def parse_adjustments(adjustments_path):
dicts = parse_csv(adjustments_path)
return [
AdjustmentRecord(
day=str_to_date(d['day']),
delta=str_to_timedelta(d['delta']),
)
for d in dicts
]
def _preprocess_path_contexts(self, result_path):
result = {}
for file in ["node_types", "paths", "tokens"]:
file_path = result_path / "{}.csv".format(file)
if not os.path.exists(file_path):
raise Exception(
"File {} was not created by astminer.".format(file_path))
result[file] = parse_csv(str(file_path), delimiter=",")
path_contexts = parse_line_csv(result_path / "path_contexts.csv",
delimiter=" ")
file_paths = {}
for index, paths in path_contexts:
all_paths = []
for path in paths:
path = path.split(",")
if len(path) != 3:
logging.critical("No valid paths for {} !".format(index))
break
all_paths.append({
"start": path[0],
"path_index": path[1],
"end": path[2]
})
index = index.split(os.path.sep)[-1][:-4]
file_paths[index] = all_paths
result["file_paths"] = file_paths
def _create_index_map(data, field_name):
field2index = "{}2index".format(field_name)
index2field = "index2{}".format(field_name)
result[field2index] = {}
result[index2field] = {}
for match in data:
idx = match["id"]
field = match[field_name]
result[field2index][field] = idx
result[index2field][idx] = field
_create_index_map(result["node_types"], "node_type")
_create_index_map(result["tokens"], "token")
_create_index_map(result["paths"], "path")
return result
def parse_month(month_path, year):
month = int(os.path.basename(month_path).split('.')[0])
dicts = parse_csv(month_path)
return MonthRecord(
year=year,
month=month,
records=[
_day_dict_from_csv_to_day_record(d=d, year=year, month=month)
for d in dicts
]
)
def main():
arguments = docopt(__doc__)
db_path = arguments['<db_path>']
csv_path = arguments['<csv_path>']
dicts = parse_csv(csv_path)
day_records_from_csv = (dict_to_day_record(d) for d in dicts)
day_records_from_csv = [r for r in day_records_from_csv if r]
for day_record_from_csv in day_records_from_csv:
inserted = write_day_record(db_path, day_record_from_csv)
if inserted:
print 'Inserted {}'.format(day_record_from_csv)
else:
print 'Discarded: {}'.format(day_record_from_csv)
random_number_of_days = random.randrange(days_between_dates)
random_date = start_date + datetime.timedelta(days=random_number_of_days)
return random_date
# DATABASE SCHEMA
# items(name, brand, type, RFID, price) IMPLEMENTED
# stock(itemRFID, amt, expirationDate, location) _
# employees(lastName, firstName, ID, role) IMPLEMENTED
# hours(employeeID, day, checkIn, checkOut, dayHours) _
# tasks(taskName, description, taskID, state, employeeID, timeCreated, timeCompleted) implemented
# sales(transactionID, time, totalPaid) _
# transactions(transactionID, time, item, amt) _
# logins(username, password, accountType) IMPLEMENTED
items = util.parse_csv("items.csv", 0)
# util.print_nested_list(items)
employees = util.parse_csv("employees.csv", 0)
# util.print_nested_list(employees)
# CREATING THE STOCK CSV
stock = [["itemRFID", "amt", "expirationDate", "location"]]
stock_item_no = util.parse_csv("random_items_numbers.csv", 0)
# util.print_nested_list(stock_item_no)
sin_len = len(stock_item_no[0])-1
sin_half_len = sin_len/2
for i in range(0, sin_len):
insert = []
## Written by: Kimberly Chang
## Tested by: Kimberly Chang
## Debugged by: Kimberly Chang
import random
import datetime
import util
items = util.parse_csv("items.csv", 0)
# util.print_nested_list(items)
customerIDs = ["katie587", "coolcat53", "lakes", "laura", "LeaAnderson", "jjohnson", "flyingpigs43", "ilovecats", "amy67", "roger23"]
shopping_list = [["username", "item"]]
for customer in customerIDs:
no = random.randint(1, 30)
insert = []
for j in range(0, no):
insert.append(customer)
i = random.randint(1, 10000)
# items(name, brand, type, RFID, price)
insert.append(items[i][3])
shopping_list.append(insert)
insert = []
util.print_nested_list(shopping_list)