Introduction

motionpicture is a Python library to simplify the creation of videos out of individual frames. With motionpicture, you just have to specify how to produce a generic frame, and the package will do everything else for you. In motionpicture, your code can be configured via command-line or text files: turning your code into a plug-in for motionpicture is trivial, so you will be able to reuse your code with ease.

Examples

There are two important ingredients to use motionpicture: mopi, and a movie file. mopi is a command-line utility that comes when you install this package. It will be your main interface to motionpicture and it has a comprehensive --help function. A movie file is a recipe on how to produce a generic frame. With few small restrictions, you have full control over this file (more info in section Movie files).

In these examples we are going to use matplotlib to do the plotting, but you are completely free to generate frames with any Python package you wish.

Unveiling a sine wave

In this example, we show how to use mopi to generate the following video.

To produce this video, we need the following movie file.

import matplotlib.pyplot as plt
import numpy as np

class MOPIMovie:
    def __init__(self, _args):
        self.times = np.linspace(0, 10, 100)
        self.values = np.sin(self.times)

    def get_frames(self):
        # Here we tell motionpicture what we consider a frame
        return range(len(self.times))

    def make_frame(self, path, frame_number):
        # Here we plot a specific frame
        plt.clf()
        plt.plot(self.times[:frame_number], self.values[:frame_number])
        plt.xlim([0, self.times[-1]])
        plt.ylim([-1, 1])
        plt.savefig(path)

Assuming this file is saved in sin_wave.py, we run

mopi -m sin_wave.py -o frames_dir --parallel

This is produce the individual frames in a folder frames_dir using all the CPUs available on your machine. Then, it will glue the frames together in a video that has the default name of video.mp4. If you want to change name, or other properties (e.g., the fps), you can add options to mopi

mopi -m sin_wave.py -o frames_dir --parallel --fps 10 --movie-name sin_wave

This will produce a sin_wave.mp4 video with 10 frames per second instead

Unveiling a sine wave with controllable frequency

Let us continue on the example of the sine wave, and let us assume that we want to explore different frequencies.

We can edit the previous movie file adding a mopi_add_custom_options function:

def mopi_add_custom_options(parser):
    """Add command-line options specific to this movie."""
    parser.add_argument(
        "-f",
        "--frequency",
        default=1,
        type=int,
        help="Frequency of the sine wave (default: %(default)s)",
    )

Then, we edit the __init__ function too:

def __init__(self, args):
    self.times = np.linspace(0, 10, 100)
    self.values = np.sin(args.frequency * self.times)

Movie files have to have an __init__ that takes two arguments. The second is a Namespace that contains all the controllable options. These arguments can be passed via command-line or configuration file.

mopi -m sin_wave.py -o frames_dir --parallel --frequency 3

This command will produce the following video.

Alternatively, you can put any of arguments in a config file conf, for example:

outdir: frames_dir
frequency: 3

Config files support several syntaxes. Once you have the file, just call

mopi sin_wave.py -c conf

You can use config files and command-line options at the same time, but in case of conflict, the command-line arguments have the precedence.

Unveiling data in an arbitrary file

Now that you have seen that you can control movies via command-line, it is time to introduce you to the plugin system in motionpicture.

Suppose we have two-column files with time series data, we can modify the movie file used in the previous example to animate those files, specifying which one at run-time.

def mopi_add_custom_options(parser):
    """Add command-line options specific to this movie."""
    parser.add_argument(
        "-f",
        "--file",
        required=True,
        help="File to plot",
    )

Then, we import numpy as np and edit the __init__ function too:

def __init__(self, args):
    self.times, self.values = np.loadtxt(args.file).T
    self.y_min, self.y_max = np.amin(self.value), np.amax(self.value)

We computed the minimum and maximum of the value so that we can adjust the y axis range. The make_frame method will be the same, with the exception that we change the plt.ylim([-1, 1]) line to plt.ylim([self.y_min, self.y_max]).

We can save this file as plot_timeseries and call mopi:

mopi -m plot_timeseries -o frames -f my_file.dat

Of course, we can add as many options as we wish to control the output. For instance, we may want to add a switch to use logarithmic axes instead. The class MOPIMovie has full access to the user-supplied options, so you can do anything you wish.

We did not hard-code anything in plot_timeseries, so the code will work for any dataset. However, if we want to use this file again, but in a different folder, we would have to copy it over, since mopi -m expects the path of the movie file. Alternatively, we can copy plot_timeseries to a specific folder of our choice, for example ~/.mopi_videos. Then, we can set the environment variable MOPI_MOVIES_DIR to be ~/.mopi_videos, and mopi will be able to find plot_timeseries from anywhere in your filesystem. In this case, you can simply call:

mopi plot_timeseries -o frames -f my_other_file.dat

Essentially, plot_timeseries became a plugin for motionpicture and you can animate any data without having to write new code. This is one of the greatest strengths of motionpicture, as it encourages you to write generic code that you can easily reuse.

Installation

motionpicture is available on PyPI. You can install it with pip:

pip3 install motionpicture

To produce the final video, you have to have ffmpeg installed. Without ffmpeg, you will not be able to glue together the frames, but you can still use motionpicture to render the frames.

Movie files

In the language of motionpicture, a movie file is a recipe on how to generate an individual frame. It is completely up to you how you do that, but motionpicture imposes some minimum requirements:

• It has to be a valid Python 3 file.
• It has to contain a class MOPIMovie with a method make_frame and a method get_frames.
• The method __init__ has to take two arguments.
• The method get_frames has to return an iterable (e.g., a list) that identifies each frame. The elements of this iterable are passed as the frame argument to make_frame.
• The method make_frame has to take two arguments, the path of the output of the frame, and frame, the value that identifies frame (typically the frame number). path is where the image has to be saved. You are in charge of saving the image using the save method of your plotting package.

Other than these requirements, you can do anything you want in the movie file (e.g., you can add more methods, functions, classes...).

To have support for the --overwrite option, the function make_frame must always write the data regardless of possible pre-existing files at destination.

⚠️ Due to its own nature, motionpicture has to execute any code that you supply. Do not use motionpicture with codes you do not trust!

mopi

mopi is a command-line utility with several options. Its --help flag can tell you what it can do:

General options:
  movie                 Movie to render among the ones found in MOPI_MOVIES_DIR. See bottom of the help message for list.
  -m MOVIE_FILE, --movie-file MOVIE_FILE
                        Path of the movie file.
  -c CONFIG, --config CONFIG
                        Config file path
  --movies-dir MOVIES_DIR
                        Folder where to look form movies.   [env var: MOPI_MOVIES_DIR]
  -o OUTDIR, --outdir OUTDIR
                        Output directory for frames and video.
  --snapshot SNAPSHOT   Only produce the specified snapshot (useful for testing).
  --overwrite           Overwrite files that already exist.
  --disable-progress-bar
                        Do not display the progress bar when generating frames.
  --parallel            Render frames in parallel.
  --skip-existing       Do not generate frames that already exist. No consistency checks are performed.
  --num-workers NUM_WORKERS
                        Number of cores to use (default: 8).
  --max-tasks-per-child MAX_TASKS_PER_CHILD
                        How many chunks does a worker have to process before it is respawned? Higher number typically leads to higher performance
                        and higher memory usage. (default: 1).
  --chunks-size CHUNKS_SIZE
                        How many frames does a worker have to do each time? Higher number typically leads to higher performance and higher memory usage.
  --only-render-movie   Do not generate frames but only render the final video.
  --frame-name-format FRAME_NAME_FORMAT
                        If only-render-movie is set, use this C-style frame name format instead of computing it. For example, '%04d.png' will
                        assemble a video with frames with names 0000.png, 0001.png, and so on, as found in the outdir folder.
  -v, --verbose         Enable verbose output.
  -h, --help            Show this help message and exit.

Frame selection:
  --min-frame MIN_FRAME
                        Do not render frames before this one.
  --max-frame MAX_FRAME
                        Do not render frames after this one.
  --frames-every FRAMES_EVERY
                        Render a frame every N (default: render all the possible frames).

Video rendering options:
  --movie-name MOVIE_NAME
                        Name of output video file, without extension (default: video).
  --extension EXTENSION
                        File extension of the video (default: mp4).
  --fps FPS             Frames-per-second of the video (default: 25).
  --codec CODEC         Codec to use for the final encoding. If not specified, it is determined from the file extension.
  --author AUTHOR       Author metadata in the final video.
  --title TITLE         Title metadata in the final video.
  --comment COMMENT     Comment metadata in the final video.

No movies found in the MOPI_MOVIES_DIR (.)

A useful option for debugging is --snapshot. If you pass the keyword --snapshot and the identifier for a specific frame (an element of the iterable MOPIMoive.get_frames()), mopi will only render that single frame. This can be used to test your movie file.

Another interesting option is --only-render-movie. This skips the generation of frames and only produces the final video. When this option is enable, mopi will still go through the selection of frames from the movie file, so options like --min-frame or --frames-every will affect the result. If you specify also --frame-name-format, you can skip this step too (which skips the movie file entirely), and just render the final video. This option requires a C-style format string to specify which files have to be assembled to the final video. This refers to the name of the files in the output folder.

Development

We use:

• Poetry to manage dependencies, build, and publish motionpicture.
• Black for formatting the code (with 89 columns).
• pytest for unit tests (with pytest-cov for test coverage).
• GitHub actions for continuous integration.

We are happy to accept contributions.

A note on the inner workings

Multiprocessing with Python is a pain. Hence, we need to hack our way lo support parallelism in such a way that is completely transparent to the user. To achieve this motionpicture uses two tricks:

• The movie file is evaluated verbatim with exec in the global namespace
• The MOPIMovie class is patched to a pMOPIMovie (always using exec) to provide a function p_make_frames that works better with multiprocessing.

So, motionpicture directly manipulates the global namespace to be able to use multiple processes. This can lead to surprises in the code, for example, MOPIMovie is used without apparently being imported.

Changelog

See NEWS.md for a changelog.

Credits

The idea for motionpicture originated from the SimVideo package developed by Wolfgang Kastaun.