README.md

Migrating your Flickr photo library to Google Photos

This set of scripts can help you migrate your Flickr photo collection over to Google Photos. It uses the Flickr API and Google API to exchange information and mirror the structure of your Flickr albums on Google Photos. The scripts are written in Python and make use of the python-flickr-api library by @alexis-mignon. These scripts were built for python 3+.

Installation

Begin by cloning this repo to your local machine:

git clone https://github.com/llevar/flickr_to_google_photos_migration

At this point you might want to set up and activate a virtual environment to hold the installation dependencies without compromising your other installs.

Go to the cloned repo and install the required libraries:

pip install -r requirements.txt

You now want to create some necessary directories:

mkdir auth
mkir -p celery/out
mkdir -p celery/processed
mkdir -p celery/results 
mkdir -p photosets
mkdir -p photosets-complete
mkdir -p photosets-queue

Authentication and Authorization

You now want to authenticate with the Flickr API. It's best to follow this guide. You want to save the resulting authentication handler into auth/flickr_auth_handler. The script build_flickr_verifier.py has some helpful commands that, together with the guide above, should get you a working verifier.

You now want to set up your access to the Google Photos API. Google's page for the API has a number of useful guides that will help you get set up. You need to set up a project and user with oauth2 access to your Google Photos library, so that in the end you end up with a google_credentials.json file that looks like this:

{
  "installed": {
    "client_id": "your_id",
    "project_id": "your_project",
    "auth_uri": "https://accounts.google.com/o/oauth2/auth",
    "token_uri": "https://oauth2.googleapis.com/token",
    "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
    "client_secret": "your_secret",
    "redirect_uris": [
      "urn:ietf:wg:oauth:2.0:oob",
      "http://localhost"
    ]
  }
}

Place this file under auth/google_credentials.json

Now that Google authentication is complete, setup Google authorization by running the oauth.py script:

python oauth.py

An authorization server page will be opened in your default browser. Follow the prompts to grant the migration script access to your photos. When successful, an additional file, auth/google_token.json will be created.

Building a list of photos to migrate

Because one can have many thousands of photos in their library and errors may occur when communicating with either Flickr or Google Photos, we will carry out the migration process in several steps so that it can be restarted if it fails.

The first step is to build a file containing a list of URLs and titles of all your photos, as well as the album they belong to. These scripts currently assume that all of your photos are stored in albums. They walk through all of your albums and make a list of the photos in each album. If your photos are not in any albums they will not be captured by the scripts in their current form.

We will be running the script build_migration_photos_list.py to build our list of photos. This script relies on two environment variables FLICKR_API_KEY and FLICKR_API_SECRET. These should be set in your environment before running the script using the values you get when you activate your Flickr API app.

export FLICKR_API_KEY=my_key
export FLICKR_API_SECRET=my_secret
python build_migration_photos_list.py

This script walks through all the albums and builds a list of photos that we will later use to download these photos and upload them to Google. If available, tags on the photo in Flickr will be used as the description of the photo in Google, otherwise the title in Flickr is used as the description.

To make the process restartable, we'll use Redis to record the albums that have been retrieved from Flickr.
Fire up your own redis instance using docker:

docker run --name my-redis -p 6379:6379 --restart always --detach redis

For each album, a file named photosets-queue/photoset-${album-id}-${# of photos}.pickle will be created and an entry will be added to Redis to record that the album has been retrieved. If the script should fail, simply restart it. It will skip all of the albums that have previously been downloaded.

Creating album cache

To speed up the process of identifying albums in Google, a local cache of Google album titles will created.

python create_album_cache.py

This will find all of the existing albums in Google and create an entry in Redis.

Creating migration tasks

To manage the orderly download/upload of photos between providers, and allow one to stop and resume the process we will be using Celery, which is a python queue-based task manager. Celery supports many options, including different message brokers, parallelization of tasks via multiple workers and worker concurrency and so on. We will be using Celery in a very basic configuration. Celery will be configured to use the filesystem as both a results backend (can use a database instead, if desired) and a message broker (can use RabbitMQ, etc. instead, if desired). We will create a bunch of tasks and then spin up one celery worker to process them one after the other without any parallelization. If you wish to experiment with parallel execution it is easy enough to do, but I'm not sure what throttling rules Flickr and Google place on their APIs.

Move one or more of the pickle files in photosets-queue/ to photosets/

mv photosets-queue/*.pickle photosets/

and generate tasks by running:

python create_migration_tasks.py

This script will read the pickle files in photosets/*.pickle directory and create a separate Celery task for each photo. The tasks end up as files inside the celery/out folder. A task's job is to migrate a single photo from Flickr to Google Photos.

Running the migration

In order to start the actual processing of tasks you need to start celery. Do this with the following command from the root directory of the git repo:

celery -A celery_migration_app worker --loglevel=debug --concurrency=1 -E

This starts a single worker with a concurrency of 1, meaning that only one task will be processed at a time. Celery will grab task definitions from celery/out and process them. Processed tasks will end up in celerey/processed. The results will be stored in celery/results where you can look at their status. You can start and stop Celery as many times as you want and it will pick up from where it left off. You can get a quick summary of your successes and failures by running python check_migration_status.py. After a few hours your library should hopefully be migrated over to Google Photos.

N.B. Another current limitation of the Google Photos API is that all files are uploaded in their original size, even if you have selected the "High Quality" version of Google Photos that shouldn't count towards your Google Drive storage. That means that all of your photos will actually count towards your Google Drive capacity, and if you are not careful will run you out of your Google Drive space, which will cause subsequent uploads to fail. If you are on the free tier of Google Drive you can go to Google Photos Settings and choose 'Recover Storage' to force the conversion of all of your photos to their 'High Quality' size to reclaim the space back. The only catch is that you can only trigger this process once per day. So if you are hurting for space (or don't want to spend any money on a bigger storage allocation for a month) you can run migration for a while, until you start running out of space, stop celery, reclaim the space, then resume the migration on the next day, and so on...

N.B. #2 It looks like the Google Photos API currently has a 10000 request daily limit. You should keep an eye on this and stop the migration before you hit the quota as you will otherwise get task failures.

Enjoy!

P.S. This software has been tested on Mac OS and CentOS. It will probably work on other Linux flavors. Not sure how it will behave on Windows. There is currently very little error handling code. Your contributions are welcome.

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