def problem_edit_view(request, **kwargs):
problem = get_object_or_404(Problem, pk=kwargs['pk'])
return render(request, 'patients_app/problems/problem_form.html', {
'problem': problem,
'onset_date': date_to_str(problem.date_onset),
'diagnosis_date': date_to_str(problem.date_diagnosis),
'method': 'PATCH',
})
def pass_tostr(pass_data, sig_freq_hz=1000):
if pass_data is not None:
return "%s (%3d azim, %+2.2f kHz) -> %s (%2.0f deg) -> %s (%3d azim, %+2.2f kHz)" % (
utils.date_to_str(
pass_data["rise_time"]), pass_data["rise_azimuth"],
(sig_freq_hz / 1000.0) * pass_data["rise_doppler_factor"],
utils.date_to_str(pass_data["max_alt_time"]),
pass_data["max_alt"], utils.date_to_str(
pass_data["set_time"]), pass_data["set_azimuth"],
(sig_freq_hz / 1000.0) * pass_data["set_doppler_factor"])
else:
return None
def medication_edit_view(request, **kwargs):
medication = get_object_or_404(Medication, pk=kwargs['pk'])
return render(request, 'patients_app/medications/med_form.html', {
'medication': medication,
'date_prescribed': date_to_str(medication.date_prescribed),
'date_started_taking': date_to_str(medication.date_started_taking),
'date_stopped_taking,': date_to_str(medication.date_stopped_taking),
'dispense_quantity': num_to_str(medication.dispense_quantity),
'dosage_quantity': num_to_str(medication.dosage_quantity),
'number_refills': num_to_str(medication.number_refills),
'method': 'PATCH',
})
def create_xbrl_url_json(self):
result_dict = {}
target_date = utils.str_to_date(settings.since)
count = 0
while True:
response_string = self.get_link_info_str(utils.date_to_str(target_date))
target_list = self.__json_parse(response_string)
if not target_list:
target_date = target_date + timedelta(days=1)
continue
info_dict = self.get_link(target_list)
result_dict.update(info_dict)
time.sleep(1)
target_date = target_date + timedelta(days=1)
count += 1
logger.info(f'action=create_xbrl_url_json count={count}')
if target_date >= utils.str_to_date(settings.until):
break
return result_dict
def to_dict(self):
return {
'id': self.id,
'date': date_to_str(self.date),
'name': self.name,
'raid_id': self.raid.id,
}
async def random_comic() -> Response:
"""Serve a random comic."""
first = str_to_date(FIRST_COMIC)
latest = curr_date()
rand_date = date_to_str(random.uniform(first, latest)) # type: ignore
# If there is no comic for this date yet, "dilbert.com" will auto-redirect
# to the latest comic.
return redirect(f"/{rand_date}")
async def _serve_template(date: str, data: dict, latest_comic: str) -> str:
"""Serve the HTML given scraped data.
Both input dates must be in the format used by "dilbert.com".
Args:
date: The (possibly corrected) date of the comic
data: The scraped comic data
latest_comic: The date of the latest comic
Returns:
The rendered template for the comic page
"""
date_obj = str_to_date(date)
# Links to previous and next comics
previous_comic = date_to_str(
max(str_to_date(FIRST_COMIC), date_obj - timedelta(days=1))
)
next_comic = date_to_str(
min(str_to_date(latest_comic), date_obj + timedelta(days=1))
)
# Whether to disable left/right navigation buttons
disable_left_nav = date == FIRST_COMIC
disable_right_nav = date == latest_comic
# Link to original strip on "dilbert.com"
permalink = SRC_PREFIX + date
return await render_template(
"layout.html",
data=data,
date=date,
first_comic=FIRST_COMIC,
previous_comic=previous_comic,
next_comic=next_comic,
disable_left_nav=disable_left_nav,
disable_right_nav=disable_right_nav,
permalink=permalink,
repo=REPO,
)
async def latest_comic() -> str:
"""Serve the latest comic."""
# If there is no comic for this date yet, "dilbert.com" will auto-redirect
# to the latest comic.
today = date_to_str(curr_date())
# If there is no comic for this date yet, we still want to keep this as the
# homepage, as a redirection would alter the URL, and lead to slower
# loading.
return await serve_comic(today, allow_redirect=False)
async def cache_data(self, data, date):
"""Cache the comic data into the database."""
# The given date can be invalid (i.e. we may have been redirected to a
# comic with a different date), hence get the correct date from the
# scraped data.
date = date_to_str(str_to_date(data["dateStr"], fmt=ALT_DATE_FMT))
# This lock ensures that the no. of rows in the cache doesn't increase.
# This can happen, as the code involves first clearing excess rows,
# then adding a new row. Therefore, the following can increase the no.
# of rows:
# 1. Coroutine 1 clears excess rows
# 2. Coroutine 2 clears no excess rows, as coroutine 1 did them
# 3. Coroutine 1 adds its row
# 4. Coroutine 2 adds its row
async with Lock():
try:
await self._clean_cache()
except Exception as ex:
# This crash means that there can be some extra rows in the
# cache. As the row limit is a little conservative, this should
# not be a big issue.
self.logger.error(f"Failed to clean cache: {ex}")
self.logger.debug("", exc_info=True)
date_obj = str_to_date(date)
try:
async with self.pool.acquire() as conn:
await conn.execute(
"""INSERT INTO comic_cache (comic, img_url, title)
VALUES ($1, $2, $3);""",
date_obj,
data["imgURL"],
data["title"],
)
except UniqueViolationError:
# This comic date exists, so some other coroutine has already
# cached this date in parallel. So we can simply update
# `last_used` later (outside the lock).
self.logger.warn(
f"Trying to cache date {date}, which is already cached."
)
else:
return # succeeded in caching data, so exit
# This only executes if caching data led to a UniqueViolation error.
# The lock isn't needed here, as this command cannot increase the no.
# of rows in the cache.
self.logger.info("Now trying to update `last_used` in cache.")
async with self.pool.acquire() as conn:
await conn.execute(
"UPDATE comic_cache SET last_used = DEFAULT WHERE comic = $1;",
date_obj,
)
def past_price(ticker_obj,
days): # past real days, automatically displays graph
delta = int(round(days * (5 / 7)))
delta = str(delta) + "d"
hist = ticker_obj.history(period=delta)
start_date = utils.date_to_str(hist.index[0].date())
today = utils.date_to_str(datetime.date.today())
close = list(hist['Close'])
days_list = [i for i in range(len(close))]
df = pd.DataFrame({"Price": close, "Days": days_list})
plot = sb.lineplot(x="Days", y="Price", data=df)
plot.set(xlabel=("{start} to {today} ~ {days} days"
).format(start=utils.date_concat(start_date),
today=utils.date_concat(today),
days=days))
plot.set(ylabel=str(ticker_obj.info['symbol'] + " Price"))
plt.show()
return
def option_data(self): # returns dataframe of options info
if not self.expiry:
return ("Invalid option; err1")
exp_date = utils.date_to_str(self.expiry)
chain = self.obj.option_chain(exp_date)
if self.put:
chain = chain.puts
else:
chain = chain.calls
option_data = chain[chain['strike'] == self.strike]
return option_data
def default(self, obj):
if isinstance(obj, datetime.datetime):
# convert any datetime to RFC 1123 format
return date_to_str(obj)
elif isinstance(obj, (datetime.time, datetime.date)):
# should not happen since the only supported date-like format
# supported at dmain schema level is 'datetime' .
return obj.isoformat()
elif isinstance(obj, ObjectId):
# BSON/Mongo ObjectId is rendered as a string
return str(obj)
return json.JSONEncoder.default(self, obj)
def on_bt_select_clicked(self, data=None):
"""
Check user information and accept or reject the login
"""
# Calendar widget holds month in zero based index 0..11
y, m, d = self.calendar.get_date()
date = datetime.date(y, m + 1, d)
try:
self.__entry.set_text(u.date_to_str(date))
if self.__callback:
self.__callback()
self.window.destroy()
except:
self.message_error(_(u'Selecione a data corretamente'))
async def serve_comic(
date: str, allow_redirect: bool = True
) -> Union[str, Response]:
"""Serve the requested comic.
Args:
date: The date of the requested comic, in the format used by
"dilbert.com"
allow_redirect: If there is no comic found for this date, then
whether to redirect to the correct date
Returns:
The rendered template for the comic page
"""
# Execute both in parallel, as they are independent of each other
data, latest_comic = await asyncio.gather(
app.comic_scraper.get_data(date), app.latest_date_scraper.get_data(),
)
# This date differs from the input date if the input is invalid (i.e.
# "dilbert.com" would redirect to a comic with a different date).
actual_date_obj = str_to_date(data["dateStr"], fmt=ALT_DATE_FMT)
actual_date = date_to_str(actual_date_obj)
# Replicates the behaviour of "dilbert.com" by redirecting to the correct
# date.
if allow_redirect and actual_date != date:
return redirect(f"/{actual_date}")
# This will contain awaitables for caching data (if required) and rendering
# the template. They are both independent of each other, and thus can be
# run in parallel.
todos = []
# The date of the latest comic is often retrieved from the cache. If
# "dilbert.com" has redirected to a date which is newer than the cached
# value, then there is a new "latest comic". So cache the answer of
# "dilbert.com".
if str_to_date(latest_comic) < actual_date_obj:
latest_comic = actual_date
todos.append(app.latest_date_scraper.cache_data(actual_date))
todos.append(_serve_template(actual_date, data, latest_comic))
results = await asyncio.gather(*todos)
return results[-1] # this is the rendered template
def check(update, context):
user = get_user(update)
if len(user.followed_issues) == 0:
update.message.reply_text('Non segui nessun manga, aggiungine con /add_issue')
elif user.last_check + CHECK_COOLDOWN <= time.time():
locale.setlocale(locale.LC_TIME, user.language or 'it_IT')
new_issues = spider.get_new_chapters(user.followed_issues, user.last_check)
user.last_check = int(time.time())
ud.save_user_data(user)
if len(new_issues) == 0:
update.message.reply_text('Non ci sono novità dall\'ultimo controllo')
else:
for i, issue in enumerate(new_issues):
reply = [
f'<b>{issue}</b>'
]
volumes = list(new_issues[issue].keys())
if len(volumes) > 3:
volumes = volumes[0:3]
for volume in volumes:
reply.append(volume)
chapters = new_issues[issue][volume]['chapters']
chapters.sort(key=lambda x: x['title'])
for chapter in chapters:
title = chapter['title']
url = chapter['url']
released = date_to_str(chapter['release'])
reply.append(f'● <a href="{url}">{title}</a> - <i>{released}</i>')
reply.append('\n')
update.message.reply_html('\n'.join(reply))
if i < len(new_issues) - 1:
time.sleep(1.0)
else:
update.message.reply_text('Si può effettuare un controllo ogni 15 minuti')
async def scrape_data(self):
"""Scrape the date of the latest comic from "dilbert.com"."""
# If there is no comic for this date yet, "dilbert.com" will
# auto-redirect to the latest comic.
latest = date_to_str(curr_date())
url = SRC_PREFIX + latest
async with self.sess.get(url) as resp:
self.logger.debug(f"Got response for latest date: {resp.status}")
date = resp.url.path.split("/")[-1]
# Check to see if the date is invalid
try:
str_to_date(date)
except ValueError:
raise ScrapingException(
"Error in scraping the latest date from the URL")
return date
async def get_cached_data(self):
"""Get the cached latest date from the database.
If the latest date entry is stale (i.e. it was updated a long time
back), or it wasn't found in the cache, None is returned.
"""
async with self.pool.acquire() as conn:
# The interval for "freshness" of the entry has to be given this
# way instead of '$1 hours', because of PostgreSQL's syntax.
# All dates managed by asyncpg are set to UTC.
date = await conn.fetchval(
"""SELECT latest FROM latest_date
WHERE last_check >= CURRENT_TIMESTAMP - INTERVAL '1 hour' * $1;
""",
LATEST_DATE_REFRESH,
)
if date is not None:
# A "fresh" entry was found
date = date_to_str(date)
return date
async def get_cached_data(self, date):
"""Get the cached comic data from the database."""
async with self.pool.acquire() as conn:
# The other columns in the table are: `comic`, `last_used`. `comic`
# is not required here, as we already have the date as a function
# argument. In case the date given here is invalid (i.e. it would
# redirect to a comic with a different date), we cannot retrieve
# the correct date from the cache, as we aren't caching the mapping
# of incorrect:correct dates. `last_used` will be updated later.
row = await conn.fetchrow(
"SELECT img_url, title FROM comic_cache WHERE comic = $1;",
str_to_date(date),
)
if row is None:
# This means that the comic for this date wasn't cached, or the
# date is invalid (i.e. it would redirect to a comic with a
# different date).
return None
data = {
"title": row[1],
"dateStr": date_to_str(str_to_date(date), fmt=ALT_DATE_FMT),
"imgURL": row[0],
}
# Update `last_used`, so that this comic isn't accidently de-cached. We
# want to keep the most recently used comics in the cache, and we are
# currently using this comic.
self.logger.info("Updating `last_used` for data in cache")
async with self.pool.acquire() as conn:
await conn.execute(
"UPDATE comic_cache SET last_used = DEFAULT WHERE comic = $1;",
str_to_date(date),
)
return data
def __init__(self, option):
# assert(type(option) == Option)
self.date_init = utils.date_to_str(dt.date.today)
self.last_price = 0
def count_someDays_request(self,start_date,end_date):
all_dates = utils.get_all_dates(start_date,end_date)
for d in all_dates:
print d
self.count_daily_request(utils.date_to_str(d))
date_borders = date_range(min_date, max_date, delta_days=granularity_in_days)
date_borders.append(max_date)
# extract and clean data
current_timeseries = timseries_data[
(timseries_data['currency'] == currency)
& (timseries_data['category'] == category)
# & (timseries_data['departments_ids'].str.contains('29')) # per vedere singolo dipartimento
# & ( timseries_data['departments_ids'].str.contains('29') | timseries_data['departments_ids'].str.contains('74') | timseries_data['departments_ids'].str.contains('111') ) # per vedere piuù dipartimenti
]
current_timeseries.dropna(inplace=True)
# create aggregated timeseries
dates = [date_to_str(d) for d in date_borders[:-1]]
ys = []
ys_err = []
for i in range(len(date_borders) - 1):
cur_date = date_borders[i]
next_date = date_borders[i + 1]
partial_timeseries = current_timeseries[(current_timeseries['date'] >= cur_date)
& (current_timeseries['date'] <= next_date)]
ys.append(partial_timeseries[kpi].mean()) # aggregate with mean
# ys_err.append(partial_timeseries[kpi].std() / sqrt(partial_timeseries[kpi].count()) )
# ys.append(partial_timeseries[kpi].sum()) # aggregate with sum
# stat analysis
def __str__(self):
return "Examen Realizado el: %s" %date_to_str(self.fecha)
def fecha_(self):
return date_to_str(self.fecha)
def req_historical_data(bbg_identifier, startDate, endDate):
# Recast start & end dates in Bloomberg's format
startDate = date_to_str(startDate, "%Y%m%d")
endDate = date_to_str(endDate, "%Y%m%d")
if (pd.to_datetime(startDate) >= pd.to_datetime(endDate)):
sys.exit(
"in req_historical_data in 'bloomberg_functions.py': " + \
"specified startDate is later than endDate!"
)
# First, check to see if there is already a local .p data file with the
# data you need for bbg_identifier. If it's not there, create it.
if not os.path.isdir("bbg_data"):
os.makedirs("bbg_data")
print("created the 'bbg_data' folder.")
if (bbg_identifier + ".csv") in os.listdir("bbg_data"):
old_bbg_data = pd.read_csv("bbg_data/" + bbg_identifier + ".csv")
first_old = pd.to_datetime(min(old_bbg_data['Date'])).date()
last_old = pd.to_datetime(max(old_bbg_data['Date'])).date()
first_new = pd.to_datetime(startDate).date()
last_new = pd.to_datetime(endDate).date()
if first_old <= first_new and last_old >= last_new:
# Don't need to make a query; have all data we need.
histdata = old_bbg_data[[(pd.to_datetime(x).date() <= last_new) &
(pd.to_datetime(x).date() >= first_new)
for x in old_bbg_data['Date']]]
histdata.reset_index(drop=True, inplace=True)
return histdata
if first_old > first_new and last_old < last_new:
# do nothing for now, just requery the bigger dataset. Can refine
# this case later.
print(
"overwriting old data with date range: " + startDate + \
" to " + endDate
)
else:
if first_new < first_old:
endDate = date_to_str(first_old, "%Y%m%d")
else:
startDate = date_to_str(last_old, "%Y%m%d")
print(startDate)
options = parseCmdLine()
# Fill SessionOptions
sessionOptions = blpapi.SessionOptions()
sessionOptions.setServerHost(options.host)
sessionOptions.setServerPort(options.port)
print("Connecting to %s:%s" % (options.host, options.port))
# Create a Session
session = blpapi.Session(sessionOptions)
# Start a Session
if not session.start():
print("Failed to start session.")
return
try:
# Open service to get historical data from
if not session.openService("//blp/refdata"):
print("Failed to open //blp/refdata")
return
# Obtain previously opened service
refDataService = session.getService("//blp/refdata")
# Create and fill the request for the historical data
request = refDataService.createRequest("HistoricalDataRequest")
request.getElement("securities").appendValue(bbg_identifier)
request.getElement("fields").appendValue("OPEN")
request.getElement("fields").appendValue("HIGH")
request.getElement("fields").appendValue("LOW")
request.getElement("fields").appendValue("PX_LAST")
request.getElement("fields").appendValue("EQY_WEIGHTED_AVG_PX")
request.set("periodicityAdjustment", "ACTUAL")
request.set("periodicitySelection", "DAILY")
request.set("startDate", startDate)
request.set("endDate", endDate)
request.set("maxDataPoints", 1400) # Don't adjust please :)
print("Sending Request:", request)
# Send the request
session.sendRequest(request)
# Process received events
while (True):
# We provide timeout to give the chance for Ctrl+C handling:
ev = session.nextEvent(500)
for msg in ev:
if str(msg.messageType()) == "HistoricalDataResponse":
histdata = []
for fd in msg.getElement("securityData").getElement(
"fieldData").values():
histdata.append([fd.getElementAsString("date"), \
fd.getElementAsFloat("OPEN"),
fd.getElementAsFloat(
"HIGH"),
fd.getElementAsFloat("LOW"), \
fd.getElementAsFloat("PX_LAST"), \
fd.getElementAsFloat(
"EQY_WEIGHTED_AVG_PX")])
histdata = pd.DataFrame(histdata,
columns=[
"Date", "Open", "High", "Low",
"Close", "VWAP"
])
if ev.eventType() == blpapi.Event.RESPONSE:
# Response completely received, so we could exit
if 'old_bbg_data' in locals():
histdata = pd.concat([histdata, old_bbg_data], axis=0)
histdata = histdata.drop_duplicates('Date')
histdata = histdata.sort_values('Date')
histdata.reset_index(drop=True, inplace=True)
pd.DataFrame.to_csv(histdata,
"bbg_data/" + bbg_identifier + ".csv",
index=False)
return histdata
finally:
# Stop the session
session.stop()