def covid_page():
data = get_data()
df = pd.DataFrame({
"height": [x['height'] for x in data],
"weight": [x['weight'] for x in data],
"pokemon": [x['name'] for x in data],
"image": [x['image'] for x in data],
"size": [x['weight'] / x['height'] for x in data]
})
fig = px.scatter(df,
x="height",
y="weight",
size='size',
text="pokemon",
hover_data=["pokemon"])
# fig.update_traces(hovertemplate="<b>%{marker.pokemon}%{text}</b><br><br><b>Height: </b>%{x:.2f}<br><b>Weight: </b>%{y:.2f}")
content = html.Div([
html.Div([
dbc.Button(
"Back to home", color="dark", className="mr-1", href='/'),
html.Div([dcc.Graph(id='Pokemon and their height', figure=fig)],
style={"paddingTop": "40px"})
],
className='text-center container',
style={'paddingTop': "50px"})
])
return content
def get_data():
dataset_id = int(request.args['id'])
dataset = dict()
dataset['data'] = utils.get_data(dataset_id)
dataset['metadata'] = utils.read_metadata(dataset_id)
return jsonify(dataset)
async def plot(
*,
resource_url: str = Query(...,
title="Resource URL",
description="URL to a NetCDF resource"),
get: str = Query(
...,
title="Query string",
description=
"Receive list of parameters or get the plot, specifying the variable name",
regex='^(param|plot)$'),
variable: str = Query(None,
title="Variable name",
description="String with the NetCDF Variable name"),
metadata: bool = Query(
False,
title="metadata",
description="If true add metadata tab to the plot widget")):
if get == 'param':
return get_variables(resource_url)
if get == 'plot':
data = get_data(resource_url, variable)
# json_plot = create_plot(data)
json_plot = create_page(data, metadata=metadata)
json_data = json_item(json_plot, target='tsplot')
return json_data
def webhook():
try:
data = request.get_json()
#if 'token' in data and data['token'] == TOKEN:
if 'type' in data:
_type = data['type']
if 'data' in data:
_data = data['data']
if 'custom' in _data:
custom = _data['custom']
else:
custom = {}
# Actions
if _type == 'downloadStarted':
return jsonify({'status': True})
json_back_data = _data['uid']
uid = json_back_data['uid']
print(uid)
f = open(DEBUG_UID, 'w')
f.write(str(uid) + '\n')
f.close()
elif _type == 'downloadCompleted':
_file = custom['file']
_video_data = get_data(_file)
_response = {
'datetime': _video_data['datetime'],
'uid': _data['uid'],
'url': _data['url'],
'meta': {
'storage': _data['meta']
}
}
print(_data['uid'])
f = open(DEBUG_UID, 'w')
f.write(_data['uid'] + '\n')
send('newVideo', _response, False, False)
f.close()
remove_uploaded_file(_file)
update()
return jsonify({'status': True})
elif _type == 'downloadError':
return jsonify({'status': True})
else:
abort(400, {'status': False, 'message': 'Type no found.'})
else:
abort(400, {'status': False, 'message': 'Invalid data.'})
else:
abort(400, {'status': False, 'message': 'Invalid type.'})
#else:
# abort(400, {
# 'status': False,
# 'message': 'Invalid token.'
# })
except BadRequest:
abort(400, {'status': False, 'message': 'Invalid input data.'})
def stats(num_weeks):
"""
Return the graph with the number of training sessions per sport
"""
if num_weeks <= 0:
num_weeks = 1
data = make_weeklycount(get_data(num_weeks))
return render_template('stats.html',
num_weeks=num_weeks,
data=data,
title='Stats')
def init_data():
"""倒入原始数据"""
d = utils.get_data('./initdata/data.csv')
sdb = sqldb.SQLDB()
results = []
for r in d:
x = r[0].split(',')
results.append([x[0], x[1], x[2], x[3], x[4], x[5]])
sdb.write_data(results)
def get_bill_protocol(form, payment):
data = {
"payer_currency": USD_CURRENCY,
"shop_amount": float(form.amount.data),
"shop_currency": USD_CURRENCY,
"shop_id": SHOP_ID,
"shop_order_id": str(payment.shop_order_id),
}
data = get_data(data, REQUIRED_FIELDS_BILL, PIASTIX_BILL_URL)
return redirect(data["url"])
async def plot(
*,
resource_url: str = Query(...,
title="Resource URL",
description="URL to a NetCDF resource"),
get: str = Query(
...,
title="Query string",
description=
"Receive list of parameters or get the plot, specifying the variable name",
regex='^(param|plot)$'),
variable: str = Query(None,
title="Variable name",
description="String with the NetCDF Variable name"),
axis: str = Query(None,
title="axis type",
description="String with the NetCDF Variable name",
regex='^(x_axis|y_axis)$'),
metadata: bool = Query(
False,
title="metadata",
description="If true add metadata tab to the plot widget")):
if get == 'param':
try:
return get_variables(resource_url)
except IOError:
raise HTTPException(
status_code=422,
detail="URL To invalid or not supported NetCDF resource")
if get == 'plot':
if not axis:
axis = 'y_axis'
data = get_data(resource_url, variable, axis)
# json_plot = create_plot(data)
json_plot = create_page(data, metadata=metadata)
json_data = json_item(json_plot, target='tsplot')
return json_data
def index(**options):
locale, strings = utils.localization(options.get('locale', 'en'))
html = utils.get_data("roadmap.html")
return render_template("roadmap.html", locale=locale, strings=strings)
async def download(
*,
resource_url: str = Query(...,
title="Resource URL",
description="URL to a NetCDF resource"),
variable: List[str] = Query(None,
title="Variable name",
description="List of NetCDF Variable names"),
axis: str = Query(None,
title="axis type",
description="String with the NetCDF Variable name",
regex='^(x_axis|y_axis)$'),
output_format: str = Query(None,
title="output format",
description="output format",
regex='^(csv|nc)$')):
# list of variables
plottable_variables = get_variables(resource_url)
# axis = list(plottable_variables.keys())[0]
if not axis:
axis = 'y_axis'
if not variable:
variables_items = {'variables': plottable_variables[axis]}
else:
variables_items = {'variables': variable}
# check if the user provided valid parameters
valid_vars = []
for i in variables_items['variables']:
if i in plottable_variables[axis]:
valid_vars.append(i)
else:
print('removed:', i)
print(valid_vars)
# create an empty list to append one dataframe for each variables
data = []
for i in valid_vars:
# get_data is handling only variable selection at the moment
# TODO: add an option in get_data to allow time-selection
# a good candidate for this is by using pandas time-range slicing
# it will require one extra parameters in the URL request,
# to handle start/end time selection
data.append(get_data(resource_url, i, axis))
# merge the requested data in a single dataframe
# suffixes = ['_'+i.variable_metadata['standard_name'] for i in data]
try:
df_final = reduce(
lambda left, right: pd.merge(
left, right, suffixes=(False, False), on=data[0].index.name),
data)
except ValueError:
suffixes = ['_' + i.variable_metadata['standard_name'] for i in data]
df_final = reduce(
lambda left, right: pd.merge(
left, right, suffixes=suffixes, on=data[0].index.name), data)
# generate a uuid for the filename
if not output_format:
output_format = 'csv'
if output_format == 'csv':
rv = base64.b64encode(uuid.uuid4().bytes).decode('utf-8')
unique = re.sub(r'[\=\+\/]', lambda m: {
'+': '-',
'/': '_',
'=': ''
}[m.group(0)], rv)
filename = str(unique) + '.' + str(output_format) + '.zip'
# TODO: read the secret-key from a configuration file
s = TimestampSigner('secret-key')
download_token = s.sign(filename).decode()
# this stores the data in the 'DOWNLOAD_DIR' which is set in the docker-compose.yml instruction
outfile = Path(os.environ['DOWNLOAD_DIR'], str(filename))
compression_opts = dict(method='zip', archive_name='dataset.csv')
df_final.to_csv(outfile, compression=compression_opts)
with open('metadata.csv', 'w', newline="") as csv_file:
writer = csv.writer(csv_file)
for key, value in data[0].dataset_metadata.items():
writer.writerow([key, value])
with open('metadata.html', 'w') as f:
f.write(
json2html.convert(json={**data[0].dataset_metadata},
table_attributes="id=\"metadata\" "))
zip = zipfile.ZipFile(outfile, 'a')
zip.write('metadata.html', os.path.basename('metadata.html'))
zip.write('metadata.csv', os.path.basename('metadata.csv'))
zip.close()
# the line below will return a direct download
if os.path.isfile(outfile):
return FileResponse(path=outfile, filename='dataset.csv.zip')
# the line below will redirect to a download landing page
# return RedirectResponse(url='/download/%s' % str(download_token))
if output_format == 'nc':
filename = str(uuid.uuid5(uuid.NAMESPACE_URL,
'download')) + '.' + str(output_format)
s = TimestampSigner('secret-key')
download_token = s.sign(filename).decode()
# this stores the data in the 'DOWNLOAD_DIR' which is set in the docker-compose.yml instruction
outfile = Path(os.environ['DOWNLOAD_DIR'], str(filename))
ds = df_final.to_xarray()
ds.attrs = data[0].dataset_metadata
for i in data:
ds[i.columns.values[0]].attrs = i.variable_metadata
ds.to_netcdf(outfile)
# the line below will return a direct download
if os.path.isfile(outfile):
return FileResponse(path=outfile, filename='out.nc')
def index(**options):
locale, strings = utils.localization(options.get('locale', 'en'))
versions = utils.get_data('changelog.json')
return render_template("changelog.html", locale=locale, strings=strings, versions=versions)