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moviepy

Edit and compose video with Python using MoviePy. Use when a user asks to programmatically edit videos, create video montages, add text overlays, build automated video pipelines, composite multiple clips, apply video effects, generate social media videos from templates, concatenate clips, extract audio, create GIFs, build slideshows, add transitions, resize and crop videos, or integrate video editing into Python applications. Covers MoviePy 2.x for compositing, effects, text, and rendering.

#moviepy#python#video-editing#compositing#automation
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed moviepy v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Write a blog post about the benefits of AI-assisted development"
  • "Create social media copy for the product launch announcement"

Documentation

Overview

Edit video programmatically with MoviePy — the Python library for video compositing, cutting, effects, and rendering. Ideal for automated video pipelines: social media content generation, bulk video processing, slideshow builders, subtitle embedding, template-based video creation, and any workflow where you need code-driven video editing without a GUI. Built on ffmpeg.

Instructions

Step 1: Installation

bash
pip install moviepy
apt install -y ffmpeg         # Ubuntu/Debian
# Optional for text: apt install -y imagemagick
# Or: pip install Pillow (MoviePy v2.x uses PIL for text)

Step 2: Basic Operations

python
from moviepy import VideoFileClip, AudioFileClip

clip = VideoFileClip("input.mp4")
print(f"Duration: {clip.duration}s, Size: {clip.size}, FPS: {clip.fps}")

trimmed = clip.subclipped(10, 60)            # 10s to 60s
resized = clip.resized(height=720)            # Maintain aspect ratio
resized = clip.resized((1080, 1920))          # Force size
cropped = clip.cropped(x1=100, y1=50, x2=1820, y2=1030)
fast = clip.with_speed_scaled(2.0)            # 2x speed
silent = clip.without_audio()

trimmed.write_videofile("output.mp4", fps=24, codec="libx264",
    audio_codec="aac", bitrate="5000k", preset="medium", threads=4)
clip.subclipped(5, 10).write_gif("output.gif", fps=15)
clip.close()

Step 3: Concatenation & Composition

python
from moviepy import VideoFileClip, concatenate_videoclips, CompositeVideoClip, ColorClip

# Concatenate clips sequentially
final = concatenate_videoclips([
    VideoFileClip("scene1.mp4"),
    VideoFileClip("scene2.mp4"),
    VideoFileClip("scene3.mp4"),
])

# Composite (overlay layers)
bg = ColorClip(size=(1920, 1080), color=(15, 23, 42), duration=10)
main = VideoFileClip("main.mp4").resized(height=800).with_position("center")
logo = (VideoFileClip("logo.png", duration=10)
        .resized(height=60).with_position((1820, 30)))

composite = CompositeVideoClip([bg, main, logo], size=(1920, 1080))
composite.write_videofile("composite.mp4", fps=30)

Step 4: Text Overlays

python
from moviepy import TextClip, CompositeVideoClip, VideoFileClip

video = VideoFileClip("input.mp4")
title = (TextClip(text="Episode 1: Getting Started",
                  font_size=60, color="white", font="Arial-Bold",
                  stroke_color="black", stroke_width=2)
         .with_duration(5).with_position("center").with_start(1))

subtitle = (TextClip(text="Welcome to the show",
                     font_size=36, color="white", bg_color="rgba(0,0,0,128)")
            .with_duration(4).with_position(("center", 900))
            .with_start(3).crossfadein(0.5).crossfadeout(0.5))

final = CompositeVideoClip([video, title, subtitle])
final.write_videofile("titled.mp4")

Step 5: Audio Operations

python
from moviepy import VideoFileClip, AudioFileClip, CompositeAudioClip

video = VideoFileClip("input.mp4")
video.audio.write_audiofile("extracted.mp3")

# Mix audio tracks
original = video.audio.with_volume_scaled(0.3)
music = AudioFileClip("bg_music.mp3").with_volume_scaled(0.15)
voiceover = AudioFileClip("narration.mp3")
mixed = CompositeAudioClip([original, music, voiceover])
final = video.with_audio(mixed)
final.write_videofile("mixed.mp4")

Step 6: Effects & Custom Filters

python
from moviepy import VideoFileClip, vfx

clip = VideoFileClip("input.mp4")
clip.with_effects([vfx.MirrorX()])           # Mirror horizontally
clip.with_effects([vfx.BlackAndWhite()])      # Grayscale
clip.with_effects([vfx.FadeIn(1), vfx.FadeOut(2)])

# Custom frame-by-frame effect
def add_vignette(frame):
    import numpy as np
    rows, cols = frame.shape[:2]
    X, Y = np.meshgrid(np.arange(cols) - cols/2, np.arange(rows) - rows/2)
    mask = 1 - np.clip(np.sqrt(X**2 + Y**2) / (max(rows, cols) * 0.5), 0, 1)
    return (frame * mask[:, :, np.newaxis] ** 1.5).astype("uint8")

vignetted = clip.image_transform(add_vignette)

Step 7: Batch Processing

python
import os
from moviepy import VideoFileClip, TextClip, CompositeVideoClip

def process_video(input_path, output_path, watermark_text="@mychannel"):
    clip = VideoFileClip(input_path).resized(height=1080)
    watermark = (TextClip(text=watermark_text, font_size=24, color="white")
                 .with_opacity(0.5).with_duration(clip.duration).with_position((20, 20)))
    final = CompositeVideoClip([clip, watermark])
    final.write_videofile(output_path, fps=clip.fps, codec="libx264",
                          audio_codec="aac", preset="fast", threads=4)
    clip.close()

input_dir, output_dir = "raw_videos", "processed"
os.makedirs(output_dir, exist_ok=True)
for f in os.listdir(input_dir):
    if f.endswith((".mp4", ".mov", ".avi")):
        process_video(os.path.join(input_dir, f),
                      os.path.join(output_dir, f.rsplit(".", 1)[0] + ".mp4"))

Examples

Example 1: Generate 30 Instagram story videos from a JSON config

User prompt: "I have a products.json file with 30 entries, each containing name, price, tagline, and image_path. Write a Python script that generates a 1080x1920 Instagram story for each product with the product image as background, name in bold white at the top, price in green, and tagline at the bottom with a fade-in."

The agent will write a script that loads products.json, iterates over each entry, creates a ColorClip background at 1080x1920, loads the product image and resizes it to fill the frame, creates TextClip layers for the name (72px, bold, top), price (56px, green #22c55e, center), and tagline (36px, bottom with crossfadein(0.5)), composites them with CompositeVideoClip, renders each to stories/{name}.mp4 at 30fps, and closes all clips.

Example 2: Concatenate interview clips with title cards and background music

User prompt: "I have 5 interview clips in /footage/ named q1.mp4 through q5.mp4. Create a script that puts a 3-second dark title card with white text before each clip showing 'Question 1' through 'Question 5', concatenates everything, adds background music from ambient.mp3 at 20% volume, and exports as interview_final.mp4."

The agent will write a script that builds title cards using ColorClip with dark background and TextClip for each question number, loads each interview clip with VideoFileClip, interleaves title cards and clips into a list, concatenates with concatenate_videoclips, loads ambient.mp3 as an AudioFileClip trimmed to the total duration at 20% volume, mixes it with the original audio using CompositeAudioClip, and writes the final video.

Guidelines

  • Always call clip.close() after writing output to free ffmpeg processes and file handles, especially in batch loops
  • MoviePy 2.x changed many method names from 1.x; use subclipped() not subclip(), resized() not resize(), with_position() not set_position()
  • Set threads=4 or higher in write_videofile() for multi-core encoding, and use preset="fast" for batch jobs where speed matters more than file size
  • For text rendering, MoviePy 2.x uses Pillow by default; install ImageMagick only if you need the method="caption" word-wrapping feature
  • Large batch jobs can exhaust RAM since each clip keeps decoded frames in memory; process one clip at a time and close it before starting the next

Information

Version
1.0.0
Author
terminal-skills
Category
Content
License
Apache-2.0

Use Cases

→Produce Video Content with Programmatic Editing and Waveform Visualization