small script to fetch all canadian companies who issued LMIA

importer.py

mport rows
from collections import OrderedDict
from rows import fields, Table
import tqdm

files = [
    ("2017Q2-Q1","Descargas/2017Q2_Positive_Employer_EN.csv"),
    ("2017Q3","Descargas/2017Q3_Positive_Employer-EN.csv"),
    ("2017Q4","Descargas/2017Q4_Positive_Employer-EN.csv"),
    ("2018Q1","Descargas/2018Q1_Positive_Employer_EN.csv"),
    ("2018Q2","Descargas/2018Q2_Positive_Employer_EN.csv"),
    ("2018Q3","Descargas/2018Q3_Positive_Employer_en.csv"),
    ("2018Q4","Descargas/2018Q4_Positive_Employer_en.csv"),
]

outputs =[]

for ph, fi in tqdm.tqdm(files):
    output = rows.import_from_csv(fi)
    outputs.append((ph,output))

set_fields  = OrderedDict([
    ('year', fields.TextField),
    ("location", fields.TextField),
    ("company", fields.TextField),
    ("address", fields.TextField),
    ("noc", fields.TextField),
    ("count", fields.TextField),
])

out = Table(fields = set_fields)



for year,output in tqdm.tqdm(outputs):
    location, company, address  = None, None, None
    for row in tqdm.tqdm(output):
        location_field = row[0].strip()
        company_field = row.field_1.strip()
        address_field = row.field_2.strip()
        noc_field = row.field_3.strip()
        count_field = row.field_4.strip()
        if location_field:
            location = location_field
            address = address_field
        if company_field:
            company = company_field
        if noc_field.strip():
            out.append({
                'year':year,
                'location':location, 'company': company,
                'address':address, 'noc': noc_field,
                'count':count_field
                   })
    #print(location, company, address_field, noc_field, count_field)


rows.export_to_csv(out, "out.csv")