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Digital Cinema Package (DCP) probing and checking utility

Project description

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ClairMeta

ClairMeta is a python package for Digital Cinema Package (DCP) probing and checking.

Features

  • DCP Probe:
    • Metadata extraction of the whole DCP, including all XML fields and MXF assets inspection.

  • DCP Checker:
    • SMPTE / Interop standard convention

    • Integrity (MIME type, size, hash) of all assets

    • Foreign file identification

    • XSD Schema validation for XML files (VOLINDEX, ASSETMAP, CPL, PKL)

    • Digital signature validation (CPL, PKL)

    • Intra / Inter Reels integrity and coherence

    • Metadata match between CPL assets and MXF headers

    • Re-link VF / OV

    • Picture tests : FrameRate, BitRate

    • Sound tests : Channels, Sampling

    • Subtitle : Deep inspection of Interop and SMPTE subtitles

  • DSM / DCDM Checker:
    • Basic image file sequence validation with some specific rules.

Installation

Requirements:

  • Python: 3.6 or later

  • Platform: Windows (with limitations), macOS, Linux

  • External (non-python) dependencies:
    • asdcplib

    • mediainfo (opt)

    • sox (opt)

Install from PyPI package (this does not install external dependencies):

pip install clairmeta

If you need help installing the external dependencies, you can have a look at our continuous integration system, specifically the .github folder.

Usage

General

As a command line tool:

# Probing
python3 -m clairmeta.cli probe -type dcp path/to/dcp
python3 -m clairmeta.cli probe -type dcp path/to/dcp -format json > dcp.json
python3 -m clairmeta.cli probe -type dcp path/to/dcp -format xml > dcp.xml

# Checking
python3 -m clairmeta.cli check -type dcp path/to/dcp
python3 -m clairmeta.cli check -type dcp path/to/dcp -format json > check.json
python3 -m clairmeta.cli check -type dcp path/to/dcp -format xml > check.xml
python3 -m clairmeta.cli check -type dcp path/to/dcp -kdm /path/to/kdm -key /path/to/privatekey
python3 -m clairmeta.cli check -type dcp path/to/dcp -progress

As a python library:

from clairmeta import DCP

dcp = DCP("path/to/dcp")
dcp.parse()
status, report = dcp.check()
# Check DCP VF against OV
status, report = dcp.check(ov_path="/path/to/dcp_ov")
# DCP check with console progression report
from clairmeta.utils.file import ConsoleProgress

status, report = dcp.check(hash_callback=ConsoleProgress())
# Alternatives
# - function matching utils.file.ConsoleProgress.__call__ signature
# - derived class from utils.file.ConsoleProgress

Profiles

Check profile allow custom configuration of the DCP check process such as bypassing some unwanted tests or error level specification. To implement a check profile, simply write a JSON file derived from this template (actual content listed below is for demonstration purposes only):

  • criticality key allow custom criteria level specification, check name can be incomplete to quickly ignore a bunch of tests, default is used if no other match where found.

  • bypass key allow specific test bypass, incomplete names are not allowed.

{
    "criticality": {
        "default": "ERROR",
        "check_dcnc_": "WARNING",
        "check_cpl_reel_duration_picture_subtitles": "WARNING",
        "check_picture_cpl_avg_bitrate": "WARNING",
        "check_picture_cpl_resolution": "WARNING"
    },
    "bypass": ["check_assets_pkl_hash"]
}

Custom profile check:

python3 -m clairmeta.cli check -type dcp path/to/dcp -profile path/to/profile.json
from clairmeta import DCP
from clairmeta.profile import load_profile

dcp = DCP("path/to/dcp")
profile = load_profile("/path/to/profile.json")
status, report = dcp.check(profile=profile)

Logging

Logging is customizable, see the settings.py file or below. By default ClairMeta logs to stdout and a rotated log file.

'level': 'INFO'  # Minimum log level
'enable_console': True  # Enable / Disable stdout logging
'enable_file': True  # Enable / Disable file logging
'file_name': '/log/path/clairmeta.log'  # Log file absolute path
'file_size': 1e6  # Individual log file maximum size
'file_count': 10  # Number of files to rotate on

Contributing

  • To setup your environment follow these steps:

git clone https://github.com/Ymagis/ClairMeta.git
cd clairmeta
git clone https://github.com/Ymagis/ClairMeta_Data tests/resources

pip install pipenv
pipenv install --dev
pipenv shell

# Code... and tests
pytest --doctest-modules
  • Open a Pull Request

  • Open an Issue

Changes

The release changes are available on Github: https://github.com/Ymagis/ClairMeta/releases

References

The following sources / software were used:

About

http://www.ymagis.com/

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