Milestone 1 lab

Trace Python on the workbench

Six short exercises for following values through creative-media code. Python downloads only when you choose Run, and Stop ends the isolated runner.

6 exercises8–15 minutes eachRuns in this browser

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This lab supports standard Python, numpy, and pillow. Exercises that need other packages route to a cloud notebook or local Python setup.

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Six exercises, readable without JavaScript

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Variable slate · 8 min

Store the clip title and frame count in variables, then print one production-ready sentence that uses both values.

clip_title = "Night Shift"
frame_count = 240

# Print: Night Shift contains 240 frames.

Index the shot list · 8 min

Use zero-based indexing to print the close-up from the shot list. Do not change the list order.

shots = ["wide", "medium", "close-up"]

# Print the close-up by indexing shots.

Loop through takes · 12 min

Loop through every take and print a numbered review line for each one.

takes = ["take-a.mov", "take-b.mov", "take-c.mov"]

# Print lines such as: Review 1: take-a.mov

Return the QC verdict · 15 min

Complete the function so it returns PASS for scores of 0.8 or higher and REVIEW otherwise. Print both sample verdicts.

def qc_verdict(score):
    # Return "PASS" or "REVIEW".
    pass

print(qc_verdict(0.92))
print(qc_verdict(0.61))

Look up clip metadata · 12 min

Read the codec and duration from the metadata dictionary, then print: prores · 18 seconds.

clip = {
    "name": "harbour-01.mov",
    "codec": "prores",
    "duration_seconds": 18
}

# Look up two values and print the summary.

Trace and repair · 15 min

Trace the value passed into normalized_score, repair the wrong variable name, and make the script print 0.85.

raw_score = 85

def normalized_score(score):
    return value / 100

print(normalized_score(raw_score))

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