def make_app(**kwargs):
T = sc.tic()
app = sw.ScirisApp(
name='HealthPrior',
filepath=__file__,
config=hp.webapp.config,
RPC_dict=hp.webapp.rpcs.RPC_dict
) # Create the ScirisApp object. NOTE: app.config will thereafter contain all of the configuration parameters, including for Flask.
sw.make_default_users(app)
print('>> Webapp initialization complete (elapsed time: %0.2f s)' %
sc.toc(T, output=True))
return app
import os
import sys
import numpy as np
import plotly.graph_objects as go
import plotly.figure_factory as ff
import sciris as sc
import base64 # Download/upload-specific import
import json
import tempfile
# Check requirements, and if met, import scirisweb
cv.requirements.check_scirisweb(die=True)
import scirisweb as sw
# Create the app
app = sw.ScirisApp(__name__, name="Covasim")
app.sessions = dict() # For storing user data
flask_app = app.flask_app
#%% Define the API
# Set defaults
max_pop = 10e3 # Maximum population size
max_days = 180 # Maximum number of days
max_time = 10 # Maximum of seconds for a run
die = False # Whether or not to raise exceptions instead of continuing
@app.register_RPC()
def get_defaults(region=None, merge=False):
''' Get parameter defaults '''
# Imports
import pylab as pl
import sciris as sc
import scirisweb as sw
from dask.distributed import Client
client = Client()
runserver = False # Choose to run in the frontend or backend
# Create the app
app = sw.ScirisApp(__name__, name="ParallelComputation")
#def
# Define the RPCs
@app.register_RPC()
def computation(seed=0, n=1000):
# Make graph
pl.seed(int(seed))
fig = pl.figure()
ax = fig.add_subplot(111)
xdata = pl.randn(n)
ydata = pl.randn(n)
colors = sc.vectocolor(pl.sqrt(xdata**2+ydata**2))
ax.scatter(xdata, ydata, c=colors)
# Convert to FE
graphjson = sw.mpld3ify(fig, jsonify=False) # Convert to dict
rawdata = sc.wget(dataurl).splitlines()
data = []
for r,rawline in enumerate(rawdata):
line = rawline.split(',')
if r==0: # Read header
cols = line
else: # Read data
tag = line[0]
yearnum = convertdate(line[1], '%Y-%m-%dT%I:%M:%fZ')
value = float(line[2]) if r>0 else line[2]
data.append([tag, yearnum, value])
df = sc.dataframe(cols=cols, data=data)
return df
# Create the app
app = sw.ScirisApp(__name__, name="PyShiny")
df = loaddata()
# Define the RPCs
@app.register_RPC()
def getoptions(tojson=True):
options = sc.odict([
('Advertising', 'advert'),
('Education', 'educat'),
('Small business', 'smallbiz'),
('Travel', 'travel'),
('Unemployment', 'unempl'),
])
if tojson:
output = sc.sanitizejson(options.keys(), tostring=False)
else:
Super simple Sciris app.
To run, simply type
python app.py
after ScirisWeb has been installed.
To use, go to localhost:8080 in your browser.
Version: 2019jan12
'''
import pylab as pl
import scirisweb as sw
app = sw.ScirisApp(__name__, name="helloworld")
@app.route("/")
def hello():
output = 'Hello world!<br><br>Click <a href="/number">here</a> for a random number.'
return output
@app.route("/number")
def number():
number = pl.rand()
output = 'Random number: %s.<br><br>Click <a href="/">here</a> to go back.' % number
return output