amazon-photos 0.0.32

Amazon Photos API

Amazon Photos API

Table of Contents

• Installation
• Setup
• Query Syntax
• Examples

Installation

pip install amazon-photos

It is recommended to use this API in a Jupyter Notebook, as the results from most endpoints are a DataFrame which can be neatly displayed in a notebook, and efficiently manipulated with vectorized operations. This becomes increasingly important when dealing with large quantities of data.

Setup

There are two ways to set up authentication. The first is to pass the cookies explicitly to the AmazonPhotos constructor, the second is to add your cookies as environment variables.

Log in to Amazon Photos and copy the cookies:

• *ubid-acbxx
• *at-acbxx
• session-id

*Replace xx with your country code

Option 1: Cookies Dict

from amazon_photos import AmazonPhotos

ap = AmazonPhotos(
    cookies={
        "session-id": ...,
        "ubid-acbca": ...,
        "at-acbca": ...,
    },
    db_path="ap.parquet",  # initialize a simple database to store results
)

# sanity check, verify authenticated endpoint can be reached
ap.usage()

Option 2: Environment Variables

E.g. for amazon.ca (Canada), you would add to your ~/.bashrc:

export session_id="..."
export ubid_acbca="..."
export at_acbca="..."

Query Syntax

For valid location and people IDs, see the results from the aggregations() method.

Example query:

drive/v1/search

type:(PHOTOS OR VIDEOS)
AND things:(plant AND beach OR moon)
AND timeYear:(2019)
AND timeMonth:(7)
AND timeDay:(1)
AND location:(CAN#BC#Vancouver)
AND people:(CyChdySYdfj7DHsjdSHdy)

/drive/v1/nodes

kind:(FILE* OR FOLDER*)
AND contentProperties.contentType:(image* OR video*)
AND status:(AVAILABLE*)
AND settings.hidden:false
AND favorite:(true)

Examples

from amazon_photos import AmazonPhotos

## e.g. using cookies dict
ap = AmazonPhotos(cookies={
    "at-acbca": ...,
    "ubid-acbca": ...,
    "session-id": ...,
})

## e.g. using env variables and specifying tld. E.g. amazon.ca (Canada)
# ap = AmazonPhotos(tld="ca")

# get current usage stats
ap.usage()

# get entire Amazon Photos library. (default save to `ap.parquet`)
nodes = ap.query("type:(PHOTOS OR VIDEOS)")

# query Amazon Photos library with more filters applied. (default save to `ap.parquet`)
nodes = ap.query("type:(PHOTOS OR VIDEOS) AND things:(plant AND beach OR moon) AND timeYear:(2023) AND timeMonth:(8) AND timeDay:(14) AND location:(CAN#BC#Vancouver)")

# sample first 10 nodes
node_ids = nodes.id[:10]

# move a batch of images/videos to the trash bin
ap.trash(node_ids)

# get trash bin contents
ap.trashed()

# permanently delete a batch of images/videos.
ap.delete(node_ids)

# restore a batch of images/videos from the trash bin
ap.restore(node_ids)

# upload media (preserves local directory structure and copies to Amazon Photos root directory)
ap.upload('path/to/files')

# download a batch of images/videos
ap.download(node_ids)

# convenience method to get photos only
ap.photos()

# convenience method to get videos only
ap.videos()

# get all identifiers calculated by Amazon.
ap.aggregations(category="all")

# get specific identifiers calculated by Amazon.
ap.aggregations(category="location")

Common Paramters

name	type	description
ContentType	str	"JSON"
_	int	1690059771064
asset	str	"ALL" "MOBILE" "NONE "DESKTOP" default: "ALL"
filters	str	"type:(PHOTOS OR VIDEOS) AND things:(plant AND beach OR moon) AND timeYear:(2019) AND timeMonth:(7) AND location:(CAN#BC#Vancouver) AND people:(CyChdySYdfj7DHsjdSHdy)" default: "type:(PHOTOS OR VIDEOS)"
groupByForTime	str	"day" "month" "year"
limit	int	200
lowResThumbnail	str	"true" "false" default: "true"
resourceVersion	str	"V2"
searchContext	str	"customer" "all" "unknown" "family" "groups" default: "customer"
sort	str	"['contentProperties.contentDate DESC']" "['contentProperties.contentDate ASC']" "['createdDate DESC']" "['createdDate ASC']" "['name DESC']" "['name ASC']" default: "['contentProperties.contentDate DESC']"
tempLink	str	"false" "true" default: "false"

Notes

https://www.amazon.ca/drive/v1/batchLink

• This endpoint is called when downloading a batch of photos/videos in the web interface. It then returns a URL to download a zip file, then makes a request to that url to download the content. When making a request to download data for 1200 nodes (max batch size), it turns out to be much slower (~2.5 minutes) than asynchronously downloading 1200 photos/videos individually (~1 minute).