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Beit-Hatfusot Backend

Welcome to the API server of the museum of the jewish people. The code is in Python using Flask and MongoDB. The API docs are at http://api.dbs.bh.org.il/v1/docs

The server is built on top of 6 datasets the museum has collected in the last four decades. We have >72,000 Pictures and >1,100 movies. We have text articles about >6,000 communities >8,000 luminaries and >17,000 family names.

The last dataset is of family trees. People have contributed to the museum ~11,000 trees with ~5,000,000 individuals.

Installation

This server uses MongoDB so you'll have to have one up and running. Mongo installation is quite simple, just read the manual.

While a search engine is not a must, it is recommended to install Elasticsearch. Once you have MongoDB installed you can go on to install the python code:

Linux

$ sudo apt-get install libffi-dev libjpeg62 libjpeg62-dev zlib1g-dev libssl-dev
$ git clone [your_fork@github...]
$ cd dbs-back
$ virtualenv env
$ . env/bin/activate
$ pip install -r requirements.txt

Getting a DB

To play with the server you'll need some data in your db. Please download the tar ball from here and run

$ tzr xf bhdata.tgz
$ mongorestore -d bhdata dump/bhdata

To load the search engine with the dump you restores run:

$ python scripts/dump_mongo_to_es.py --db bhdata

Testing

$ py.test tests

Running a local server

A local server uses port 5000 and is activated by:

$ python scripts/runserver.py

Using the shell

If you want to play around with the flask shell you can start it using a special script and gain access to the app object.

$ python scripts/flask_shell.py

Getting a the frontend

The frontend that uses this API server lives here. To run the fronend so it will use your local server you just need to run, in separate window:

$ API_SERVER=local gulp serve

(the API_SERVER part tells the frontend to use a server at localhost:5000)

Migration

Part of the code in this repository deals with migrating the databases from the legacy MSSQL server. You don't haver to do it, as you get all the data you need from the dump above, but if you want to contribute to the migration you'll need access to MoJP local server on MoJP local network. The migration process is executed done using a celery based task queue and redis as a storage backend. To install the required packages run:

$ pip install -r requirements.migrate.txt

You'll also need to create some local system folders:

# mkdir /run/bhs
# mkdir /etc/bhs

And get the super secret migrate_config.yaml file into /etc/bhs. To activate the migration worker run:

$ celery -A migration.tasks worker --loglevel info

There are two enviornment variables for finer control over the worker:

  • MIGRATE_ES - set it to anything other than 1 to skip elastic search update
  • MIGRATE_MODE - set it to i to use mongo's insert command, otherwise update_one is used

Once the worker is listening, run in a separate window:

$ python scripts/migrate.py --lasthours 200

elasticsearch <-> mongo sync and management

Unofortunately we currently have 2 databases which need to be synced.

Generally, mongo is used for showing the item page, elasticsearch is used for searching

syncing from mongo to elasticsearch
  • ensure_required_metadata command can do that
    • it doesn't update all fields, only required ones like permissions / slug
    • you can add the optional --add parameter which will copy documents from mongo to elastic
  • how to run it
    • PYTHONPATH=. scripts/ensure_required_metadata.py --add
  • for development you can also add --legacy parameter which will copy from old mongo collections as well (don't use in production!)
(re)indexing elasticsearch
  • Create the new index with a unique name
    • you can name it however you want, in this example it's named with current date which is usually pretty good
    • scripts/elasticsearch_create_index.py --index bhdata-date +%Y-%m-%d``
  • copy the documents from the old index to the new index
    • simplest is to use reindex api - good enought for dev but it has some limitations
      • this command copies from bhdata to bhdata-(CURRENT_DATE)
      • curl -X POST localhost:9200/_reindex --data '{"source":{"index":"bhdata"},"dest":{"index":"bhdata-'date +%Y-%m-%d'"}}'
    • see devops elasticsearch documentation for more advanced methods
  • create (or modify) an alias that points to the new index
    • if this is your first time, delete the old bhdata index and create an alias
      • curl -X DELETE localhost:9200/bhdata
      • curl -X PUT localhost:9200/bhdata-date +%Y-%m-%d/_alias/bhdata
    • if you already have an alias
      • remove the old alias and add the new alias in a single operation
      • curl -X POST localhost:9200/_aliases --data '{"actions":[{"remove":{"index":"*","alias":"bhdata"}},{"add":{"index":"bhdata-'date +%Y-%m-%d'","alias":"bhdata"}}]}'
    • you can use this command to see which aliases are configured:
      • curl -X GET localhost:9200/_aliases?pretty

getting a copy of dev/prod db to run locally

  • creating the dump
    • only run if needed, there should already be some existing dumps for you to use
    • gcloud compute ssh mongo1
    • sudo mongodump --out=/data/dump-dev-date +%Y-%m-%d --gzip --db=mojp-dev
  • downloading the dump
    • gcloud compute copy-files mongo1:/data/dump-date +%Y-%m-%d ~/
  • restoring the dump on your local mongo
    • mongorestore --gzip --drop ~/dump-date +%Y-%m-%d``
  • point your settings to this new DB
    • if you haven't done so already - copy dbs-back/conf/app_server.yaml to /etc/bhs
      • sudo mkdir -p /etc/bhs && sudo chown -R $USER /etc/bhs
      • cp conf/app_server.yaml /etc/bhs/
    • edit /etc/bhs/app_server.yaml
      • set data_db_name to the new db name
      • make sure elasticsearch_data_index points to the correct ES index name
  • create mongo index
    • PYTHONPATH=. scripts/mongo_create_index.py
  • ensure elasticsearch has latest index (see above regarding (re)indexing elasticsearch)
  • sync mongo to elasticsearch
    • PYTHONPATH=. scripts/ensure_required_metadata.py --add

Contributing

Contributions from both Jews and Gentiles are welcomed! We even have a beginner label to help you start with (hopefully) simple issues. Once you have an issue, just follow these simple steps:

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Test your code
  4. Commit your changes: git commit -am 'Add some feature'
  5. Push to the branch: git push origin my-new-feature
  6. Submit a pull request :D

Updating the docs

If you've made any changes to the API please update the docs. The documentation lives in the /docs folder. We are using API Blueprint, a markdown based format, and aglio to render it to HTML. Once you've updated the docs you'll have to regenerate the html file::

$ cd docs
$ aglio -i index.apib -o index.html

and commit both files.