import.py

#!/usr/bin/env python
import dateparser
from training.models import Training

headers = (
    "received",
    "email",
    "title",
    "description",
    "start",
    "end",
    "location",
    "use_gtn",
    "attendance",
    "advertise",
    "blogpost",
    "website",
    "gtn_links",
    "training_identifier",
    "name",
    "non_gtn_links",
    "other_requests",
    "processed",
)

x = open("data.tsv", "r").read().strip().split("\n")
for idx, line in enumerate(x):
    if idx == 0:
        continue

    line = line.split("\t")
    line = line[0 : len(headers)]
    d = dict(zip(headers, line))
    # del  d['days_until']
    # del  d['gdpr']
    # del  d['days_since']
    del d["blogpost"]

    d["received"] = dateparser.parse(d["received"]).date()
    d["start"] = dateparser.parse(d["start"]).date()
    d["end"] = dateparser.parse(d["end"]).date()

    if d["processed"].lower().startswith("y"):
        d["processed"] = "AP"
    else:
        d["processed"] = "UN"

    if d["advertise"].lower().startswith("y"):
        d["advertise"] = "Y"
    else:
        d["advertise"] = "N"

    if d["use_gtn"].lower().startswith("y"):
        d["use_gtn"] = "Y"
    else:
        d["use_gtn"] = "N"

    d["training_identifier"] = d["training_identifier"][0:20]

    d["location"] = [x.strip().split(" ")[0] for x in d["location"].split(",")]

    __import__("pprint").pprint(d)
    t = Training(**d)
    t.save()