ImageKit.io Python SDK

Python SDK for ImageKit implements the new APIs and interface for different file operations.

ImageKit is complete media storage, optimization, and transformation solution that comes with an image and video CDN. It can be integrated with your existing infrastructure - storage like AWS S3, web servers, your CDN, and custom domain names, allowing you to deliver optimized images in minutes with minimal code changes.

Supported Python Versions: >=3.6

Table of contents -

Installation
Initialization
Change Log
Usage
Handling errors
Development
- Tests
- Sample
Support
Links

Installation

Go to your terminal and type the following command.

pip install imagekitio

Initialization

from imagekitio import ImageKit

imagekit = ImageKit(
    private_key='your_private_key',
    public_key='your_public_key',
    url_endpoint='your_url_endpoint'
)

Change log

This document presents a list of changes that break the existing functionality of previous versions. We try to minimize these disruptions, but they are sometimes unavoidable, especially in significant updates. Therefore, versions are marked semantically and tagged as major upgrades whenever such breaking changes occur.

Breaking History:

Changes from 2.2.8 -> 3.0.0 are listed below

Throw an Error:

What changed

Before the upgrade, an error dict was coming in the return object of any function call. Now, SDK throws an exception in case of an error.

Who is affected?

This affects any development in your software that calls APIs from ImageKit IO and handles errors based on what's returned.

How should I update my code?

To avoid failures in an application, you could handle errors as documented here

Usage

You can use this Python SDK for three different kinds of methods:

URL Generation
File Upload
File Management
Utility Functions

URL Generation

1. Using Image path and endpoint (hostname)

This method allows you to create a URL using the relative file path where the image exists and the URL endpoint(url_endpoint) you want to use to access the image. You can refer to the documentation here to read more about URL endpoints in ImageKit and the section about image origins to understand about paths with different kinds of origins.

The file can be an image, video, or any other static file supported by ImageKit.

imagekit_url = imagekit.url({
    "path": "/default-image.jpg",
    "url_endpoint": "https://ik.imagekit.io/your_imagekit_id/endpoint/",
    "transformation": [{
        "height": "300",
        "width": "400",
        "raw": "ar-4-3,q-40"
    }],
})

Sample Result URL -

https://ik.imagekit.io/your_imagekit_id/endpoint/tr:h-300,w-400,ar-4-3,q-40/default-image.jpg

2. Using full image URL

This method allows you to add transformation parameters to an absolute URL using the src parameter. This method should be used if you have the complete image URL stored in your database.

image_url = imagekit.url({
    "src": "https://ik.imagekit.io/your_imagekit_id/endpoint/default-image.jpg",
    "transformation": [{
        "height": "300",
        "width": "400",
        "raw": "ar-4-3,q-40"
    }]
})

Sample Result URL -

https://ik.imagekit.io/your_imagekit_id/endpoint/default-image.jpg?tr=h-300%2Cw-400%2Car-4-3%2Cq-40

The .url() method accepts the following parameters.

Option	Description
url_endpoint	Optional. The prepended base URL before the path of the image. If not specified, the URL Endpoint specified during SDK initialization gets used. For example, https://ik.imagekit.io/your_imagekit_id/endpoint/
path	Conditional. A path at which the image exists. For example, `/path/to/image.jpg`. Specify a `path` or `src` parameter for URL generation.
src	Conditional. Complete URL of an image already mapped to ImageKit. For example, `https://ik.imagekit.io/your_imagekit_id/endpoint/path/to/image.jpg`. Specify a `path` or `src` parameter for URL generation.
transformation	Optional. Specify an array of objects with name and the value in key-value pair to apply transformation params in the URL. Append different steps of a chained transformation as different objects of the array. This document includes a complete list of supported transformations in the SDK with some examples. If one uses an unspecified transformation name, it gets applied as it is in the URL.
transformation_position	Optional. The default value is `path`, which places the transformation string as a path parameter in the URL. One can also specify it as a query, which adds the transformation string as the query parameter `tr` in the URL. Suppose one uses the `src` parameter to create the URL. In that case, the transformation string is always a query parameter.
query_parameters	Optional. These are the other query parameters that one wants to add to the final URL. These can be any query parameters and are not necessarily related to ImageKit. Especially useful if one wants to add some versioning parameter to their URLs.
signed	Optional. Boolean. The default is `false`. If set to `true`, the SDK generates a signed image URL adding the image signature to the image URL. One can only use this if they create the URL with the `url_endpoint` and `path` parameters, not the `src` parameter.
expire_seconds	Optional. Integer. Used along with the `signed` parameter to specify the time in seconds from `now` when the URL should expire. If specified, the URL contains the expiry timestamp, and the image signature is modified accordingly.

Examples of generating URLs

1. Chained Transformations as a query parameter

image_url = imagekit.url({
    "path": "/default-image.jpg",
    "url_endpoint": "https://ik.imagekit.io/your_imagekit_id/endpoint/",
    "transformation": [
        {
            "height": "300",
            "width": "400"
        },
        {
            "rotation": 90
        }
    ],
    "transformation_position": "query"
})

Sample Result URL -

https://ik.imagekit.io/your_imagekit_id/endpoint/default-image.jpg?tr=h-300%2Cw-400%3Art-90

2. Sharpening, contrast transform and progressive JPG image

Add transformations like Sharpening to the URL with or without any other value. To use such transforms without specifying a value, set it as "-" in the transformation object. Otherwise, use the value that one wants to add to this transformation.

image_url = imagekit.url({
    "src": "https://ik.imagekit.io/your_imagekit_id/endpoint/default-image.jpg",
    "transformation": [{
        "format": "jpg",
        "progressive": "true",
        "effect_sharpen": "-",
        "effect_contrast": "1"
    }]
})

Sample Result URL -

# Note that because the `src` parameter is in effect, the transformation string gets added as a query parameter `tr`

https://ik.imagekit.io/your_imagekit_id/endpoint/default-image.jpg?tr=f-jpg%2Cpr-true%2Ce-sharpen%2Ce-contrast-1

3. Signed URL that expires in 300 seconds with the default URL endpoint and other query parameters

image_url = imagekit.url({
    "path": "/default-image.jpg",
    "query_parameters": {
        "p1": "123",
        "p2": "345"
    },
    "transformation": [{
        "height": "300",
        "width": "400"
    }],
    "signed": True,
    "expire_seconds": 300
})

Sample Result URL -

https://ik.imagekit.io/your_imagekit_id/tr:h-300,w-400/default-image.jpg?p1=123&p2=345&ik-t=1658899345&ik-s=8f03aca28432d4e87f697a48143efb4497bbed9e

List of transformations

The complete list of transformations supported and their usage in ImageKit is available here. The SDK gives a name to each transformation parameter, making the code simpler, more straightforward, and readable. If a transformation is supported in ImageKit, though it cannot be found in the table below, then use the transformation code from ImageKit docs as the name when using the URL function.

If you want to generate transformations in your application and add them to the URL as it is, use the raw parameter.

Supported Transformation Name	Translates to parameter
height	h
width	w
aspect_ratio	ar
quality	q
crop	c
crop_mode	cm
x	x
y	y
focus	fo
format	f
radius	r
background	bg
border	b
rotation	rt
blur	bl
named	n
overlay_x	ox
overlay_y	oy
overlay_focus	ofo
overlay_height	oh
overlay_width	ow
overlay_image	oi
overlay_image_trim	oit
overlay_image_aspect_ratio	oiar
overlay_image_background	oibg
overlay_image_border	oib
overlay_image_dpr	oidpr
overlay_image_quality	oiq
overlay_image_cropping	oic
overlay_image_focus	oifo
overlay_text	ot
overlay_text_font_size	ots
overlay_text_font_family	otf
overlay_text_color	otc
overlay_text_transparency	oa
overlay_alpha	oa
overlay_text_typography	ott
overlay_background	obg
overlay_text_encoded	ote
overlay_text_width	otw
overlay_text_background	otbg
overlay_text_padding	otp
overlay_text_inner_alignment	otia
overlay_radius	or
progressive	pr
lossless	lo
trim	t
metadata	md
color_profile	cp
default_image	di
dpr	dpr
effect_sharpen	e-sharpen
effect_usm	e-usm
effect_contrast	e-contrast
effect_gray	e-grayscale
original	orig
raw	replaced by the parameter value

File Upload

The SDK provides a simple interface using the .upload_file() method to upload files to the ImageKit Media library. It accepts all the parameters supported by the ImageKit Upload API.

The upload_file() method requires at least the file as (URL/Base64/Binary) and the file_name parameter to upload a file. The method returns a dict data in case of success, or it will throw a custom exception in case of failure. Use the options parameter to pass other parameters supported by the ImageKit Upload API. Use the same parameter name as specified in the upload API documentation.

Simple usage

from imagekitio.models.UploadFileRequestOptions import UploadFileRequestOptions

extensions = [
    {
        'name': 'remove-bg',
        'options': {
            'add_shadow': True,
            'bg_color': 'pink'
        }
    },
    {
        'name': 'google-auto-tagging',
        'minConfidence': 80,
        'maxTags': 10
    }
]

options = UploadFileRequestOptions(
    use_unique_file_name=False,
    tags=['abc', 'def'],
    folder='/testing-python-folder/',
    is_private_file=False,
    custom_coordinates='10,10,20,20',
    response_fields=['tags', 'custom_coordinates', 'is_private_file',
                     'embedded_metadata', 'custom_metadata'],
    extensions=extensions,
    webhook_url='https://webhook.site/c78d617f-33bc-40d9-9e61-608999721e2e',
    overwrite_file=True,
    overwrite_ai_tags=False,
    overwrite_tags=False,
    overwrite_custom_metadata=True,
    custom_metadata={'testss': 12},
)

result = imagekit.upload_file(file='<url|base_64|binary>', # required
                              file_name='my_file_name.jpg', # required
                              options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that uploaded file's ID
print(result.file_id)

If the upload succeeds, the result will be the UploadFileResult class.

If the upload fails, the custom exception will be thrown with:

response_help for any kind of help
response_metadata with raw, http_status_code and headers
message can be called to get the error message received from ImageKit's servers.

File Management

The SDK provides a simple interface for all the media APIs mentioned here to manage your files. This also returns result.

1. List & Search Files

Accepts an object specifying the parameters used to list and search files. All parameters specified in the documentation here can be passed with the correct values to get the results.

from imagekitio.models.ListAndSearchFileRequestOptions import ListAndSearchFileRequestOptions

options = ListAndSearchFileRequestOptions(
    type='file',
    sort='ASC_CREATED',
    path='/',
    search_query="created_at >= '2d' OR size < '2mb' OR format='png'",
    file_type='all',
    limit=5,
    skip=0,
    tags='Software, Developer, Engineer',
)

result = imagekit.list_files(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the first file's ID
print(result.list[0].file_id)

2. Get File Details

Accepts the file ID and fetches the details as per the API documentation here

file_id = "your_file_id"
result = imagekit.get_file_details(file_id=file_id)  # file_id required

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that file's id
print(result.file_id)

3. Get File Versions

Accepts the file ID and fetches the details as per the API documentation here

file_id = "your_file_id"
result = imagekit.get_file_versions(file_id=file_id)  # file_id required


# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that file's version id
print(result.list[0].version_info.id)

4. Get File Version details

Accepts the file_id and version_id and fetches the details as per the API documentation here

result = imagekit.get_file_version_details(
    file_id='file_id',
    version_id='version_id'
)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that file's id
print(result.file_id)

# print that file's version id
print(result.version_info.id)

5. Update File Details

Accepts all the parameters as per the API documentation here. The first argument to the update_file_details() method is the file ID, and a second argument is an object with the parameters to be updated.

from imagekitio.models.UpdateFileRequestOptions import UpdateFileRequestOptions

extensions = [
    {
        'name': 'remove-bg',
        'options': {
            'add_shadow': True,
            'bg_color': 'red'
        }
    },
    {
        'name': 'google-auto-tagging',
        'minConfidence': 80,
        'maxTags': 10
    }
]

options = UpdateFileRequestOptions(
    remove_ai_tags=['remove-ai-tag-1', 'remove-ai-tag-2'],
    webhook_url='url',
    extensions=extensions,
    tags=['tag-1', 'tag-2'],
    custom_coordinates='10,10,100,100',
    custom_metadata={'test': 11},
)

result = imagekit.update_file_details(file_id='62cfd39819ca454d82a07182'
        , options=options)  # required

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that file's id
print(result.file_id)

6. Add tags

Accepts a list of file_ids and tags as a parameter to be used to add tags. All parameters specified in the API documentation here can be passed to the .add_tags() functions to get the results.

result = imagekit.add_tags(file_ids=['file-id-1', 'file-id-2'], tags=['add-tag-1', 'add-tag-2'])

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# list successfully updated file ids
print(result.successfully_updated_file_ids)

# print the first file's id
print(result.successfully_updated_file_ids[0])

7. Remove tags

Accepts a list of file_ids and tags as a parameter to be used to remove tags. All parameters specified in the API documentation here can be passed to the .remove_tags() functions to get the results.

result = imagekit.remove_tags(file_ids=['file-id-1', 'file-id-2'], tags=['remove-tag-1', 'remove-tag-2'])

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# list successfully updated file ids
print(result.successfully_updated_file_ids)

# print the first file's id
print(result.successfully_updated_file_ids[0])

8. Remove AI tags

Accepts a list of file_ids and ai_tags as a parameter to remove AI tags. All parameters specified in the API documentation here can be passed to the .remove_ai_tags() functions to get the results.

result = imagekit.remove_ai_tags(file_ids=['file-id-1', 'file-id-2'], ai_tags=['remove-ai-tag-1', 'remove-ai-tag-2'])

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# list successfully updated file ids
print(result.successfully_updated_file_ids)

# print the first file's id
print(result.successfully_updated_file_ids[0])

9. Delete File

Delete a file according to the API documentation here. It accepts the file ID of the File that has to be deleted.

file_id = "file_id"
result = imagekit.delete_file(file_id=file_id)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

10. Delete FileVersion

Delete a file version as per the API documentation here. The method accepts the file_id and particular version id of the file that has to be deleted.

result = imagekit.delete_file_version(file_id="file_id", version_id="version_id")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

11. Bulk File Delete by IDs

Delete a file as per the API documentation here. The method accepts a list of file IDs that have to be deleted.

result = imagekit.bulk_file_delete(file_ids=["file_id1", "file_id2"])

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# list successfully deleted file ids
print(result.successfully_deleted_file_ids)

# print the first file's id
print(result.successfully_deleted_file_ids[0])

12. Copy file

Copy a file according to the API documentation here. The method accepts source_file_path, destination_path, and include_file_versions of the file that has to be copied.

from imagekitio.models.CopyFileRequestOptions import CopyFileRequestOptions

options = \
    CopyFileRequestOptions(source_file_path='/source_file_path.jpg',
                           destination_path='/destination_path',
                           include_file_versions=True)
result = imagekit.copy_file(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

13. Move File

Move a file as per the API documentation here. The method accepts source_file_path and destination_path of the file that has to be moved.

from imagekitio.models.MoveFileRequestOptions import MoveFileRequestOptions

options = \
    MoveFileRequestOptions(source_file_path='/source_file_path.jpg',
                           destination_path='/destination_path')
result = imagekit.move_file(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

14. Rename File

Rename a file per the API documentation here. The method accepts the file_path, new_file_name, and purge_cache boolean that has to be renamed.

from imagekitio.models.RenameFileRequestOptions import RenameFileRequestOptions

options = RenameFileRequestOptions(file_path='/file_path.jpg',
                                   new_file_name='new_file_name.jpg',
                                   purge_cache=True)
result = imagekit.rename_file(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the purge request id
print(result.purge_request_id)

15. Restore file Version

Restore a file as per the API documentation here. The method accepts the file_id and version_id of the file that has to be restored.

result = imagekit.restore_file_version(file_id="file_id", version_id="version_id")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print that file's id
print(result.file_id)

16. Create Folder

Create a folder per the API documentation here. The method accepts folder_name and parent_folder_path as options that must be created.

from imagekitio.models.CreateFolderRequestOptions import CreateFolderRequestOptions

options = CreateFolderRequestOptions(folder_name='test',
                                     parent_folder_path='/')
result = imagekit.create_folder(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

17. Delete Folder

Delete a folder as per the API documentation here. The method accepts folder_path as an option that must be deleted.

from imagekitio.models.DeleteFolderRequestOptions import DeleteFolderRequestOptions

options = DeleteFolderRequestOptions(folder_path='/test/demo')
result = imagekit.delete_folder(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

18. Copy Folder

Copy a folder as per the API documentation here. The method accepts the source_folder_path, destination_path, and include_file_versions boolean as options that have to be copied.

from imagekitio.models.CopyFolderRequestOptions import CopyFolderRequestOptions
options = \
    CopyFolderRequestOptions(source_folder_path='/source_folder_path',
                             destination_path='/destination/path',
                             include_file_versions=True)
result = imagekit.copy_folder(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the job's id
print(result.job_id)

19. Move Folder

Move a folder as per the API documentation here. The method accepts the source_folder_path and destination_path of a folder as options that must be moved.

from imagekitio.models.MoveFolderRequestOptions import MoveFolderRequestOptions
options = \
    MoveFolderRequestOptions(source_folder_path='/source_folder_path',
                             destination_path='/destination_path')
result = imagekit.move_folder(options=options)
# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the job's id
print(result.job_id)

20. Get Bulk Job Status

Accepts the job_id to get bulk job status as per the API documentation here. The method takes only jobId.

result = imagekit.get_bulk_job_status(job_id="job_id")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the job's id
print(result.job_id)

# print the status
print(result.status)

21. Purge Cache

Programmatically issue an explicit cache request as per the API documentation here. Accepts the full URL of the File for which the cache has to be cleared.

result = imagekit.purge_file_cache(file_url="full_url_of_file")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the purge file cache request id
print(result.request_id)

22. Purge Cache Status

Get the purge cache request status using the cache_request_id returned when a purge cache request gets submitted as per the API documentation here

result = imagekit.get_purge_file_cache_status(purge_cache_id="cache_request_id")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the purge file cache status
print(result.status)

23. Get File Metadata

Accepts the file_id and fetches the metadata as per the API documentation here

result = imagekit.get_file_metadata(file_id="file_id")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the file metadata fields
print(result.width)
print(result.exif.image.x_resolution)

24. Get File Metadata from remote URL

Accepts the remote_file_url and fetches the metadata as per the API documentation here

result = imagekit.get_remote_file_url_metadata(remote_file_url="remote_file_url")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the file metadata fields
print(result.width)
print(result.exif.image.x_resolution)

25. Create CustomMetaDataFields

Accepts an option specifying the parameters used to create custom metadata fields. All parameters specified in the API documentation here can be passed as it is with the correct values to get the results.

Check for the allowed values in the schema.

Example:

# Example for the type number

from imagekitio.models.CreateCustomMetadataFieldsRequestOptions import CreateCustomMetadataFieldsRequestOptions
from imagekitio.models.CustomMetadataFieldsSchema import CustomMetadataFieldsSchema
from imagekitio.models.CustomMetaDataTypeEnum import CustomMetaDataTypeEnum
schema = CustomMetadataFieldsSchema(type=CustomMetaDataTypeEnum.Number,
                                    min_value=100,
                                    max_value=200)
options = CreateCustomMetadataFieldsRequestOptions(name='test',
                                                   label='test',
                                                   schema=schema)
result = imagekit.create_custom_metadata_fields(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the id of created custom metadata fields
print(result.id)

# print the schema's type of created custom metadata fields
print(result.schema.type)

# MultiSelect type Example

from imagekitio.models.CreateCustomMetadataFieldsRequestOptions import CreateCustomMetadataFieldsRequestOptions
from imagekitio.models.CustomMetadataFieldsSchema import CustomMetadataFieldsSchema
from imagekitio.models.CustomMetaDataTypeEnum import CustomMetaDataTypeEnum

schema = \
    CustomMetadataFieldsSchema(type=CustomMetaDataTypeEnum.MultiSelect,
                               is_value_required=True,
                               default_value=['small', 30, True],
                               select_options=[
                                    'small',
                                    'medium',
                                    'large',
                                    30,
                                    40,
                                    True,
                                ])
options = \
    CreateCustomMetadataFieldsRequestOptions(name='test-MultiSelect',
        label='test-MultiSelect', schema=schema)
result = imagekit.create_custom_metadata_fields(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the name of created custom metadata fields
print(result.name)

# print the schema's select options of created custom metadata fields
print(result.schema.select_options)

# Date type Example

from imagekitio.models.CreateCustomMetadataFieldsRequestOptions import CreateCustomMetadataFieldsRequestOptions
from imagekitio.models.CustomMetadataFieldsSchema import CustomMetadataFieldsSchema
from imagekitio.models.CustomMetaDataTypeEnum import CustomMetaDataTypeEnum

schema = CustomMetadataFieldsSchema(type=CustomMetaDataTypeEnum.Date,
                                    min_value='2022-11-29T10:11:10+00:00',
                                    max_value='2022-11-30T10:11:10+00:00')
options = CreateCustomMetadataFieldsRequestOptions(name='test-date',
                                                   label='test-date',
                                                   schema=schema)
result = imagekit.create_custom_metadata_fields(options=options)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the label of created custom metadata fields
print(result.label)

# print the schema's min value of created custom metadata fields
print(result.schema.min_value)

26. Get CustomMetaDataFields

Accepts the include_deleted boolean as the initial parameter and fetches the metadata as per the API documentation here .

result = imagekit.get_custom_metadata_fields()  # in this case, it will consider includeDeleted as a False

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the first customMetadataField's id
print(result.list[0].id)

# print the first customMetadataField schema's type
print(result.list[0].schema.type)

result = imagekit.get_custom_metadata_fields(include_deleted=True)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the first customMetadataField's name
print(result.list[0].name)

# print the first customMetadataField schema's default value
print(result.list[0].schema.default_value)

27. Update CustomMetaDataFields

Accepts a field_id and options for specifying the parameters to be used to edit custom metadata fields as per the API documentation here .

from imagekitio.models.CustomMetadataFieldsSchema import CustomMetadataFieldsSchema
from imagekitio.models.UpdateCustomMetadataFieldsRequestOptions import UpdateCustomMetadataFieldsRequestOptions

schema = CustomMetadataFieldsSchema(min_value=100, max_value=200)
options = UpdateCustomMetadataFieldsRequestOptions(
    label='test-update',
    schema=schema
)
result = imagekit.update_custom_metadata_fields(
    field_id='id_of_custom_metadata_field',
    options=options
)

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

# print the label of updated custom metadata fields
print(result.label)

# print the schema's min value of updated custom metadata fields
print(result.schema.min_value)

28. Delete CustomMetaDataFields

Accepts the id to delete the custom metadata fields as per the API documentation here .

result = imagekit.delete_custom_metadata_field(field_id="id_of_custom_metadata_field")

# Final Result
print(result)

# Raw Response
print(result.response_metadata.raw)

Utility functions

We have included the following commonly used utility functions in this package.

Authentication parameter generation

Suppose one wants to implement client-side file upload. In that case, one will need a token, expiry timestamp, and a valid signature for that upload. The SDK provides a simple method that one can use in their code to generate these authentication parameters.

Note: Any client-side code should never expose The Private API Key. One must always generate these authentications parameters on the server-side

authentication

authentication_parameters = imagekit.get_authentication_parameters(token, expire)

Returns

{
    "token": "unique_token",
    "expire": "valid_expiry_timestamp",
    "signature": "generated_signature"
}

Both the token and expire parameters are optional. If not specified, the SDK uses the UUID to generate a random token and internally generates a valid expiry timestamp. The token and expire used to generate signature is part of a response returned by the server.

Distance calculation between two pHash values

Perceptual hashing allows you to construct a has value that uniquely identifies an input image based on the contents of an image. imagekit.io metadata API returns the pHash value of an image in the response. You can use this value to find a duplicate or similar image by calculating the distance between the two images.

This SDK exposes the phash_distance function to calculate the distance between two pHash values. It accepts two pHash hexadecimal strings and returns a numeric value indicative of the difference between the two images.

def calculate_distance():
    # fetch metadata of two uploaded image files
    ...
    # extract pHash strings from both: say 'first_hash' and 'second_hash'
    ...
    # calculate the distance between them:

    distance = imagekit.phash_distance(first_hash, second_hash)
    return distance

Distance calculation examples

imagekit.phash_distance('f06830ca9f1e3e90', 'f06830ca9f1e3e90')
# output: 0 (same image)

imagekit.phash_distance('2d5ad3936d2e015b', '2d6ed293db36a4fb')
# output: 17 (similar images)

imagekit.phash_distance('a4a65595ac94518b', '7838873e791f8400')
# output: 37 (dissimilar images)

HTTP response metadata of Internal API

HTTP response metadata of the internal API call can be accessed using the _response_metadata on the Result object. Example:

result = imagekit.upload_file(
    file="<url|base_64|binary>",
    file_name="my_file_name.jpg",
)

# Final Result
print(result)
print(result.response_metadata.raw)
print(result.response_metadata.http_status_code)
print(result.response_metadata.headers)

Sample Code Instruction

To run sample code go to the code samples here are hosted on GitHub - https://github.com/imagekit-samples/quickstart/tree/master/python and run.

python sample.py

Handling errors

Catch and respond to invalid data, internal problems, and more.

ImageKit Python SDK raises exceptions for many reasons, such as not found, invalid parameters, authentication, and internal server errors. Therefore, we recommend writing code that gracefully handles all possible API exceptions.

Example:

from imagekitio.exceptions.BadRequestException import BadRequestException
from imagekitio.exceptions.UnauthorizedException import UnauthorizedException
from imagekitio.exceptions.ForbiddenException import ForbiddenException
from imagekitio.exceptions.TooManyRequestsException import TooManyRequestsException
from imagekitio.exceptions.InternalServerException import InternalServerException
from imagekitio.exceptions.PartialSuccessException import PartialSuccessException
from imagekitio.exceptions.NotFoundException import NotFoundException
from imagekitio.exceptions.UnknownException import UnknownException

try:

    # Use ImageKit's SDK to make requests...
    print('Run image kit api')
except BadRequestException, e:
    # Missing or Invalid parameters were supplied to Imagekit.io's API
    print('Status is: ' + e.response_metadata.http_status_code)
    print('Message is: ' + e.message)
    print('Headers are: ' + e.response_metadata.headers)
    print('Raw body is: ' + e.response_metadata.raw)
except UnauthorizedException, e:
    print(e)
except ForbiddenException, e:
    # No valid API key was provided.
    print(e)
except TooManyRequestsException, e:
    # Can be for the following reasons:
    # ImageKit could not authenticate your account with the keys provided.
    # An expired key (public or private) was used with the request.
    # The account is disabled.
    # If you use the upload API, the total storage limit (or upload limit) is exceeded.
    print(e)
except InternalServerException, e:
    # Too many requests made to the API too quickly
    print(e)
except PartialSuccessException, e:
    # Something went wrong with ImageKit.io API.
    print(e)
except NotFoundException, e:
    # Error cases on partial success.
    print(e)
except UnknownException, e:
    # If any of the field or parameter is not found in the data
    print(e)

# Something else happened, which can be unrelated to ImageKit; the reason will be indicated in the message field

Development

Tests

Tests are powered by Tox.

$ git clone https://github.com/imagekit-developer/imagekit-python && cd imagekit-python
$ pip install tox
$ tox

Sample

Get & Install local ImageKit Python SDK

$ git clone https://github.com/imagekit-developer/imagekit-python && cd imagekit-python
$ pip install -e .

Get samples

To integrate ImageKit Samples in the Python, the code samples covered here are hosted on GitHub - https://github.com/imagekit-samples/quickstart/tree/master/python.

Open the python/sample.py file and replace placeholder credentials with actual values. You can get the value of URL-endpoint from your ImageKit dashboard. API keys can be obtained from the developer section in your ImageKit dashboard.

In the python/sample.py file, set the following parameters for authentication:

from imagekitio import ImageKit
imagekit = ImageKit(
    private_key='your private_key',
    public_key='your public_key',
    url_endpoint = 'your url_endpoint'
)

To install dependencies that are in the python/requirements.txt file, can fire this command to install them:

pip install -r python/requirements.txt

Now run python/sample.py. If you are using CLI Tool (Terminal/Command prompt), open the project in CLI and execute it.

# if not installed already
pip install imagekitio

# if installing local sdk
pip install -e <path_to_local_sdk>

# to run sample.py file
python3 python/sample.py

Support

For any feedback or to report any issues or general implementation support, please reach out to [email protected]

Links

License

Released under the MIT license.

Name		Name	Last commit message	Last commit date
Latest commit History 227 Commits
.github/workflows		.github/workflows
imagekitio		imagekitio
requirements		requirements
tests		tests
.coveragerc		.coveragerc
.editorconfig		.editorconfig
.gitignore		.gitignore
DEVELOPMENT.md		DEVELOPMENT.md
LICENSE		LICENSE
README.md		README.md
setup.py		setup.py
tox.ini		tox.ini

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