def run(self):
index_name = (self.source_definition.get('frontend_index')
or self.source_definition['index_name'])
api_args = self.source_definition['frontend_args']
# TODO: this stuff is hacky but no real idea to fix it in a good way
try:
from_date = iso8601.parse_date(api_args['date']['from'])
except iso8601.ParseError:
from_date = timestring.Range(api_args['date']['from']).start.date
try:
to_date = iso8601.parse_date(api_args['date']['to'])
except iso8601.ParseError:
to_date = timestring.Range(api_args['date']['to']).start.date
api_args['date']['from'] = from_date.isoformat()[0:19]
api_args['date']['to'] = to_date.isoformat()[0:19]
api_results = 1
api_page = 1
api_offset = 0
while api_results > 0 and api_page < 250:
print "Fetching page %s ..." % (api_page, )
api_args['from'] = api_offset
results = self.api_request(index_name,
self.source_definition['frontend_type'],
**api_args) # 100 for now ...
for result in results[u'hits'][u'hits']:
yield 'application/json', json.dumps(result)
api_results = len(results[u'hits'][u'hits'])
api_offset += api_results
api_page += 1
def get_body_data(client, date=None):
username = str(client.effective_username)
filename = ""
start_date = datetime.today().date()
dates = []
weights = []
body_fats = []
client_weight = OrderedDict()
client_body_fat = OrderedDict()
if date is None:
date_string = timestring.Range(
'30 days ago').start.date.date().strftime('%m%d%Y')
filename = username + '_body_data_since_' + date_string + '.csv'
client_weight = client.get_measurements('Weight')
client_body_fat = client.get_measurements('Body Fat %')
else:
filename = username + 'body_data_since_' + date + '.csv'
start_date = start_date = timestring.Range(date).start.date.date()
client_weight = client.get_measurements('Weight', start_date)
client_body_fat = client.get_measurements('Body Fat %', start_date)
i = 0
date_keys = []
for (d1, w) in sorted(client_weight.iteritems()):
dates.append(datetime.strftime(d1, "%m/%d/%Y"))
weights.append(w)
date_keys.append(d1)
body_fat_dict = dict(client_body_fat)
for key in date_keys:
body_fats.append(body_fat_dict.get(key, 0) or 0)
f = open(filename, 'wt')
try:
writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(('Index', 'Date (mm/dd/YYYY)', 'Weight (lbs)',
'Weight (kg)', 'Body Fat (%)'))
for i in range(len(dates)):
writer.writerow(
(i + 1, dates[i], weights[i], round(weights[i] * LBS_TO_KG,
2), body_fats[i]))
finally:
f.close()
print(open(filename, 'rt').read())
def test_daterange(self):
schema = valideer.parse({"daterange": "daterange"})
for daterange in ('2 weeks', 'this year', 'next thursday'):
self.assertEqual(
schema.validate(dict(daterange=daterange))['daterange'],
timestring.Range(daterange))
self.assertRaises(error, schema.validate, dict(daterange="never"))
def migrate(self):
db = self.db
all_users = self.os.get_user()
services = ['ceilometer', 'nova', 'neutron', 'glance', 'keystone', 'admin']
for user in all_users:
if user.name not in services:
try:
found = db.select_by('email', user.email)
if found is None:
u = User()
u.user_id = user.id
u.project_id = user.default_project_id
u.email = user.email
u.enabled = user.enabled
u.name = user.name
u.expiration = (timestring.Range("next 30d")).end
u.history.register()
db.insert(u)
except:
continue
def get_nutrition_data(client, date=None):
username = str(client.effective_username)
filename = ""
start_date = datetime.today().date()
dates = []
nutrition_data = []
client_macros = []
if date is None:
date_string = timestring.Range('today').start.date.date().strftime(
'%m%d%Y')
filename = username + '_nutrition_data_since_' + date_string + '.csv'
start_date = timestring.Range('today').start.date.date()
dates.append(start_date)
nutrition_data.append(client.get_date(start_date).totals)
else:
day = timedelta(days=1)
date_o = timestring.Range(date).start.date.date()
date_f = timestring.Range(date).end.date.date()
filename = username + '_nutrition_data_since_' + date_o.strftime(
'%m%d%Y') + '.csv'
while date_o <= date_f:
dates.append(date_o.strftime('%m/%d/%Y'))
nutrition_datum = client.get_date(date_o).totals
nutrition_data.append(client.get_date(date_o).totals)
date_o += day
f = open(filename, 'wt')
try:
writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(
('Index', 'Date (mm/dd/YYYY)', 'Calories', 'Fats (g)',
'Carbohydrates (g)', 'Protein (g)', 'Fiber (g)', 'Sodium (mg)'))
for i in range(len(nutrition_data)):
writer.writerow(
(i + 1, dates[i], nutrition_data[i]['calories'],
nutrition_data[i]['fat'], nutrition_data[i]['carbohydrates'],
nutrition_data[i]['protein'], nutrition_data[i]['fiber'],
nutrition_data[i]['sodium']))
finally:
f.close()
print(open(filename, 'rt').read())
def age(self):
"""Return the age in years
Returns:
[type] -- [description]
"""
diff = timestring.Range(self._birthday, timestring.Date('today'))
return diff.elapse
def validate(self, value, adapt=True):
try:
if isinstance(value, timestring.Range):
if value.tz is None:
value.tz = "UTC"
return value
return timestring.Range(value, tz="UTC")
except timestring.TimestringInvalid:
self.error("Invalid range provied")
def validate_range(ctx, param, custom_range):
if not custom_range:
return None
try:
r = timestring.Range(custom_range)
date_range = [r[0].date, r[1].date]
return date_range
except timestring.TimestringInvalid:
raise click.BadParameter(
"range needs to be a simple phrase like 'last 2 weeks' or a YYYY-MM-DD-YYYY-MM-DD string"
)
def __generate_user_data(self, name, email, enabled, expire):
user = User()
user.name = name
user.email = email
user.enabled = enabled
if (is_int(expire)):
expire = str(expire) + "d"
user.expiration = (timestring.Range("next " + expire)).end
project_name = (user.name).title() + "'s project"
password = __generate_password()
user.project_name = project_name
user.password = password
return user
def date_filter(friends, from_date, to_date):
""" date_filter creates a list of friend objects
which the friends are added between from_date and to_date
Arguments:
friends: a list of friend objects
from_date: a timestring.Date instance or None
to_date: a timestring.Date instance or None
"""
if from_date is None and to_date is None:
return friends
if from_date and to_date: # both are not None
date_range = timestring.Range(start=from_date, end=to_date)
# if timestamp in date_range is implemented by the timestring library
return [f for f in friends if f['timestamp'] in date_range]
# before to_date
if from_date is None:
return [f for f in friends if f['timestamp'] < to_date]
# after from_date
if to_date is None:
return [f for f in friends if f['timestamp'] > from_date]
def DateConvertorFromInterval(UserInput):
return timestring.Range(UserInput).start.date, timestring.Range(
UserInput).end.date
def sorted_todos_by_project(cfg, todo_cfg=None):
"""
Takes our todo list, and returns two dictionaries of where the keys equal
to the project name, and the value is a list of todo items under that
project.
- Note that a todo item may be appended to multiple second level HTML lists
if the item is listed under multiple projects.
- Note that todo items without a project are discarded.
- Note that completed items beyond `completion_cutoff` (measured in days)
are discarded.
todo_cfg is called to topydo.config directs as the path of the test
configuration. Setting this to None will use the normal configuration.
"""
'''
print(type(cfg))
print(cfg)
print(type(cfg['todo']), cfg['todo'])
print(type(cfg['todo']['completion_cutoff']), cfg['todo']['completion_cutoff'])
'''
completion_range = timestring.Range('last {!s} days'.format(cfg['todo']['completion_cutoff']))
my_sorter = Sorter(p_sortstring=cfg['todo']['sort_string'])
todofile = TodoFile.TodoFile(topydo_config(todo_cfg).todotxt())
# print('Loaded todo file from {}'.format(todofile.path))
todotodos = TodoList.TodoList(todofile.read())
# todolist = my_sorter.sort(todolist) # in topydo v0.10
# json_str = JsonPrinter().print_list(todolist) # in topydo v0.10
todolist = my_sorter.sort(todotodos.todos()) # sort before filters
# filters return a list, so apply them all at once?
todolist = HiddenTagFilter().filter(todolist)
todo_json_str = JsonPrinter().print_list(todolist)
todo_json = json.loads(todo_json_str)
donefile = TodoFile.TodoFile(topydo_config(todo_cfg).archive())
# print('Loaded done file from {}'.format(donefile.path))
donetodos = TodoList.TodoList(donefile.read())
donelist = my_sorter.sort(donetodos.todos())
donelist = HiddenTagFilter().filter(donelist)
done_json_str = JsonPrinter().print_list(donelist)
done_json = json.loads(done_json_str)
active_todos = {}
completed_todos = {}
for my_json in [todo_json, done_json]:
for todo in my_json:
if not todo['completed']:
for project in todo['projects']:
try:
active_todos[project].append(todo['source'])
except KeyError:
active_todos[project] = [todo['source']]
else:
completion_date = timestring.Date(todo['completion_date'])
if completion_date in completion_range:
for project in todo['projects']:
try:
completed_todos[project].append(todo['source'])
except KeyError:
completed_todos[project] = [todo['source']]
return active_todos, completed_todos
def get_full_nutrition_data(client, date=None):
username = str(client.effective_username)
filename = ""
start_date = datetime.today().date()
dates = []
nutrition_data = []
client_macros = []
meal_keys = client.get_date(start_date).keys(
) #['supplements', 'meal 1', 'meal 2', 'meal 3', 'snacks', 'refeed']
meals = []
# for a single day
if date is None:
date_string = timestring.Range('today').start.date.date().strftime(
'%m%d%Y')
filename = username + '_nutrition_data_since_' + date_string + '.csv'
start_date = timestring.Range('today').start.date.date()
dates.append(start_date)
nutrition_data.append(client.get_date(start_date).totals)
else:
day = timedelta(days=1)
date_o = timestring.Range(date).start.date.date()
date_f = timestring.Range(date).end.date.date()
filename = username + '_full_nutrition_data_since_' + date_o.strftime(
'%m%d%Y') + '.csv'
while date_o <= date_f:
nutrition_datum = client.get_date(date_o).totals
nutrition_data.append(client.get_date(date_o))
dates.append(date_o.strftime('%m/%d/%Y'))
date_o += day
f = open(filename, 'wt')
try:
writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
for i in range(len(nutrition_data)):
writer.writerow(
(i + 1, dates[i], 'Meals', 'Food Entry', 'Calories', 'Fat (g)',
'Carbohydrates (g)', 'Net Carbohydrate (g)', 'Protein (g)',
'Fiber (g)', 'Sodium (mg)'))
for meal_key in nutrition_data[i].keys():
writer.writerow(
(' ', ' ', meal_key, 'Totals',
(nutrition_data[i][meal_key].totals.get('calories', 0)
or 0), (nutrition_data[i][meal_key].totals.get('fat', 0)
or 0), (nutrition_data[i][meal_key].totals.get(
'carbohydrates', 0) or 0),
(nutrition_data[i][meal_key].totals.get(
'carbohydrates', 0) or 0) if
((nutrition_data[i][meal_key].totals.get(
'carbohydrates', 0) or 0) -
(nutrition_data[i][meal_key].totals.get('fiber', 0) or 0)
< 0) else
((nutrition_data[i][meal_key].totals.get(
'carbohydrates', 0) or 0) -
(nutrition_data[i][meal_key].totals.get('fiber', 0) or 0)
), (nutrition_data[i][meal_key].totals.get('protein', 0)
or 0),
(nutrition_data[i][meal_key].totals.get('fiber', 0) or 0),
(nutrition_data[i][meal_key].totals.get('sodium', 0)
or 0)))
if len(nutrition_data[i][meal_key].entries) is 0:
continue
else:
for meal_entry in nutrition_data[i][meal_key].entries:
writer.writerow(
(' ', ' ', ' ', meal_entry.name,
meal_entry['calories'], meal_entry['fat'],
meal_entry['carbohydrates'],
(meal_entry['carbohydrates']) if
(meal_entry['carbohydrates'] -
meal_entry['fiber'] < 0) else
(meal_entry['carbohydrates'] -
meal_entry['fiber']), meal_entry['protein'],
meal_entry['fiber'], meal_entry['sodium']))
writer.writerow(
(' ', ' ', ' ', 'Daily Totals',
(nutrition_data[i].totals.get('calories', 0)
or 0), (nutrition_data[i].totals.get('fat', 0) or 0),
(nutrition_data[i].totals.get('carbohydrates', 0) or 0),
(nutrition_data[i].totals.get('carbohydrates', 0) or 0) if
((nutrition_data[i].totals.get('carbohydrates', 0) or 0) -
(nutrition_data[i].totals.get('fiber', 0) or 0) < 0) else
((nutrition_data[i].totals.get('carbohydrates', 0) or 0) -
(nutrition_data[i].totals.get('fiber', 0) or 0)),
(nutrition_data[i].totals.get('protein', 0)
or 0), (nutrition_data[i].totals.get('fiber', 0)
or 0), (nutrition_data[i].totals.get('sodium', 0)
or 0)))
finally:
f.close()
print(open(filename, 'rt').read())
def get_food_entries_data(client, filter=None):
username = str(client.effective_username)
date_string = timestring.Range('4 days ago').start.date.date().strftime(
'%m%d%Y')
dates = []
nutrition_data = []
food_entries = {}
day = timedelta(days=1)
date_o = timestring.Range('4 days ago').start.date.date()
date_f = timestring.Range('4 days ago').end.date.date()
while date_o <= date_f:
current_diary_entry = client.get_date(date_o)
for meal in current_diary_entry.meals:
for entry in meal.entries:
if food_entries.get(entry.name, 0) == 0:
entry_totals = entry.totals
entry_totals['frequency'] = 1
food_entries[entry.name] = entry_totals
else:
food_entries[entry.name]['frequency'] += 1
date_o += day
sorted_food_entries = (
sorted(food_entries.items(), key=lambda x: x[1].get('calories', 0)),
sorted(
food_entries.items(), key=lambda x: (x[1].get('fat', 0) or 1)
), #/((x[1].get('protein',0) or 1) + (x[1].get('carbohydrates', 0) or 1) + (x[1].get('fat', 0) or 1))),
sorted(
food_entries.items(),
key=lambda x: (x[1].get('carbohydrates', 0) or 1)
), #/((x[1].get('protein',0) or 1) + (x[1].get('carbohydrates', 0) or 1) + (x[1].get('fat', 0) or 1))),
sorted(food_entries.items(),
key=lambda x: (x[1].get('carbohydrates', 0) or 0)
if ((x[1].get('carbohydrates', 0) or 0) -
(x[1].get('fiber', 0) or 0) < 0) else
((x[1].get('carbohydrates', 0) or 0) -
(x[1].get('fiber', 0) or 0))),
sorted(
food_entries.items(), key=lambda x: (x[1].get('protein', 0) or 1)
), #/((x[1].get('protein',0) or 1) + (x[1].get('carbohydrates', 0) or 1) + (x[1].get('fat', 0) or 1))),
sorted(food_entries.items(), key=lambda x: x[1].get('fiber', 0)),
sorted(food_entries.items(), key=lambda x: x[1].get('sodium', 0)))
if filter is None:
f_calories = username + '_food_entries_sorted_by_calories' + '.csv'
f_fat = username + '_food_entries_sorted_by_fat' + '.csv'
f_carbohydrates = username + '_food_entries_sorted_by_carbohydrates' + '.csv'
f_net_carbohydrates = username + '_food_entries_sorted_by_net_carbohydrates' + '.csv'
f_protein = username + '_food_entries_sorted_by_protein' + '.csv'
f_fiber = username + '_food_entries_sorted_by_fiber' + '.csv'
f_sodium = username + '_food_entries_sorted_by_sodium' + '.csv'
files = [
f_calories, f_fat, f_carbohydrates, f_net_carbohydrates, f_protein,
f_fiber, f_sodium
]
file_number = 0
for file in files:
f = open(file, 'wt')
try:
writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(
('Index', 'Food Entry', 'Calories', 'Fat (g)',
'Carbohydrates (g)', 'Net Carbohydrate (g)',
'Protein (g)', 'Fiber (g)', 'Sodium (mg)', 'Frequency'))
i = 0
for food_entry_name, food_entry_totals in sorted_food_entries[
Nutrient().nutrients_array[file_number]]:
writer.writerow(
(i + 1, food_entry_name, food_entry_totals['calories'],
food_entry_totals['fat'],
food_entry_totals['carbohydrates'],
(food_entry_totals.get('carbohydrates', 0) or 0) if
((food_entry_totals.get('carbohydrates', 0) or 0) -
(food_entry_totals.get('fiber', 0) or 0) < 0) else
((food_entry_totals.get('carbohydrates', 0) or 0) -
(food_entry_totals.get('fiber', 0) or 0)),
food_entry_totals['protein'],
food_entry_totals['fiber'],
food_entry_totals['sodium'],
food_entry_totals['frequency']))
i += 1
finally:
f.close()
file_number += 1
else:
filename = username + '_food_entries_by_' + filter + '.csv'
f = open(filename, 'wt')
try:
writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(
('Index', 'Food Entry', 'Calories', 'Fat (g)',
'Carbohydrates (g)', 'Net Carbohydrate (g)', 'Protein (g)',
'Fiber (g)', 'Sodium (mg)', 'Frequency'))
i = 0
for food_entry_name, food_entry_totals in sorted_food_entries[
Nutrient().valueForKey(filter)]:
writer.writerow(
(i + 1, food_entry_name, food_entry_totals['calories'],
food_entry_totals['fat'],
food_entry_totals['carbohydrates'],
(food_entry_totals.get('carbohydrates', 0) or 0) if
((food_entry_totals.get('carbohydrates', 0) or 0) -
(food_entry_totals.get('fiber', 0) or 0) < 0) else
((food_entry_totals.get('carbohydrates', 0) or 0) -
(food_entry_totals.get('fiber', 0) or 0)),
food_entry_totals['protein'], food_entry_totals['fiber'],
food_entry_totals['sodium'],
food_entry_totals['frequency']))
i += 1
finally:
f.close()
print(open(filename, 'rt').read())
def validate(self, value, adapt=True):
super(elapse, self).validate(str(value))
return str(len(timestring.Range(value)))
#convert soup object to str to get dates.
soupp = str(soup_level1)
all_dates = []
for j in soupp.split('''<span class="date_posted" data-v-5b44ba93="">'''):
all_dates.append(j.split('<')[0])
print(len(all_dates))
print(all_dates)
all_dates.pop(0)
all_jobs = jobs[2:]
# assert if the length of jobs and dates are same.
assert (len(all_jobs) == len(all_dates))
#change all string of dates(like '3 months ago' ) into datetime object.
datee = []
for u in all_dates:
datee.append(str(timestring.Range(u)).split(' ')[1])
d = [datetime.strptime(i, '%m/%d/%y') for i in datee]
for i in range(len(all_jobs)):
all_jobs[i][1] = d[i]
#creating a pandas dataframe
df = pd.DataFrame(all_jobs, columns=["JOB TITLE", "DATE"])
#sorting by ascending order of date.
df = df.sort_values(by='DATE')
#view the final dataframe.
print(df)
#save the dataframe into csv file.
df.to_csv("Techolution.csv")
def activity(self):
r = timestring.Range(self.last_seen(), timestring.Date("now"))
return r.elapse[:r.elapse.find("hour")+5]
def _convert_to_seconds(self, s):
return sum(map(lambda x: len(timestring.Range(x)), s.split(' ')))
def validate(self, value, adapt=True):
try:
_range = timestring.Range(value)
return _range if adapt else value
except timestring.TimestringInvalid:
self.error("invalid date range provied")
def time_left(self):
if (self.user.enabled is True):
# e = timestring.Date(self.user.expiration)
tl = timestring.Range("now", self.user.expiration)
return tl