {"happy": 0, "sad": 0, "angry": 0, "surprised": 0, "neutral": 0}
106
+ frame_images = []
107
+
108
+ for idx in frame_indices:
109
+ cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
110
+ ret, frame = cap.read()
111
+ if not ret:
112
+ continue
113
+
114
+ # Convert to RGB
115
+ rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
116
+
117
+ # Face detection and emotion analysis
118
+ try:
119
+ results = DeepFace.analyze(rgb_frame, actions=["emotion"], enforce_detection=True,
120
+ detector_backend=detector_backend)
121
+
122
+ for result in results:
123
+ if result is None or result == {}:
124
+ continue
125
+
126
+ # Draw bounding box
127
+ face_coordinates = result["region"]
128
+ x1, y1, x2, y2 = face_coordinates["x"], face_coordinates["y"], face_coordinates["x"] + face_coordinates[
129
+ "w"], face_coordinates["y"] + face_coordinates["h"]
130
+ cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
131
+
132
+ # Add emotion label above the bounding box
133
+ dominant_emotion = result["dominant_emotion"]
134
+ cv2.putText(frame, dominant_emotion, (x1 + 5, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
135
+
136
+ # Update emotion counts
137
+ if dominant_emotion in emotions:
138
+ emotions[dominant_emotion] += 1
139
+
140
+ except ValueError as e:
141
+ if "No face detected" in str(e):
142
+ continue
143
+ else:
144
+ raise e
145
+
146
+ # Convert frame to image for Gradio display
147
+ frame_image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
148
+ frame_images.append(frame_image)
149
+
150
+ cap.release()
151
+ cv2.destroyAllWindows()
152
+
153
+ # Determine dominant emotion
154
+ dominant_emotion = max(emotions, key=emotions.get)
155
+
156
+ # Return dominant emotion and frame images
157
+ return dominant_emotion, frame_images
158
+
159
+
160
+ # Load the classifier for sentiment analysis
161
+ classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base",
162
+ return_all_scores=True)
163
+
164
+
165
+ def classify_tweets(tweets_df):
166
+ if tweets_df.empty:
167
+ return "No tweets to analyze."
168
+
169
+ tweet_texts = tweets_df['Tweet'].tolist()
170
+ results = classifier(tweet_texts)
171
+ emotions = [max(result, key=lambda x: x['score'])['label'] for result in results]
172
+ tweet_df = tweets_df.copy()
173
+ tweet_df['Sentiment'] = emotions
174
+
175
+ # Plot sentiment distribution
176
+ sentiment_counts = tweet_df['Sentiment'].value_counts()
177
+ fig, ax = plt.subplots(figsize=(8, 5))
178
+ bars = ax.bar(sentiment_counts.index, sentiment_counts.values,
179
+ color=['#FF6F61', '#6B5B95', '#88B04B', '#F7CAC9', '#92A8D1', '#955251'])
180
+
181
+ ax.set_xlabel('Sentiment', fontsize=14, fontweight='bold', color='#34495E')
182
+ ax.set_ylabel('Count', fontsize=14, fontweight='bold', color='#34495E')
183
+ ax.set_title('Tweet Sentiment Distribution', fontsize=18, fontweight='bold', color='#2E4053')
184
+ ax.tick_params(axis='x', rotation=0, colors='#34495E', labelsize=12)
185
+ ax.tick_params(axis='y', colors='#34495E', labelsize=12)
186
+ ax.spines['top'].set_visible(False)
187
+ ax.spines['right'].set_visible(False)
188
+ ax.spines['left'].set_visible(False)
189
+ ax.spines['bottom'].set_visible(False)
190
+ ax.yaxis.grid(True, linestyle='--', which='major', color='grey', alpha=.45)
191
+ ax.xaxis.set_tick_params(width=0)
192
+
193
+ for bar in bars:
194
+ yval = bar.get_height()
195
+ ax.text(bar.get_x() + bar.get_width() / 2, yval + 0.01, round(yval, 2), ha='center', va='bottom',
196
+ color='#34495E', fontsize=12, fontweight='bold')
197
+
198
+ plt.tight_layout()
199
+ return tweet_df, fig
200
+
201
+
202
+ def classify_and_plot(hashtag, mode, num_of_tweets, since_date, until_date):
203
+ tweet_df = scrape_tweets(hashtag, mode, num_of_tweets, since_date, until_date)
204
+ tweet_df, fig = classify_tweets(tweet_df)
205
+ return tweet_df, fig
206
+
207
+
208
+ # Function to classify overall sentiment
209
+ def classify_overall_sentiment(video, text, hashtag, mode, num_of_tweets, since_date, until_date, aqi, noise, temp,
210
+ humidity, pm25, co2):
211
+ # Initialize placeholders
212
+ video_sentiment = "No video analyzed"
213
+ frame_images = []
214
+ text_emotion = "No text analyzed"
215
+ environment = "No environment data"
216
+ tweet_df = pd.DataFrame()
217
+ plot = None
218
+
219
+ # Video Sentiment Analysis
220
+ if video:
221
+ video_sentiment, frame_images = analyze_video_sentiment(video)
222
+
223
+ # Social Media Sentiment Analysis
224
+ if hashtag and since_date and until_date:
225
+ try:
226
+ tweet_df, plot = classify_and_plot(hashtag, mode, num_of_tweets, since_date, until_date)
227
+ if not tweet_df.empty:
228
+ text_emotion = tweet_df['Sentiment'].value_counts().idxmax()
229
+ except Exception as e:
230
+ print(f"Error in social media analysis: {e}")
231
+ text_emotion = "Error in social media analysis"
232
+
233
+ # Environment Sentiment Analysis
234
+ if aqi is not None and noise is not None and temp is not None and humidity is not None and pm25 is not None and co2 is not None:
235
+ environment = classify_environment(aqi, noise, temp, humidity, pm25, co2)
236
+
237
+ # Calculate overall sentiment and create a plot
238
+ overall_sentiment = f"Video Sentiment: {video_sentiment}, Environment Sentiment: {environment}"
239
+
240
+ if text_emotion != "No text analyzed" and text_emotion != "Error in social media analysis":
241
+ overall_sentiment += f", Text Emotion: {text_emotion}"
242
+
243
+ sentiments = ["Video Sentiment", "Text Emotion", "Environment Sentiment"]
244
+ scores = [video_sentiment_score(video_sentiment), text_emotion_score(text_emotion), environment_score(environment)]
245
+
246
+ fig, ax = plt.subplots()
247
+ ax.plot(sentiments, scores, marker='o')
248
+
249
+ ax.set_xlabel('Sentiment Source', fontsize=14, fontweight='bold', color='#34495E')
250
+ ax.set_ylabel('Sentiment Score', fontsize=14, fontweight='bold', color='#34495E')
251
+ ax.set_title('Overall Sentiment Scores', fontsize=18, fontweight='bold', color='#2E4053')
252
+
253
+ plt.tight_layout()
254
+
255
+ return overall_sentiment, frame_images, tweet_df, plot, fig
256
+
257
+
258
+ # Create Gradio Interfaces
259
+ video_interface = gr.Interface(
260
+ fn=analyze_video_sentiment,
261
+ inputs=[gr.Video(), gr.Slider(minimum=1, maximum=20, step=1),
262
+ gr.Radio(["retinaface", "mtcnn", "opencv", "ssd", "dlib", "mediapipe"], label="Detector Backend",
263
+ value="retinaface")],
264
+ outputs=["text", gr.Gallery(label="Analyzed Frames")],
265
+ title="Video Sentiment Analysis"
266
+ )
267
+
268
+ text_interface = gr.Interface(
269
+ fn=classify_and_plot,
270
+ inputs=[gr.Textbox(label="Hashtag"),
271
+ gr.Radio(["latest", "top"], label="Mode"),
272
+ gr.Slider(1, 1000, step=1, label="Number of Tweets"),
273
+ gr.Textbox(label="Since Date (YYYY-MM-DD)"),
274
+ gr.Textbox(label="Until Date (YYYY-MM-DD)")],
275
+ outputs=[gr.DataFrame(label="Scraped Tweets"), gr.Plot()],
276
+ title="Social Media Sentiment Analysis"
277
+ )
278
+
279
+ environment_interface = gr.Interface(
280
+ fn=classify_environment,
281
+ inputs=[gr.Slider(minimum=0, maximum=500, step=1, label="AQI"),
282
+ gr.Slider(minimum=0, maximum=110, step=1, label="Noise"),
283
+ gr.Slider(minimum=-10, maximum=50, step=1, label="Temperature"),
284
+ gr.Slider(minimum=0, maximum=100, step=1, label="Humidity"),
285
+ gr.Slider(minimum=0, maximum=500, step=1, label="PM2.5"),
286
+ gr.Slider(minimum=250, maximum=6000, step=1, label="CO2")],
287
+ outputs="text",
288
+ title="Environment Sentiment Analysis"
289
+ )
290
+
291
+ # The overall_interface
292
+ # Update the overall_interface
293
+ overall_interface = gr.Interface(
294
+ fn=classify_overall_sentiment,
295
+ inputs=[gr.Video(),
296
+ gr.Textbox(label="Hashtag"), gr.Radio(["latest", "top"], label="Mode"),
297
+ gr.Slider(1, 1000, step=1, label="Number of Tweets"),
298
+ gr.Textbox(label="Since Date (YYYY-MM-DD)"), gr.Textbox(label="Until Date (YYYY-MM-DD)"),
299
+ gr.Slider(minimum=0, maximum=500, step=1, label="AQI"),
300
+ gr.Slider(minimum=0, maximum=110, step=1, label="Noise"),
301
+ gr.Slider(minimum=-10, maximum=50, step=1, label="Temperature"),
302
+ gr.Slider(minimum=0, maximum=100, step=1, label="Humidity"),
303
+ gr.Slider(minimum=0, maximum=500, step=1, label="PM2.5"),
304
+ gr.Slider(minimum=250, maximum=6000, step=1, label="CO2")],
305
+ outputs=["text", gr.Gallery(), gr.DataFrame(), gr.Plot(), gr.Plot()],
306
+ title="Overall Sentiment Analysis"
307
+ )
308
+
309
+ scraper_interface = gr.Interface(
310
+ fn=scrape_tweets,
311
+ inputs=[gr.Textbox(label="Hashtag"),
312
+ gr.Radio(["latest", "top"], label="Mode"),
313
+ gr.Slider(1, 1000, step=1, label="Number of Tweets"),
314
+ gr.Textbox(label="Since Date (YYYY-MM-DD)"),
315
+ gr.Textbox(label="Until Date (YYYY-MM-DD)")],
316
+ outputs=gr.DataFrame(),
317
+ title="Scrape Tweets"
318
+ )
319
+
320
+ # Combine Interfaces into Tabbed Layout
321
+ tabbed_interface = gr.TabbedInterface(
322
+ [video_interface, text_interface, environment_interface, overall_interface, scraper_interface],
323
+ ["Video Sentiment Analysis", "Social Media Sentiment Analysis", "Environment Sentiment Analysis",
324
+ "Overall Sentiment Analysis", "Scrape Tweets"])
325
+
326
+ # Launch the Interface
327
+ tabbed_interface.launch(debug=True, share=True)
tweets_kuru.csv ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Scraping Tweets for #women
2
+ User,Username,Tweet,Date
3
+ Ardoun Shop,@ArdounShop,https://www.zazzle.com/z/afyq6mnk?rf=238606493597814217 #humanrights #human #rights #lifeline #freedom #equality #ZazzleMade #manfashion #Women #socks,"Dec 31, 2023 · 11:52 PM UTC"
4
+ Purselogic WOMEN OF THE SENTRY,@purselogic,#WOMEN #GIRLS IF THIS VID SHOWS ONE THING... ...IT'S 'NEVER SAY NEVER' #WINDEPENDENTparty #WINDEPENDENTwomen #LOGICofFUTURE POLITICS,"Dec 31, 2023 · 11:51 PM UTC"
5
+ BusaraSA,@BusaraSA,"For full conversation, click on https://inv.tux.pizza/watch?v=LR4LmN1kT5w&si=iDOuYx6MaO6_691i @christabonnet is #CEO and Founder of The Difference Makers Group, a community-driven organisation that is dedicated to empowering #women and promoting #entrepreneurship. Wishing you a renewing and meaningful #2024!","Dec 31, 2023 · 11:46 PM UTC"
6
+ CreatedbyGODnotchance,@GodDBestAvenger,"When Students for Life, Kristen Hawkins and Abby Johnson and others post something against the evil act #abortion, there's always someone who says or implies that they ruin #women lives. No, Abortion has ruined a lot of females' lives and it have some females in the #grave.","Dec 31, 2023 · 11:45 PM UTC"
7
+ Dudu Msomi,@DuduMsomi,"For full conversation, click on https://inv.tux.pizza/watch?v=LR4LmN1kT5w&si=iDOuYx6MaO6_691i @christabonnet is #CEO and Founder of The Difference Makers Group, a community-driven organisation that is dedicated to empowering #women and promoting #entrepreneurship. Wishing you a renewing and meaningful #2024!","Dec 31, 2023 · 11:42 PM UTC"
8
+ Kate *Non Compliant* 🚫🙅🏼‍♀️,@KingdomRise7,"Finally, you ladies can feel like one of the #Men! 🤦🏼‍♀️🙄 #WomenEmpowerment #Women #LGBTQ #Trans #Cult","Dec 31, 2023 · 11:41 PM UTC"
9
+ Meilleure Mode,@meilleuremode,LANE BRYANT WOMEN'S DEEP TEAL LONG SLEEVE TWIST WAIST MIDI SHEATH DRESS Sz 22/24 https://ift.tt/GIV5391 #women #dress #lingerie #dance #ladies #ebay,"Dec 31, 2023 · 11:39 PM UTC"
10
+ freedom fighter,@BreatheCouture,#handmade and #vintage #jewelry on Sale etsy.me/3Ok42Sa #fashion #jewellery #style #beauty #giftideas #men #women #fashionblogger #jewelryaddict #jewelryforsale. #HolidayGiftGuide #BoxingWeekSale #sundayvibes #HappyNewYear,"Dec 31, 2023 · 11:37 PM UTC"
11
+ Baccara,@BaccaraOficial,"Por un año lleno de Salud, Amor, Ilusión y Mucha Música ❤️❤️❤️ Feliz Año Nuevo 🎆 Happy New Year ! Feliz 2024 🍾🥂 #FelizAñoNuevo #FelizAño #HappyNewYear #Feliz2024 #NewYear #Welcome2024 #Bienvenido2024 #NuevoAño #Enero #FelizAño #Music #Singers #Women #Baccara 🌹","Dec 31, 2023 · 11:36 PM UTC"
12
+ MaryfromMarin,@MaryfromMarin,Hamas’ Mass Rape of Israeli Women Exposed in Unlikely Place https://townhall.com/columnists/alanjosephbauer/2023/12/31/hamas-mass-rape-of-israeli-women-exposed-in-unlikely-place-n2633009 .#tcot #ccot #NYT #Hamas #rape #Israeli #women @wombat_socho @GoldBaron08 @PubliusNV @MikeProof @Arqahn @soonintheclouds,"Dec 31, 2023 · 11:36 PM UTC"
13
+ ORF Marathi,@ORFMarathi,भारताने महिला सबलीकरणासाठीच्या आपल्या वचनबद्धतेचे पालन करणे व त्यासोबतच देशाच्या व्यापार परिसंस्थेतील जेंडर गॅप कमी करण्यासाठी प्रयत्न करणे गरजेचे आहे. https://orfonline.org/marathi/research/womens-participation-in-indias-trade-ecosystem #women #WomenEmpowerment #ecosystem #trade,"Dec 31, 2023 · 11:30 PM UTC"
14
+ The Centre for New Economic Diplomacy,@ORF_CNED,"With the passing of the long-awaited #Women’s Reservation Bill this year that reserves legislative seats for #women, there are lessons to be drawn from the achievements & failures in their experiences in local government:@sunaina_kumar & @AmbarKumarGhos1 https://tinyurl.com/33fdc43r","Dec 31, 2023 · 11:30 PM UTC"
15
+ Lisa the Resolute,@lisa_enough,Hey women Have we fucking had enough yet? Billions of our money invested in #ResourceWars But fucking zero For actual #WarOnWomen in this Fkn cuntry Fvck you @AustralianLabor You don’t give a fvck about #women #dv #fv #sa #rape #femicide Ask us survivors,"Dec 31, 2023 · 11:28 PM UTC"
16
+ Lara,@RageOfDemeter,➡️ Getting to know #Women #Liberation #Ideology as basis of todays #JinJiyanAzadîRevolution in the Middle East ➡️ Understanding the #Source for the breathtaking Revolutionary #Spirit of the People in #Kurdistan,"Dec 31, 2023 · 11:26 PM UTC"
17
+ ORF Bangla,@orfbangla,"স্থিতিশীল উন্নয়ন লক্ষ্যমাত্রা অর্জনের ক্ষেত্রে একটি লিঙ্গ–সংবেদনশীল গতিশীলতা ব্যবস্থার স্থান হল শহুরে নকশার কেন্দ্রে। বিশেষজ্ঞ- অনুশা কেশরকর গাভাঙ্কর, রাধিকা সারিন #women #gender #mobility #transportation #urban https://tinyurl.com/4f2x6wr4","Dec 31, 2023 · 11:15 PM UTC"