import sys
sys.path.append('../../')
from moviegoer.tables import film_id_from_film_directory, load_film_object
from random import choice

film_id = film_id_from_film_directory()
film_id

'the_invasion_2007'

film_obj = load_film_object(film_id)
film_obj.print_info()

*Film Information*
Title, Release Year: The Invasion (2007)
File Runtime: 01:39:21
Film Runtime (No Credits): 1:31:48

*Technical Details*
Aspect Ratio: 1.78
Avg. Shot Duration: 6.63
Avg. Brightness: 59
Avg. Contrast: 44

*Dialogue Cadence*
Sentences Per Minute: 16
Words Per Sentence 5.09
Questions Per Minute: 2.16
Pct. Questions: 13%

*Emotion*
Pct. Upset Faces: 68%
Profanity Per Minute: 0.03
Words Per Profanity: 2562
Exclamations Per Minute: 1.83

print(len(film_obj.scene_objects))
film_obj.display_scenes()

11

*Plot Context*
Context Themes: Counter({'transit': 268, 'driving': 264})
Potential Common Locations: Counter({'car': 264})
Establishing Shot Locations: Counter({'building': 16})
Descriptors: ['sitting']
Active Actions: Counter({'driving': 4, 'open': 3})

*Plot Context*
Establishing Shot Locations: Counter({'building': 9})
Named Participants: Counter({'ollie': 1, 'mom': 1})
Descriptors: ['indoors']
Right Wearing: Counter({'mask and a purple cape': 21, 'mask': 11, 'mask sitting': 1, 'mask and cape': 1})

*Plot Context*
Context Themes: Counter({'transit': 409, 'driving': 409, 'intimacy': 45})
Potential Common Locations: Counter({'car': 409})
Descriptors: ['indoors', 'sitting']
Active Actions: Counter({'kissing': 45})
Right Wearing: Counter({'suit': 89})

*Plot Context*
Descriptors: ['indoors']
Held Items: Counter({'cell phone': 3})
Active Actions: Counter({'seen': 2, 'peeking': 1, 'open': 1})
Right Wearing: Counter({'suit': 47})

*Plot Context*
Context Themes: Counter({'dining': 157})
Potential Common Locations: Counter({'kitchen': 157})
Potential Other Locations: Counter({'doorway': 2})
Named Participants: Counter({'carol': 1})
Descriptors: ['indoors', 'standing']
Left Wearing: Counter({'suit': 60})

*Plot Context*
Context Themes: Counter({'transit': 4, 'driving': 4, 'dining': 3})
Potential Common Locations: Counter({'car': 4, 'kitchen': 3})
Potential Other Locations: Counter({'street': 16, 'doorway': 2, 'hallway': 1, 'park': 1})
Establishing Shot Locations: Counter({'building': 20, 'train': 5})
Descriptors: ['indoors', 'standing']
Held Items: Counter({'clipboard': 11, 'pen': 6, 'clipboard standing': 5})
Active Actions: Counter({'open': 5, 'making': 1, 'blowing': 1, 'yelling': 1})
Left Wearing: Counter({'suit': 2, 'green jacket': 2, 'brown jacket': 2})

*Plot Context*
Descriptors: ['indoors', 'sitting']
Active Actions: Counter({'reading': 42, 'lit': 14})

*Plot Context*
Context Themes: Counter({'transit': 90})
Potential Common Locations: Counter({'airplane': 90})
Potential Other Locations: Counter({'hallway': 18, 'doorway': 4})
Establishing Shot Locations: Counter({'building': 5, 'train': 3})
Named Participants: Counter({'gene': 1})
Descriptors: ['indoors', 'standing']
Active Actions: Counter({'open': 1})

*Plot Context*
Potential Other Locations: Counter({'doorway': 30})
Descriptors: ['indoors', 'standing']

*Plot Context*
Context Themes: Counter({'intimacy': 103})
Descriptors: ['indoors']
Held Items: Counter({'child': 3, 'head': 1, 'long hair and a cell phone': 1})
Active Actions: Counter({'hugging': 99, 'kissing': 4})

*Plot Context*
Context Themes: Counter({'violence': 101, 'dining': 11})
Named Participants: Counter({'carol': 1})
Descriptors: ['indoors', 'standing']
Held Items: Counter({'gun': 101})
Active Actions: Counter({'pointing': 8, 'hiding': 2})

[None, None, None, None, None, None, None, None, None, None, None]

film_obj.chart_all_dialogue_emotional_indicators()

film_obj.chart_all_dialogue_shape()

film_obj.chart_all_dialogue_question_proportion()

film_obj.display_color_shots()

rand_scene = None
if film_obj.dialogue_objects:
    rand_scene = choice(film_obj.dialogue_objects)
    rand_scene.display_qna_frames()

if rand_scene:
    rand_scene.display_first_p_sentence_frames()

if rand_scene:
    rand_scene.display_second_p_address_frames()

film_obj.display_laughs()

[]

film_obj.display_unintelligible_language()

film_obj.display_self_intros()

film_obj.display_other_intros()

Mr. Lenk, this is Dr. Bennell.

This is Dr. Bennell.

This is Dr. Ben Driscoll.