photo-metadata 0.3.1

Python library to extract, read, modify, and write photo and video metadata (EXIF, IPTC, XMP) using ExifTool. Supports JPEG, RAW, and video files.

photo-metadata

Python library to extract, read, modify, and write photo and video metadata (EXIF, IPTC, XMP) using ExifTool. Supports JPEG, RAW, and video files.

---

---

📕 README_Japanese

---

photo-metadata is a Python library for extracting, manipulating, and writing metadata from photo and video files. It uses ExifTool as a backend and supports a wide range of image and video formats. Full support for Japanese tags is also provided.

---

Key Features

• Extract metadata from photos and videos
• Read, write, and delete metadata
• Convenient methods for various metadata operations
• Compare two Metadata objects
• Filter multiple files by metadata
• Rename multiple files based on capture date or other metadata

---

Supported OS

• Windows
• Linux

---

Installation

pip install photo-metadata

Dependencies

• [ExifTool] (needs to be installed separately; either add to PATH or provide full path)
• [tqdm] (automatically installed via pip; used for progress display)
• [charset-normalizer] (automatically installed via pip; used for encoding detection)

---

Configuring ExifTool

import photo_metadata

# Set the path to ExifTool
photo_metadata.set_exiftool_path(exiftool_path)

Notes

The default exiftool_path is "exiftool". If ExifTool is already in your PATH, calling set_exiftool_path is not required.

---

Metadata Class

The Metadata class is the core class for working with metadata.

from photo_metadata import Metadata

Initialization

metadata = Metadata(file_path="path/to/your/image.jpg")

• file_path (str): Path to the image file

Accessing Metadata

Metadata can be accessed like a dictionary.

Access using English tags:

date_time = metadata["EXIF:DateTimeOriginal"]
print(date_time)

Access using Japanese tags:

date_time = metadata[photo_metadata.key_ja_to_en("EXIF:撮影日時")]
print(date_time)

Modifying Metadata

You can modify metadata like a dictionary:

metadata["EXIF:DateTimeOriginal"] = "2024:02:17 12:34:56"

Writing Metadata to File

metadata.write_metadata_to_file()

Deleting Metadata

Metadata can be deleted using the del statement:

del metadata["EXIF:DateTimeOriginal"]

Comparison

Two Metadata objects can be compared using == and !=:

metadata1 = Metadata("image1.jpg")
metadata2 = Metadata("image2.jpg")

if metadata1 == metadata2:
    print("Metadata is identical")
else:
    print("Metadata is different")

---

Working with Multiple Files – MetadataBatchProcess Class

MetadataBatchProcess allows you to process metadata for multiple files.

from photo_metadata import MetadataBatchProcess

Initialization

mbp = MetadataBatchProcess(file_path_list)

Filter Files by Metadata

mbp.filter_by_metadata(
    keyword_list=["NEX-5R", 2012],
    exact_match=True,
    all_keys_match=True,
    search_by="value"
)

for file, md in mbp.metadata_objects.items():
    print(f"{os.path.basename(file)}")

This example keeps files whose metadata values include both "NEX-5R" and 2012.

Filter Using Custom Conditions

mbp.filter_by_custom_condition(
    lambda md: md[photo_metadata.key_ja_to_en("EXIF:F値")] >= 4.0
    and md[photo_metadata.key_ja_to_en("EXIF:モデル")] == 'NEX-5R'
)

for file, md in mbp.metadata_objects.items():
    print(f"{os.path.basename(file)}")

This example keeps files where the EXIF F-number is ≥ 4.0 and the camera model is 'NEX-5R'.

Rename Files Using Metadata

import os
from tkinter import filedialog
from photo_metadata import MetadataBatchProcess, Metadata

def date(md: Metadata):
    date = md.get_date('%Y-%m-%d_%H.%M.%S', default_time_zone="+00:00")
    if date == md.error_string:
        raise Exception("Not Found")
    return f"{date}-{MetadataBatchProcess.DUP_SEQ_1_DIGIT}"  # This is a duplicate sequence. It increments if duplicates exist, starting from 0. Must be included in the format.

file_path_list = list(map(os.path.normpath, filedialog.askopenfilenames()))
mbp = MetadataBatchProcess(file_path_list)

# Prepare rename creates new_name_dict for preview
mbp.prepare_rename(format_func=date)

print("new_name_dict")
for file, new_name in mbp.new_name_dict.items():
    print(f"{file}\n{new_name}")

print("\nerror_dist")
for file, new_name in mbp.error_files.items():
    print(f"{file}\n{new_name}")

input("Press Enter to rename files")

mbp.rename_files()

---

API Reference

photo_metadata

• get_key_map() -> dict: Returns a dictionary for Japanese key conversion.
• set_exiftool_path(exiftool_path: str | Path) -> None: Sets the path to exiftool.
• get_exiftool_path() -> Path: Returns the configured path to exiftool.
• set_jp_tags_json_path(jp_tags_json_path: str | Path) -> None: Sets the path to the Japanese tags JSON file.
• get_jp_tags_json_path() -> Path: Returns the configured path to the Japanese tags JSON file.
• key_en_to_ja(key_en: str) -> str: Converts an English key to its Japanese equivalent.
• key_ja_to_en(key_ja: str) -> str: Converts a Japanese key to its English equivalent.

photo_metadata.Metadata

• __init__(self, file_path: str | Path): Constructor.

• display_japanese(self, return_type: Literal["str", "print", "dict"] = "print") -> str: Displays metadata using Japanese keys.

• write_metadata_to_file(self, file_path: str = None) -> None: Writes metadata to a file.

• get_metadata_dict(self) -> dict: Returns the metadata as a dictionary.

• export_metadata(self, output_path: str = None, format: Literal["json", "csv"] = 'json', lang_ja_metadata: bool = False) -> None: Exports metadata to a file.

• keys(self) -> list[str]: Returns a list of metadata keys.

• values(self) -> list[Any]: Returns a list of metadata values.

• items(self) -> list[tuple[str, Any]]: Returns a list of key-value pairs for metadata.

• get_gps_coordinates(self) -> str: Returns GPS coordinates.

• export_gps_to_google_maps(self) -> str: Converts GPS information to a Google Maps URL.

• get_date(self, format: str = '%Y:%m:%d %H:%M:%S', default_time_zone: str = '+00:00') -> str: Returns the capture date (customizable date format).

• get_image_dimensions(self) -> str: Returns image dimensions.

• get_file_size(self) -> tuple[str, int]: Returns the file size.

• get_model_name(self) -> str: Returns the camera model name.

• get_lens_name(self) -> str: Returns the lens name.

• get_focal_length(self) -> dict: Returns focal length information.

• show(self) -> None: Displays the file.

• get_main_metadata(self) -> dict: Returns major metadata fields.

• contains_key(self, key, exact_match: bool = True): Checks whether the specified key exists.

• contains_value(self, value, exact_match: bool = True): Checks whether the specified value exists.

• copy(self) -> "Metadata": Copies the instance of the Metadata class.

• @classmethod def load_all_metadata(cls, file_path_list: list[str], progress_func: Callable[[int], None] | None = None, max_workers: int = 40) -> dict[str, "Metadata"]: Efficiently loads metadata from multiple files in parallel.

photo_metadata.MetadataBatchProcess

• __init__(self, file_list: list[str], progress_func: Callable[[int], None] | None = None, max_workers: int = 40): Constructor.
• filter_by_custom_condition(self, condition_func: Callable[[Metadata], bool]) -> None: Filters metadata using a custom condition function.
• filter_by_metadata(self, keyword_list: list[str], exact_match: bool, all_keys_match: bool, search_by: Literal["either", "value", "key"]) -> None: Finds files containing specific values, keys, or either in their metadata.
• prepare_rename(self, format_func: Callable[[Metadata], str]) -> None: Prepares files for renaming.
• rename_files(self) -> str: Renames the files.
• copy(self) -> "MetadataBatchProcess": Copies the instance of the MetadataBatchProcess class.

---

If you find this library useful, please consider giving it a ⭐ on GitHub!

---

URLs

• PyPI: https://pypi.org/project/photo-metadata/
• GitHub: https://github.com/kingyo1205/photo-metadata

---

Notes

ExifTool is required. This library uses ExifTool as an external command to process image and video metadata.

---

About AI-assisted Code Generation

Some parts of the code in this repository were generated or assisted by AI tools such as ChatGPT and Gemini CLI.

---

Required Software

ExifTool must be installed on your system. Download it from the official website.

---

License

This library is distributed under the MIT License.

However, this library utilizes ExifTool as an external tool, and ExifTool is distributed under a dual license (GPL 1.0 or later, or Artistic License 1.0).

If you use ExifTool, please make sure to comply with its license terms.

Dependencies and Licenses

(Verified in 2025 / Based on information listed on PyPI)

Library	License
charset_normalizer	MIT
tqdm	MIT

---