![https://readthedocs.org/projects/iati-partner-search/badge/?version=latest]

A tool using NLP technology to match aid funders with potential implementers.

A more detailed break-down of the project can be found here.

To install the python packages, make sure that you have your virtual environment activated and run the following:

pip install invoke
invoke install-all

This will install all of the development and testing packages as well

To run tests:

invoke test

To run linting, formatting and tests:

invoke ci

This repo provides a Dockerfile (app.Dockerfile), that you can build on your machine, which should provide an environment in which the code can execute.

We do not currently publish our images to DockerHub. You must build them on your machine. Make sure that the Docker VM is running, then run:

docker build -t iati_partner_search -f ./app.Dockerfile .

Or if you have invoke installed, run invoke build-dev-docker which will run this command on your behalf.

The -t iati_partner_search means that we're telling Docker that we want the image to be called iati_partner_search. The -f ./app.Dockerfile tells Docker which Dockerfile to use.

Once the image has been built, we can run a container:

docker run --name=ips -it -v ${pwd}:/iati-partner-search -p 5000:5000 iati_partner_search bash

to break this down:

• --name=ips: tells what we will call this container when we want to start and stop it again.
• -it:
• -v ${pwd}:/iati-partner-search: tells Docker to share the files on your machine, with the Docker container.
• -p 5000:5000: tells Docker that we want to map port 5000 on our machine to port 5000 of the container
• iati_partner_search: refers to the image that we want to build the container from.
• bash: is the process that want the container to run. In this case we're asking it to start the CLI. If instead we want to start the web application, do not include this, and it will be started automatically.

You can then stop and start the container by running docker stop ips and docker start ips respectively.

You can read more about Docker containers and this process here.

Currently (and temporarily) we copy in the data manually. Copy the file named all_downloaded_records.csv in to the /data/ directory.

If you're not working from within the Docker container, you will also need to download the nltk data. Execute the following:

invoke download-nltk-data

After adding the required data and installing the required packages you will be able to run the web application on your own computer.

In the /data directory make sure you have

- all_downloaded_records.csv
- processed_records.csv
- term_document_matrix.pkl
- vectorizer.pkl

Then, using invoke, run

invoke build-docker

to build the docker and then

invoke run-docker

to run it.

After a few seconds of start up time it should be up and running. Navigate to localhost:5000 in your web browser to view the page.