Create a dummy predict function

[leandroradusky]

In order to start with the skeleton of our package, let's create a dummy predict function that given a list of UniProt accessions (protein IDs) & a list of GO terms, returns a CAFA-formatted pandas dataframe of predictions fulfilled with random probabilities

We can define another name for it after, but for now, let's call our package manas-cafa5.

When the package is installed we should be able to run

import predict from manas-cafa5

proteins = ["Q88YH3", "Q89GE3", ...]
go_terms = ["GO:0016787", "GO:0005515", ...]

predictions = predict(proteins, go_terms)

And then when printing the predictions var we should see the dataframe as follows:

| uniprot_acc | go_term    | probability |
| Q88YH3      | GO:0016787 |       0.213 |
| Q88YH3      | GO:0016787 |       0.832 |
| Q89GE3      | GO:0005515 |       0.054 |
| Q89GE3      | GO:0005515 |       0.934 |
| ...         | ...        | ...         |

We will use the pandas package here because it is widely used in Python to handle tabular data, all the plotting libraries accept it as input, it is easily interconvertible with numpy arrays, etc.

Here the official tutorial about python packaging: https://packaging.python.org/en/latest/tutorials/packaging-projects/