Example #1
0
def addFile(path, properties, index):
    manageFiles.parameters['path'] = path
    inputList = manageFiles.read()
    idx = getProp(index, inputList)
    corpus = {}
    for property in properties:
        corpus[property] = getProp(property, inputList)
    return idx, corpus, len(inputList)
Example #2
0
import manageFiles

import processor
import score
import recommender

processor.parameters['index'] = "codigo"
processor.parameters['properties'] = ["desc","titulo","area_atuacao"]

processor.parameters['new_path'] = reachrAPI.getJobToRecommend()
processor.parameters['current_path'] = reachrAPI.getAllJobs()

print(processor.parameters['new_path'])
print(processor.parameters['current_path'])

score.parameters['properties'] =  ["desc","titulo","area_atuacao"]
score.parameters['weights'] = {"desc":0.3, "titulo":0.6, "area_atuacao":0.1}
score.parameters['input'] = processor.run()

recommender.parameters['threshold'] = 0.2
recommender.parameters['selection-step'] = 2
recommender.parameters['key'] = processor.parameters['index']
recommender.parameters['inner-list'] = 'processo_seletivo'
recommender.parameters['candidates-list'] = 'candidatos'

recommender.parameters['input-jobs'] = manageFiles.read(processor.parameters['current_path'])
recommender.parameters['input-similars'] = score.run()

ret = reachrAPI.postJobRecommendation(recommender.run())
print(ret)
Example #3
0
import setup
setup.load()

import manageFiles
import recommender

recommender.parameters['threshold'] = 0.2
recommender.parameters['selection-step'] = 3
recommender.parameters['key'] = 'codigo'
recommender.parameters['inner-list'] = 'processo_seletivo'
recommender.parameters['candidates-list'] = 'candidatos'

root = '/home/mnf/reachr/projects/RecommenderSystem/test'
manageFiles.parameters['path'] = root + '/support/vagas.json'
recommender.parameters['input-jobs'] = manageFiles.read()

manageFiles.parameters['path'] = root + '/support/similiars.json'
recommender.parameters['input-similars'] = manageFiles.read()

output = recommender.run()
print(output)

manageFiles.parameters['path'] = root + '/support/recommendation.json'
manageFiles.write(output)
import setup

setup.load()

import manageFiles

manageFiles.parameters['path'] = './support/vagas.json'
inputList = manageFiles.read()  # Le o arquivo

corpus = []
for doc in inputList:  # captura a descrição
    corpus.append(doc["desc"])

import preprocessor

preprocessor.parameters['corpus'] = corpus

X, Z = preprocessor.run()

print(X)
print(Z)

output_file = []
for i in range(0, X.shape[0]):
    output = {"titulo": "", "texto": "", "tokens": []}
    output["titulo"] = 'Código: {} - Título: {}'.format(
        inputList[i]["codigo"], inputList[i]["titulo"])
    output["texto"] = corpus[i]
    for j in range(0, X.shape[1]):
        if X[i, j] > 0:
            token = {"item": Z[j], "tfidf": X[i, j]}
Example #5
0
def getAllJobs():
    #response = requests.get(parameters['url'])
    #return response;
    obj = manageFiles.read(root + "/support/vagas.json")
    return manageFiles.write(obj)
Example #6
0
def getJobToRecommend():
    obj = manageFiles.read(root + "/support/new_vaga.json")
    return manageFiles.write(obj)
Example #7
0
import setup
setup.load()

import manageFiles
import score

root = '/home/mnf/reachr/projects/RecommenderSystem/test'
manageFiles.parameters['path'] = root + '/support/similiars.json'

score.parameters['properties'] = ["desc", "titulo", "area_atuacao"]
score.parameters['weights'] = {"desc": 0.5, "titulo": 0.4, "area_atuacao": 0.1}
score.parameters['input'] = manageFiles.read()

manageFiles.write(score.run())
import setup
setup.load()

import manageFiles

expected_ret = {}

# Teste Leitura
ret = manageFiles.read('./support/vagas.json')
print(ret)
assert (isinstance(ret, list)), 'Erro ao abrir arquivo JSON'

# Teste Gravação
ret = manageFiles.write(ret)
print(ret)
assert (ret != 1), 'Erro ao gravar arquivo JSON'