Annual Video Statistics Recap

The Idea

You’ve uploaded hundreds of videos this year. You’ve run thousands of searches. Your automation has processed countless scenes. But how do you celebrate and share those numbers in a way that actually captivates people? Traditional dashboards and spreadsheets are boring. What if you could transform your video analytics into a shareable cinematic recap video?

What You’ll Build

Turn your video analytics into a shareable recap video. This system creates a cinematic journey through your video stats:

Total minutes uploaded with growth metrics
Search activity visualization
Clips generated via automation
Scenes and frames analyzed
All set to music with dynamic video grids and text overlays

All powered by VideoDB’s Editor SDK — turning data into a visual story through code.

Setup

Install Dependencies

pip install videodb

Connect to VideoDB

import json
import random
import videodb
from videodb import MediaType, play_stream

# Connect to VideoDB
api_key = "your_api_key"
conn = videodb.connect(api_key=api_key)
coll = conn.get_collection()

Implementation

Step 1: Calculate Your Video Metrics

# Get all videos from your collection
videos = coll.get_videos()

TOTAL_SECONDS = 0
for v in videos:
  TOTAL_SECONDS += v.length

# Core metrics
TOTAL_MINUTES = round(TOTAL_SECONDS / 60, 1)
TOTAL_SEARCHES = 2573
CLIPS_GENERATED = 574
SCENES_ANALYZED = 248
FRAMES_ANALYZED = 3200

# Previous year comparison
PREV_YEAR_MINUTES = 6400

# Time conversions
TOTAL_HOURS = round(TOTAL_MINUTES / 60, 1)
TOTAL_DAYS = round(TOTAL_HOURS / 24, 1)

# Growth percentage
MINUTES_GROWTH = round(((TOTAL_MINUTES - PREV_YEAR_MINUTES) / PREV_YEAR_MINUTES) * 100)

Step 2: Upload Background Music

# Upload background music as audio
audio = coll.upload("https://youtu.be/vIEi8AoP_Fw?si=AUVUt6Komqtt7rWI", media_type="audio")

Step 3: Create Timeline with 5 Sections

Initialize the timeline and set up base configuration:

from videodb.editor import (
    Timeline, Track, Clip, VideoAsset, AudioAsset, TextAsset,
    Offset, Transition, Font, Filter,
)

# Use subset of videos
videos = videos[20:40]

# Create timeline
timeline = Timeline(conn)
timeline.background = "#E85E00"
track = Track()
video_track = Track()

# Add background music
b_music = Clip(
    asset=AudioAsset(id=audio.id, start=0, volume=1),
    duration=28,
)
track.add_clip(4, b_music)

Step 4: Build Intro Section (0-5s)

Create a dynamic mosaic effect with 60 video clips:

# Intro text
intro_text = Clip(
    asset=TextAsset(
        text="2025 was a blur. Let's index it.",
        font=Font(size=60, family="Roboto Bold"),
    ),
    duration=5,
    transition=Transition(in_="fade"),
)
track.add_clip(1, intro_text)

# Create 60 video clips with varying scales and random positioning
for i in range(60):
    scale_value = 0.5 + (i * 0.025)  # Scale: 0.5 to 0.975
    start_time = random.randint(0, 4)
    volume = 0.5
    if start_time == 3:
        volume = 0.3
    elif start_time == 4:
        volume = 0.3

    video = random.choice(videos)

    video_clip = Clip(
        asset=VideoAsset(
            id=video.id,
            start=random.randint(10, int(video.length - 10)),
            volume=volume,
        ),
        duration=1,
        scale=scale_value,
        fit=None,
        offset=Offset(x=random.uniform(-0.5, 0.5), y=random.uniform(-0.5, 0.5)),
    )

    video_track.add_clip(start=start_time, clip=video_clip)

Step 5: Build Upload Metrics Section (6-13s)

Display total minutes uploaded with zoom-out effect:

# Section 1 text
section1_text = Clip(
    asset=TextAsset(
        text=f"You uploaded {TOTAL_MINUTES:,} minutes\nof video content.\n\nThat's {TOTAL_HOURS} hours.\nOr {TOTAL_DAYS} full days of footage.\n\n↑ {MINUTES_GROWTH}% from 2024",
        font=Font(size=48, family="default"),
    ),
    duration=7,
)
track.add_clip(6, section1_text)

# Zoom out effect with greyscale filter
for i in range(20):
    scale_value = 0.5 + (i * 0.0263)  # Scale: 0.5 to 1.0
    start_time = 6 + (i * 0.175)

    video = random.choice(videos)
    video_start = random.randint(10, max(11, int(video.length - 10)))

    video_clip = Clip(
        asset=VideoAsset(
            id=video.id,
            start=video_start,
            volume=0.15,
        ),
        duration=1,
        scale=scale_value,
        fit="crop",
        filter=Filter.greyscale,
    )

    video_track.add_clip(start=start_time, clip=video_clip)

Step 6: Build Search Analytics Section (13-19s)

Create 3 rows of horizontal scanning video clips:

# Section 2 text
section2_text = Clip(
    asset=TextAsset(
        text=f"{TOTAL_SEARCHES:,} questions asked.\n\nYour videos aren't just stored—\nthey're understood.",
        font=Font(size=58, family="default"),
    ),
    duration=6,
)
track.add_clip(13, section2_text)

# Create horizontal scanning effect with 3 rows
rows = [
    {"y": -0.5, "num_clips": 20, "duration": 0.25, "scale": 0.35},  # Top row
    {"y": 0, "num_clips": 15, "duration": 0.33, "scale": 0.45},     # Middle row
    {"y": 0.5, "num_clips": 12, "duration": 0.42, "scale": 0.35},   # Bottom row
]

clip_idx = 0
for row in rows:
    for i in range(row["num_clips"]):
        x_pos = -0.9 + (i * 0.1)
        video = videos[clip_idx % len(videos)]

        video_start = 30 + (clip_idx % 10)
        if video_start > video.length - 10:
            video_start = 15

        video_clip = Clip(
            asset=VideoAsset(
                id=video.id,
                start=video_start,
                volume=0.15,
            ),
            duration=row["duration"],
            scale=row["scale"],
            fit="crop",
            offset=Offset(x=x_pos, y=row["y"]),
        )
        video_track.add_clip(start=12 + (i * row["duration"]), clip=video_clip)
        clip_idx += 1

Step 7: Build Automation Stats Section (19-25s)

Large background clips with cycling effect:

# Section 3 text
section3_text = Clip(
    asset=TextAsset(
        text=f"{CLIPS_GENERATED:,} clips\ngenerated via code.\n\nAutomation at its finest.",
        font=Font(size=62, family="default"),
    ),
    duration=6,
)
track.add_clip(19, section3_text)

# Cycling background effect
for i in range(3):
    video = videos[(i + 5) % len(videos)]
    video_start = 20 + (i * 15)
    if video_start > video.length - 10:
        video_start = 10

    bg_clip = Clip(
        asset=VideoAsset(
            id=video.id,
            start=video_start,
            volume=0.05,
        ),
        duration=2,
        scale=1.2,
        fit="crop",
        filter=Filter.greyscale,
        opacity=0.2,
        z_index=0,
    )
    video_track.add_clip(start=19 + (i * 2), clip=bg_clip)

Step 8: Build Intelligence Metrics Section (25-31s)

3x3 grid with scanning animation:

# Section 4 text
section4_text = Clip(
    asset=TextAsset(
        text=f"{SCENES_ANALYZED:,} scenes analyzed\n{FRAMES_ANALYZED:,} Frames Analyzed\n\nPure video intelligence.\nPowered by you.",
        font=Font(size=52, color="#FFFFFF", family="Arial Bold"),
    ),
    duration=5,
)
track.add_clip(25, section4_text)

# 3x3 grid with scanning effect
grid_positions = [
    (-0.4, -0.4), (0, -0.4), (0.4, -0.4),  # Top row
    (-0.4, 0), (0, 0), (0.4, 0),           # Middle row
    (-0.4, 0.4), (0, 0.4), (0.4, 0.4),     # Bottom row
]

for idx, (x_pos, y_pos) in enumerate(grid_positions):
    video = videos[idx % len(videos)]

    video_start = 50 + (idx % 10)
    if video_start > video.length - 10:
        video_start = 20

    video_clip = Clip(
        asset=VideoAsset(
            id=video.id,
            start=video_start,
            volume=0.1,
        ),
        duration=0.6,
        scale=0.28,
        fit="crop",
        offset=Offset(x=x_pos, y=y_pos),
        transition=Transition(in_="fade", duration=0.15),
        filter=Filter.contrast if idx % 2 == 0 else Filter.boost,
        opacity=0.9,
    )

    video_track.add_clip(start=24.5 + (idx * 0.08), clip=video_clip)

# Add cascading columns
num_columns = 2
clips_per_column = 8
for col in range(num_columns):
    x_pos = -0.3 + (col * 0.6)

    for row in range(clips_per_column):
        y_pos = -0.7 + (row * 0.23)
        clip_idx = col * clips_per_column + row

        video = videos[clip_idx % len(videos)]

        video_start = 40 + (clip_idx % 8)
        if video_start > video.length - 10:
            video_start = 25

        video_clip = Clip(
            asset=VideoAsset(
                id=video.id,
                start=video_start,
                volume=0.15,
            ),
            duration=0.3,
            scale=0.3,
            fit="crop",
            offset=Offset(x=x_pos, y=y_pos),
        )
        video_track.add_clip(start=25.7 + (row * 0.3) + (col * 0.1), clip=video_clip)

Step 9: Add Outro and Render

# Outro text
outro_text = Clip(
    asset=TextAsset(
        text="Ready for 2026? Build it.",
        font=Font(size=60, family="Roboto Bold")
    ),
    duration=2,
)
track.add_clip(31, outro_text)

# Add tracks to timeline
timeline.add_track(video_track)
timeline.add_track(track)

# Generate stream
stream_url = timeline.generate_stream()

What You Get

A professional video that:

Visualizes your video metrics in real-time
Uses 100+ of your actual videos in the composition
Creates dynamic animations and transitions
Pairs everything with music
Tells the story of your year in video data

Perfect for:

Marketing your platform
Celebrating milestones with users
Annual reports
Social media recap posts
Team celebrations

Here’s the final rendered recap video:

The Result

With this system, you transform dry analytics into engaging visual stories. Your users see not just numbers, but a cinematic journey through what you’ve accomplished together. It’s data visualization meets creative storytelling — all powered by code.

Explore the Full Notebook

Open the complete implementation with procedural animation logic, timing calculations, and advanced effects.

Faceless Video Creator

Generate complete videos from scripts

TikTok Lyric Videos

Auto-sync lyrics to music with animations

Overview

Agentic Workflows

Video Search and Understanding

Live Intelligence

Content Factory

Programmatic Editing

Safety & Compliance

The Idea

What You’ll Build

Setup

Install Dependencies

Connect to VideoDB

Implementation

Step 1: Calculate Your Video Metrics

Step 2: Upload Background Music

Step 3: Create Timeline with 5 Sections

Step 4: Build Intro Section (0-5s)

Step 5: Build Upload Metrics Section (6-13s)

Step 6: Build Search Analytics Section (13-19s)

Step 7: Build Automation Stats Section (19-25s)

Step 8: Build Intelligence Metrics Section (25-31s)

Step 9: Add Outro and Render

What You Get

The Result

Explore the Full Notebook

Faceless Video Creator

TikTok Lyric Videos

​The Idea

​What You’ll Build

​Setup

​Install Dependencies

​Connect to VideoDB

​Implementation

​Step 1: Calculate Your Video Metrics

​Step 2: Upload Background Music

​Step 3: Create Timeline with 5 Sections

​Step 4: Build Intro Section (0-5s)

​Step 5: Build Upload Metrics Section (6-13s)

​Step 6: Build Search Analytics Section (13-19s)

​Step 7: Build Automation Stats Section (19-25s)

​Step 8: Build Intelligence Metrics Section (25-31s)

​Step 9: Add Outro and Render

​What You Get

​The Result

Explore the Full Notebook

​Related Tutorials

Faceless Video Creator

TikTok Lyric Videos

The Idea

What You’ll Build

Setup

Install Dependencies

Connect to VideoDB

Implementation

Step 1: Calculate Your Video Metrics

Step 2: Upload Background Music

Step 3: Create Timeline with 5 Sections

Step 4: Build Intro Section (0-5s)

Step 5: Build Upload Metrics Section (6-13s)

Step 6: Build Search Analytics Section (13-19s)

Step 7: Build Automation Stats Section (19-25s)

Step 8: Build Intelligence Metrics Section (25-31s)

Step 9: Add Outro and Render

What You Get

The Result

Related Tutorials