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Recommender Metrics Framework

A framework for generating statistics, metrics, KPIs, and graphs for Recommender Systems

Preprocessor

RS metrics

Dependencies

  1. Install Conda from here. Tested on conda v 4.10.3.
  2. Run from terminal: conda env create -f environment.yml
  3. Run from terminal: conda activate rsmetrics
  4. Run from terminal: chmod +x ./preprocessor.py ./preprocessor_common.py ./rsmetrics.py

Usage

Usage of the Batch System

  1. Configure ./preprocessor_common.py, ./preprocessor.py and ./rsmetrics.py by editting the config.yaml or providing another with -c.
  2. Run from terminal: ./preprocessor_common.py in order to gather users and resources and store them in the Datastore:
./preprocessor_common.py # this will ingest users and resources [from scratch] by retrieving the data from 'marketplace_rs' provider (which is specified in the config file
./preprocessor_common.py -p marketplace_rs # equivalent to first one
./preprocessor_common.py -p marketplace_rs --use-cache # equivalent to first one but use the cache file to read resources instead of downloading them via the EOSC Marketplace
./preprocessor_common.py -p athena # currently is not working since users collection only exist in 'marketplace_rs'
  1. Run from terminal: ./preprocessor.py -p <provider> in order to gather user_actions and recommendations from the particular provider and store them in the Datastore:
./preprocessor.py # this will ingest user_actions and recommendations [from scratch] by retrieving the data from 'marketplace_rs' provider (which is specified in the config file
./preprocessor.py -p marketplace_rs # equivalent to first one
./preprocessor.py -p athena # same procedure as the first one but for 'athena' provider
  1. Run from terminal: ./rsmetrics.py -p <provider> in order to gather the respective data (users, resources, user_actions and recommendations), calculate statistics and metrics and store them in the Datastore, concerning that particular provider:
./rsmetrics.py # this will calculate and store statistics and metrics concerning data (users, resources, user_actions and recommendations) concerning the specified provider (which by default is 'marketplace_rs')
./rsmetrics.py -p marketplace_rs # equivalent to first one
./rsmetrics.py -p athena # same procedure as the first one for 'athena' provider
  1. A typical rsmetrics.py command for a monthly report, would be:
./rsmetrics.py -p provider -s $(date +"%Y-%m-01") -e $(date +"%Y-%m-%d") -t "$(date +"%B %Y")"

Usage of the Streaming System

  1. Run from terminal ./rs-stream.py in order to listen to the stream for new data, process them, and store them in the Datastore, concerning that particular provider:
./rs-stream.py -a username:password -q host:port -t user_actions -d ""mongodb://localhost:27017/datastore"" -p provider_name

Reporting

The reporting script generates an evalutation report in html format automatically served from a spawed localserver default: localhost:8080 and automatically opens the default browser to present the report.

To execute the script issue:

chmod u+X ./report.py
report.py

The script will automatically look for evaulation result files in the default folder ./data and will output the report in the default folder: ./report

Additional script usage with parameters

The report.py script can be used with the --input parameter: a path to a folder that the results from the evaluation process have been generated (default folder:./data). The report script can also take an --output parameter: a path to an output folder where the generated report will be served automatically.

Note: the script copies to the output folder all the necessary files such as pre_metrics.json, metrics.json as well as report.html.prototype renamed to index.html

usage: report.py [-h] [-i STRING] [-o STRING] [-a STRING] [-p STRING]

Generate report

optional arguments:
  -h, --help            show this help message and exit
  -i STRING, --input STRING
                        Input folder
  -o STRING, --output STRING
                        Output report folder
  -a STRING, --address STRING
                        Address to bind and serve the report
  -p STRING, --port STRING
                        Port to bind and serve the report

Utilities

Get item catalog script (./get_catalog.py)

This script contacts EOSC Marketplace remote service api and generates a csv with a list of all available items of a specific catalog (e.g. services, datasets, trainings, publications, data_sources, ), their name, id and url

To execute the script issue:

chmod u+x ./get_catalog.py
./get_catalog.py -u https://remote.example.foo -c service -b 100 -l 2000 -o `my-catalog.csv`

Arguments:

  • -u or -url: the endpoint url of the marketplace search service
  • -o or --output: this is the output csv file (e.g. ./service_catalog.csv or ./training_catalog.csv) - optional
  • -b or --batch: because search service returns results with pagination this configures the batch for each retrieval (number of items per request) - optional
  • -l or --limit: (optional) the user can specify a limit of max items to be retrieves (this is handy for large catalogs if you want to receive a subset) - optional
  • -c or --category: the category of list of items you want to retrieve
  • -d or --datastore: mongodb destination database uri to store the results into (e.g. mongodb://localhost:27017/rsmetrics) - optional
  • -p or --providers: state in a comma-separated list wich providers (engines) handle the items of the specific category currently supported category types for marketplace:
  • service
  • training
  • dataset (this is for items of the DATA catalog)
  • data_source (this is for items of the DATASOURCES catalog)
  • publication
  • guideline (this is for items of the INTEROPERABILITY GUIDELINES catalog)
  • software
  • bundle
  • other
Serve Evaluation Reports as a Service

The webservice folder hosts a simple webservice implemented in Flask framework which can be used to host the report results.

Note: Please make sure you work in a virtual environment and you have already downloaded the required dependencies by issuing pip install -r requirements.txt

The webservice application serves two endpoints

  • / : This is the frontend webpage that displays the Report Results in a UI
  • /api : This api call returns the evaluation metrics in json format

To run the webservice issue:

cd ./webservice
flask run

The webservice by default runs in localhost:5000 you can override this by issuing for example:

flask run -h 127.0.0.1 -p 8080

There is an env variable RS_EVAL_METRIC_SOURCE which directs the webservice to the generated metrics.json file produced after the evaluation process. This by default honors this repo's folder structure and directs to the root /data/metrics.json path

You can override this by editing the .env file inside the /webservice folder, or specificy the RS_EVAL_METRIC_SOURCE variable accordingly before executing the flask run command

Tested with python 3.9

Monitor for entries in the MongoDB collections

A typical example that counts the documents found in user_actions, recommendations, and resources for 1 day ago would be:

./monitor.py -d "mongodb://localhost:27017/rsmetrics" -s "$(date -u -d '1 day ago' '+%Y-%m-%d')" -e "$(date -u '+%Y-%m-%d')"

E-mail send over SMTP for the above example:

./monitor.py -d "mongodb://localhost:27017/rsmetrics" -s "$(date -u -d '1 day ago' '+%Y-%m-%d')" -e "$(date -u '+%Y-%m-%d')" --email "smtp://server:port" sender@domain recipient1@domain recipient2@domain

Export Capacity information for entries in the MongoDB collections

A typical example that counts the documents found in user_actions, recommendations, and resources for 1 year ago would be:

./monitor.py -d "mongodb://localhost:27017/rsmetrics" -s "$(date -u -d '1 day ago' '+%Y-%m-%d')" -e "$(date -u '+%Y-%m-%d')" --capacity

which will return results in CSV format of year,month,user_actions,recommendations

Additionally, capacity can be plotted:

./monitor.py -d "mongodb://localhost:27017/rsmetrics" -s "$(date -u -d '1 day ago' '+%Y-%m-%d')" -e "$(date -u '+%Y-%m-%d')" --capacity --plot

Deployment docs

Installation and configuration documents can be found here.