def asset_list(term=None):
import csv
master_list = []
if term is None:
term = ""
# Alphavantage Currency List - CSV
filename = os.path.join(current_path(),
'static/csv_files/physical_currency_list.csv')
with open(filename, newline='') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
if term.upper() in row[0].upper() or term in row[1].upper():
master_list.append({
'symbol': row[0],
'name': row[1],
'provider': 'aa_fx'
})
# Alphavantage Digital Currency list
filename = os.path.join(current_path(),
'static/csv_files/digital_currency_list.csv')
with open(filename, newline='') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
if term.upper() in row[0].upper() or term.upper() in row[1].upper(
):
master_list.append({
'symbol': row[0],
'name': row[1],
'provider': 'aa_digital'
})
# Alphavantage Stock Search EndPoint
try:
url = 'https://www.alphavantage.co/query?function=SYMBOL_SEARCH'
url += '&keywords=' + term
url += '&apikey=' + api
result = requests.get(url).json()
result = result['bestMatches']
for element in result:
master_list.append({
'symbol':
element['1. symbol'],
'name':
element['2. name'],
'provider':
'aa_stock',
'notes':
element['3. type'] + ' ' + element['4. region'],
'fx':
element['8. currency']
})
except Exception:
pass
return (master_list)
def histvol():
# if there's rolling variable, get it, otherwise default to 30
if request.method == "GET":
try:
q = int(request.args.get("rolling"))
except ValueError:
q = 30
else:
q = 30
ticker = request.args.get("ticker")
metadata = request.args.get("meta")
# When ticker is not sent, will calculate for portfolio
if not ticker:
data = generatenav()
data["vol"] = (data["NAV_fx"].pct_change().rolling(q).std() *
(365**0.5) * 100)
# data.set_index('date', inplace=True)
vollist = data[["vol"]]
vollist.index = vollist.index.strftime("%Y-%m-%d")
datajson = vollist.to_json()
if ticker:
filename = "thewarden/historical_data/" + ticker + ".json"
filename = os.path.join(current_path(), filename)
try:
with open(filename) as data_file:
local_json = json.loads(data_file.read())
data_file.close()
prices = pd.DataFrame(
local_json["Time Series (Digital Currency Daily)"]).T
prices["4b. close (USD)"] = prices["4b. close (USD)"].astype(
np.float)
prices["vol"] = (
prices["4b. close (USD)"].pct_change().rolling(q).std() *
(365**0.5) * 100)
pricelist = prices[["vol"]]
datajson = pricelist.to_json()
except (FileNotFoundError, KeyError):
datajson = "Ticker Not Found"
if metadata is not None:
metatable = {}
metatable["mean"] = vollist.vol.mean()
metatable["max"] = vollist.vol.max()
metatable["min"] = vollist.vol.min()
metatable["last"] = vollist.vol[-1]
metatable["lastvsmean"] = (
(vollist.vol[-1] / vollist.vol.mean()) - 1) * 100
metatable = json.dumps(metatable)
return metatable
return datajson
def fx_list():
fx_dict = {}
filename = os.path.join(current_path(),
'static/csv_files/physical_currency_list.csv')
with open(filename, newline='') as csvfile:
reader = csv.reader(csvfile)
fx_dict = {rows[0]: rows[1] for rows in reader}
q = request.args.get("term")
if q is None:
q = ""
list_key = {
key: value
for key, value in fx_dict.items() if q.upper() in key.upper()
}
list_value = {
key: value
for key, value in fx_dict.items() if q.upper() in value.upper()
}
list = {**list_key, **list_value}
list = json.dumps(list)
return list
def fxsymbol(fx, output='symbol'):
# Gets an FX 3 letter symbol and returns the HTML symbol
# Sample outputs are:
# "EUR": {
# "symbol": "",
# "name": "Euro",
# "symbol_native": "",
# "decimal_digits": 2,
# "rounding": 0,
# "code": "EUR",
# "name_plural": "euros"
from warden_modules import current_path
filename = os.path.join(current_path(), 'static/json_files/currency.json')
with open(filename) as fx_json:
fx_list = json.load(fx_json)
try:
out = fx_list[fx][output]
except Exception:
if output == 'all':
return (fx_list[fx])
out = fx
return (out)
def test_paths(self):
print("Checking that current and home paths can be returned...")
print(f"Current Path: {current_path()}")
print(f"Home Path: {home_path()}")
self.assertIsNotNone(current_path())
self.assertIsNotNone(home_path())