def load_courts_from_file(self,
json_path,
data_path='docassemble.MACourts:data/sources/'):
"""Add the list of courts at the specified JSON file into the current list"""
path = path_and_mimetype(os.path.join(data_path,
json_path + '.json'))[0]
with open(path) as courts_json:
courts = json.load(courts_json)
for item in courts:
# translate the dictionary data into an MACourtList
court = self.appendObject()
court.name = item['name']
court.phone = item['phone']
court.fax = item['fax']
court.location.latitude = item['location']['latitude']
court.location.longitude = item['location']['longitude']
court.has_po_box = item.get('has_po_box')
court.description = item.get('description')
court.address.address = item['address']['address']
court.address.city = item['address']['city']
court.address.state = item['address']['state']
court.address.zip = item['address']['zip']
court.address.county = item['address']['county']
court.address.orig_address = item['address'].get('orig_address')
def load_boston_wards_from_file(
self, json_path, data_path='docassemble.MACourts:data/sources/'):
"""load geojson file for boston wards"""
path = path_and_mimetype(
os.path.join(data_path, json_path + '.geojson'))[0]
wards = gpd.read_file(path)
return wards
def load_courts_from_file(json_path):
new_courts = []
(path, mimetype) = path_and_mimetype(json_path)
with open(path) as courts_json:
courts = json.load(courts_json)
for item in courts:
# translate the JSON data into a DA Address types
address = Address()
address.address = item['address']['address']
address.city = item['address']['city']
address.state = item['address']['state']
address.zip = item['address']['zip']
address.county = item['address']['county']
court = MACourt()
court.name = item['name']
court.phone = item['phone']
court.fax = item['fax']
court.address = address
court.lat = item['lat']
court.lng = item['lng']
new_courts.append(court)
return new_courts
def load_program_data():
(path, mimetype
) = path_and_mimetype('docassemble.lscrefer:data/sources/Programs.json')
with open(path, 'rU', encoding='utf-8') as fp:
program_list = json.load(fp)
lsc_programs.clear()
for program_dict in program_list:
program = dict()
lsc_programs[program_dict["Serv_Area_ID"]] = program
program['name'] = program_dict["R_Legalname"].strip()
program['phone_number'] = program_dict["Local_800"].strip()
program['url'] = program_dict["Web_URL"].strip()
lsc_programs_by_rin.clear()
lsc_programs_by_serv_a.clear()
area_data = service_areas()
if 'features' not in area_data:
sys.stderr.write("area data is empty\n")
else:
for item in area_data['features']:
attribs = item['attributes']
if attribs['ServArea'] == 'MA-4':
attribs['ServArea'] = 'MA04'
attribs['ServArea_1'] = 'MA-4'
attribs['servA'] = 'MA04'
service_area = attribs['ServArea_1'].strip()
if service_area in lsc_programs:
lsc_programs_by_rin[
attribs['RIN']] = lsc_programs[service_area]
lsc_programs_by_serv_a[
attribs['servA']] = lsc_programs[service_area]
lsc_programs[service_area]['rin'] = attribs['RIN']
lsc_programs[service_area]['serv_a'] = attribs['servA']
else:
sys.stderr.write("Could not find {} in program info.\n".format(
service_area))
def load_from_csv(relative_path):
""" Return a list containing a dictionary for each line of the CSV file at relative_path. Uses Docassemble path_and_mimetype to locate the path."""
(path, mimetype) = path_and_mimetype(relative_path)
reader = csv.DictReader(open(path, 'r'))
myList = []
for line in reader:
myList.append(line)
del reader
return myList
def _load_data(self)->pd.DataFrame:
"""
Return dataframe of the whole file's contents.
"""
if "/" in self.filename:
to_load = path_and_mimetype(self.filename)[0]
else:
to_load = path_and_mimetype(os.path.join("data/sources", self.filename))[0]
if self.filename.lower().endswith('.xlsx'):
df = pd.read_excel(to_load)
elif self.filename.lower().endswith('.csv'):
df = pd.read_csv(to_load)
elif self.filename.lower().endswith('.json'):
# TODO: we may need to normalize a JSON file
df = pd.read_json(to_load)
else:
raise Exception('The datafile must be a CSV, XLSX, or JSON file. Unknown file type: ' + to_load)
return df
def read_data(filename):
the_xlsx_file, mimetype = path_and_mimetype(filename)
df = pandas.read_excel(the_xlsx_file)
for indexno in df.index:
if not df['Name'][indexno]:
continue
fruit_names.append(df['Name'][indexno])
fruit_info_by_name[df['Name'][indexno]] = {
"color": df['Color'][indexno],
"seeds": df['Seeds'][indexno]
}
def load_courts_from_file(self,
court_name,
data_path='docassemble.MACourts:data/sources/'):
"""Add the list of courts at the specified JSON file into the current list"""
json_path = court_name
# 'housing_courts','bmc','district_courts','superior_courts'
if court_name == 'housing_courts':
court_department = 'Housing Court'
elif court_name == 'bmc':
court_department = 'Boston Municipal Court'
elif court_name == 'district_courts':
court_department = 'District Court'
elif court_name == 'superior_courts':
court_department = 'Superior Court'
elif court_name == 'juvenile_courts':
court_department = 'Juvenile Court'
elif court_name in ['land_courts', 'land_court']:
court_department = 'Land Court'
elif court_name == 'probate_and_family_courts':
court_department = 'Probate and Family Court'
path = path_and_mimetype(os.path.join(data_path,
json_path + '.json'))[0]
with open(path) as courts_json:
courts = json.load(courts_json)
for item in courts:
# translate the dictionary data into an MACourtList
court = self.appendObject()
court.name = item['name']
court.department = court_department
court.division = parse_division_from_name(item['name'])
court.phone = item['phone']
court.fax = item['fax']
court.location.latitude = item['location']['latitude']
court.location.longitude = item['location']['longitude']
court.has_po_box = item.get('has_po_box')
court.description = item.get('description')
court.address.address = item['address']['address']
court.address.city = item['address']['city']
court.address.state = item['address']['state']
court.address.zip = item['address']['zip']
court.address.county = item['address']['county']
court.address.orig_address = item['address'].get('orig_address')
import csv
import re
import json
import requests
import io
import docx
import textract
import tempfile
from docassemble.base.util import path_and_mimetype, ocr_file, DAObject, DAFile
(filename, mimetype) = path_and_mimetype('data/static/obce.json')
def najitObec(obec, kraj):
with open(filename, encoding='utf-8') as d:
data = json.load(d)
for polozka in data["municipalities"]:
if obec.lower() == polozka["hezkyNazev"].lower() and re.sub(
'(k|K)raj', '', kraj).strip().lower() == re.sub(
'(k|K)raj', '',
polozka["adresaUradu"]["kraj"]).strip().lower():
return (polozka)
return (False)
def vyhlaskyObce(idds):
with requests.Session() as s:
r = s.get(
'https://sbirkapp.gov.cz/vyhledavani/vysledek?typ=ozv&ovm=' +
idds +
'&kod_vusc=&ucinnost_od=&ucinnost_do=&oblast=&zmocneni=&nazev=&znacka=&format_exportu=csv'
import csv
from docassemble.base.util import path_and_mimetype
(filename, mimetype) = path_and_mimetype('data/static/obyvatele_full.csv')
__all__ = ['pocetObyvatel']
def pocetObyvatel(obec):
vysledek = []
with open(filename, newline='', encoding='utf-8') as csvfile:
reader = csv.reader(csvfile, delimiter=';')
for row in reader:
if row[1] == obec:
vysledek.append(row)
return (vysledek)
def test_path(self):
(path, mimetype) = path_and_mimetype('lithuania.svg')
self.assertTrue(
path.endswith(
'site-packages/docassemble/demo/data/static/lithuania.svg'))
self.assertEqual(mimetype, 'image/svg+xml')
def __load_yaml(self, yaml_file_name, default=[]):
path = path_and_mimetype(self.path + yaml_file_name)[0]
#try:
with open(path, encoding="utf-8") as file:
results = yaml.safe_load(file)
return results or default
