Inquery/firebase_functions.py at main · fuzzyhappy/Inquery · GitHub

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from firebase_admin import firestore
import firebase_admin
from firebase_admin import credentials

#Initalizes service account if one does not already exist
try:
    cred = credentials.Certificate('/Users/shellyschwartz/PycharmProjects/boilerMake/BoilerMake8Build/boilermake-8-project-firebase-adminsdk-n45vg-c326d22181.json')
    firebase_admin.initialize_app(cred)
except ValueError:
    pass

db = firestore.client()
#profRef = db.collection(u'profdata')

## Old format, not currently used
# def formatData(firstName, lastName, dept, email, researchAreas, links):
#     out = {
#     u'first_name': u''+ firstName +'',
#     u'last_name': u''+ lastName +'',
#     u'department': u''+ dept +'',
#     u'email': u''+ email +'',
#     u'area of research': researchAreas,
#     u'external links': links
#     }
#     #print(out)
#     return out


## Accepted data
# Full Name
# Education(in the form of a list)
# Research areas(in the form of a list)
# External link to website (if they have one)
# Publications: [[title, link to publication], [title2, link2], [title3, None]]
# Bio (in the form of a string)
def uploadData(fullName, education, researchAreas, extLink, pubTitles, pubLinks, bio):
    currentRef = db.collection(u'profdata').document(u''+ fullName +'')

    #Converts 2D array of publications to dictionary
    # pubTitles = [None]*len(publications);
    # pubLinks = [None]*len(publications);
    # for i in range(len(publications)):
    #     pubTitles[i] = publications[i][0];
    #     pubLinks[i] = publications[i][1];
    # pubMap = dict(zip(pubTitles, pubLinks));
    #print(pubMap);

    info = {
    u'fullName': fullName,
    u'education': education,
    u'researchArea': researchAreas,
    u'externalLinks': extLink,
    u'pubTitles': pubTitles,
    u'pubLinks': pubLinks,
    u'bio': bio
    }
    #print(info);
    currentRef.set(info);

#Attempted query commands, often result in errors
# def dispByName(names):
#     results[i] = profRef.where(u'area of research', u'==', True).stream()

# def literalSearch(inputResearchArea):
#     results = profRef.where(u'area_of_research', u'array_contains', u''+ inputResearchArea +'').stream()
#     return results

## Misc test lines
#currentRef = db.collection(u'profdata').document(u'pete')
#currentRef.set(formatData("Purdue Pete", "Purdue University", ["Machine Learning", "Meme History"], "https://www.purdue.edu/"));

## Upload sample data
#uploadData("Tree Mann", ["Stanford University"], ["Computational Chemistry"], "https://en.wikipedia.org/wiki/Stanford_University", [["title1", "link1"], ["title2", "link2"], ["title3", "None"]], "Studies trees using computers...or something like that")
#uploadData("Purdue Pete", ["Purdue University"], ["Computational Chemistry", "Machine Learning", "Meme History"], "https://www.purdue.edu/", [["title1", "link1"], ["title2", "link2"], ["title3", "link3"]], "Studies Meme History")
#uploadData("Perdew Yeet", ["Purdue University"], ["Computational Chemistry"], "https://en.wikipedia.org/wiki/Purdue_University", [["title1", "link1"], ["title2", None], ["title3", "link3"]], "Purdue Pete's relative. Interest in Computational Chemistry")
#uploadData("Chuck Norris", ["Harvard University", "UC Berkeley"], ["Computational Chemistry", "Meme History", "Machine Learning"], "https://en.wikipedia.org/wiki/Chuck_Norris", [["title1", None], ["title2", None], ["title3", "link3"], ["title4", "link4"]], "Professor Norris' research focuses on machine learning")
#uploadData("Micheal Reeves", ["Cornell University", "UCLA"], ["Robotics", "Meme History", "Machine Learning", "Computational Chemistry"], "https://www.youtube.com/channel/UCtHaxi4GTYDpJgMSGy7AeSw", [["title1", "link1"], ["title2", None], ["title3", None], ["title4", None]], "Professor Reeves is interested in tasing people for views- I mean robotics")
#uploadData("Mark Zuckerberg", ["Harvard University"], ["Face Recognition", "Meme History", "Cybersecurity"], None, [["title1", "link1"], ["title2", "link2"], ["title3", None]], "Professor Zuckerberg leads research in facial recognition")


#print(f'{literalSearch("Meme History")} => {literalSearch("Meme History").to_dict}')
#doc = literalSearch("Meme History")
#print(f'Document data: {doc.to_dict()}')