def python_html():
#retrieve input parameters
script, output_variable = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
# check authentication
if not security.userIsAuthenticated(user_id, knowage_address):
return "Error: authentication failed", 401
#retrieve dataset
if dataset_name != "":
dataset_file = "tmp/" + dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(user_id, knowage_address,
dataset_name, datastore_request)
df.to_pickle(dataset_file)
script = "import pandas as pd\n" + dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + script
#execute script
try:
namespace = {output_variable: ""}
exec(script, namespace)
except Exception as e:
return str(e), 400
#collect script result
html = namespace[output_variable]
#remove dataset tmp file
try:
os.remove(dataset_file)
except Exception:
pass
return html, 200
def python_bokeh():
utils.bokehGarbageCollector()
# retrieve input parameters
script = request.get_json()['script']
widget_id = request.get_json()['widget_id']
script_file_name = constants.TMP_FOLDER + "bokeh_script_" + str(widget_id) + ".txt"
user_id = utils.retrieveKnowageInfo(request.headers)
dataset_name, datastore_request = utils.retrieveDatasetInfo(request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers, script=script, user_id=user_id,
dataset_name=dataset_name, datastore_request=datastore_request, widget_id=widget_id)
# check authentication
if not security.userIsAuthorizedForFunctionality(python_widget, constants.EDIT_PYTHON_SCRIPTS):
return "Error: authentication failed", 401
#destroy old bokeh server
if utils.serverExists(python_widget.widget_id):
utils.destroyServer(python_widget.widget_id)
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace("$P{" + d + "}", "drivers_.get(\'" + d + "\')")
# retrieve dataset
if python_widget.dataset_name != None:
dataset_file = constants.TMP_FOLDER + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
#function executed by bokeh server
def modify_doc(doc):
# retrieve script from file
with open(script_file_name, "r") as bk_file:
bk_script = bk_file.read()
#replace curdoc() with keyword "curdoc_"
bk_script = bk_script.replace("curdoc()", "curdoc_")
# execute script
namespace = {'curdoc_': doc, "drivers_": drivers}
exec(bk_script, namespace)
#secondary thread function (bokeh server)
def bk_worker():
server = Server({'/bkapp'+str(python_widget.widget_id): modify_doc}, io_loop=IOLoop(), allow_websocket_origin=["*"], port=cuncurrency_manager.bokeh_resources[python_widget.widget_id].port)
with cuncurrency_manager.lck:
cuncurrency_manager.active_servers.update({python_widget.widget_id:server}) #{widget_id : bokeh_server}
server.start()
server.io_loop.start()
#flush script content to file so that modify_doc() can retrieve the code to be executed
with open(script_file_name,"w") as bokeh_file:
bokeh_file.write(python_widget.script)
#instance a bokeh server for the widget if not instanciated yet
if not utils.serverExists(python_widget.widget_id): #allocate bokeh server
t = Thread(target=bk_worker) #thread that hosts bokeh server
bk_res = BokehResourceList(thread=t, timestamp=datetime.now(), port=utils.findFreePort(), dataset_name=dataset_name)
with cuncurrency_manager.lck:
cuncurrency_manager.bokeh_resources.update({python_widget.widget_id : bk_res}) #{widget_id : BokehResourceList}
t.start()
#serve plot
jscript = server_document(utils.getPythonAddress() + ":" + str(cuncurrency_manager.bokeh_resources[python_widget.widget_id].port) + "/bkapp" + str(python_widget.widget_id))
return render_template("embed.html", script=jscript)
def python_img():
# retrieve input parameters
script, img_file = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
script = security.loadScriptFromDB(user_id, knowage_address, document_id,
widget_id)
# retrieve dataset
if dataset_name != "":
dataset_file = constants.TMP_FOLDER + dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(user_id, knowage_address,
dataset_name, datastore_request)
df.to_pickle(dataset_file)
script = "import pandas as pd\n" + dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + script
# execute script
try:
namespace = {}
exec(script, namespace)
except Exception as e:
return str(e), 400
# collect script result
with open(img_file, "rb") as f:
encoded_img = base64.b64encode(f.read())
#delete temp files
try:
os.remove(img_file)
os.remove(dataset_file)
except Exception:
pass
return "<img src=\"data:image/;base64, " + encoded_img.decode(
'utf-8') + "\" style=\"width:100%;height:100%;\">", 200
def python_html():
#retrieve input parameters
script, output_variable = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
script = security.loadScriptFromDB(user_id, knowage_address, document_id,
widget_id)
#retrieve dataset
if dataset_name != "":
dataset_file = constants.TMP_FOLDER + dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(user_id, knowage_address,
dataset_name, datastore_request)
df.to_pickle(dataset_file)
script = "import pandas as pd\n" + dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + script
#execute script
try:
namespace = {output_variable: ""}
exec(script, namespace)
except Exception as e:
return str(e), 400
#collect script result
html = namespace[output_variable]
#remove dataset tmp file
try:
os.remove(dataset_file)
except Exception:
pass
return html, 200
def python_img():
# retrieve input parameters
img_file = utils.retrieveScriptInfo(request.get_json())[1]
user_id = utils.retrieveKnowageInfo(request.headers)
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers,
output_variable=img_file,
user_id=user_id,
document_id=document_id,
widget_id=widget_id,
dataset_name=dataset_name,
datastore_request=datastore_request)
python_widget.script = security.loadScriptFromDB(python_widget)
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace(
"$P{" + d + "}", "drivers_.get(\'" + d + "\')")
try:
# retrieve dataset
if python_widget.dataset_name != None:
dataset_file = constants.TMP_FOLDER + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
except Exception as e:
logging.error("Error during dataframe conversion: {}".format(e))
return str(e), 400
try:
# execute script
namespace = {"drivers_": drivers}
exec(python_widget.script, namespace)
except Exception as e:
logging.error("Error during script execution: {}".format(e))
return str(e), 400
# collect script result
with open(img_file, "rb") as f:
encoded_img = base64.b64encode(f.read())
#delete temp files
try:
os.remove(img_file)
os.remove(dataset_file)
except Exception:
pass
return "<img src=\"data:image/;base64, " + encoded_img.decode(
'utf-8') + "\" style=\"width:100%;height:100%;\">", 200
def python_img():
# retrieve input parameters
script, img_file = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers,
script=script,
output_variable=img_file,
user_id=user_id,
knowage_address=knowage_address,
dataset_name=dataset_name,
datastore_request=datastore_request)
# check authentication
if not security.userIsAuthorizedForFunctionality(
python_widget, constants.EDIT_PYTHON_SCRIPTS):
return "Error: authentication failed", 401
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace(
"$P{" + d + "}", "drivers_.get(\'" + d + "\')")
# retrieve dataset
if python_widget.dataset_name != "":
dataset_file = constants.TMP_FOLDER + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
# execute script
try:
namespace = {"drivers_": drivers}
exec(python_widget.script, namespace)
except Exception as e:
return str(e), 400
# collect script result
with open(img_file, "rb") as f:
encoded_img = base64.b64encode(f.read())
#delete temp files
try:
os.remove(img_file)
os.remove(dataset_file)
except Exception:
pass
return "<img src=\"data:image/;base64, " + encoded_img.decode(
'utf-8') + "\" style=\"width:100%;height:100%;\">", 200
def python_html():
#retrieve input parameters
output_variable = utils.retrieveScriptInfo(request.get_json())[1]
user_id = utils.retrieveKnowageInfo(request.headers)
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers,
output_variable=output_variable,
user_id=user_id,
document_id=document_id,
widget_id=widget_id,
dataset_name=dataset_name,
datastore_request=datastore_request)
python_widget.script = security.loadScriptFromDB(python_widget)
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace(
"$P{" + d + "}", "drivers_.get(\'" + d + "\')")
try:
#retrieve dataset
if python_widget.dataset_name != None:
dataset_file = constants.TMP_FOLDER + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
except Exception as e:
logging.error("Error during dataframe conversion: {}".format(e))
return str(e), 400
try:
#execute script
namespace = {python_widget.output_variable: "", "drivers_": drivers}
exec(python_widget.script, namespace)
except Exception as e:
logging.error("Error during script execution: {}".format(e))
return str(e), 400
#collect script result
html = namespace[python_widget.output_variable]
#remove dataset tmp file
try:
os.remove(dataset_file)
except Exception:
pass
return html, 200
def python_html():
#retrieve input parameters
script, output_variable = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers,
script=script,
output_variable=output_variable,
user_id=user_id,
knowage_address=knowage_address,
dataset_name=dataset_name,
datastore_request=datastore_request)
# check authentication
if not security.userIsAuthorizedForFunctionality(
python_widget, constants.EDIT_PYTHON_SCRIPTS):
return "Error: authentication failed", 401
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace(
"$P{" + d + "}", "drivers_.get(\'" + d + "\')")
#retrieve dataset
if python_widget.dataset_name != "":
dataset_file = "tmp/" + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
#execute script
try:
namespace = {python_widget.output_variable: "", "drivers_": drivers}
exec(python_widget.script, namespace)
except Exception as e:
return str(e), 400
#collect script result
html = namespace[python_widget.output_variable]
#remove dataset tmp file
try:
os.remove(dataset_file)
except Exception:
pass
return html, 200
def python_img():
# retrieve input parameters
script, img_file = utils.retrieveScriptInfo(request.get_json())
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
# test
if not security.userIsAuthorizedForFunctionality(
user_id, knowage_address, constants.EDIT_PYTHON_SCRIPTS):
print("Unauthorized")
else:
print("Authorized")
# check authentication
if not security.userIsAuthenticated(user_id, knowage_address):
return "Error: authentication failed", 401
# retrieve dataset
if dataset_name != "":
dataset_file = constants.TMP_FOLDER + dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(user_id, knowage_address,
dataset_name, datastore_request)
df.to_pickle(dataset_file)
script = "import pandas as pd\n" + dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + script
# execute script
try:
namespace = {}
exec(script, namespace)
except Exception as e:
return str(e), 400
# collect script result
with open(img_file, "rb") as f:
encoded_img = base64.b64encode(f.read())
#delete temp files
try:
os.remove(img_file)
os.remove(dataset_file)
except Exception:
pass
return "<img src=\"data:image/;base64, " + encoded_img.decode(
'utf-8') + "\" style=\"width:100%;height:100%;\">", 200
def python_bokeh():
# retrieve input parameters
script = request.get_json()['script']
widget_id = request.get_json()['widget_id']
script_file_name = constants.TMP_FOLDER + "bokeh_script_" + str(
widget_id) + ".txt"
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
# check authentication
if not security.userIsAuthenticated(user_id, knowage_address):
return "Error: authentication failed", 401
#destroy old bokeh server
if utils.serverExists(widget_id):
utils.destroyServer(widget_id)
# retrieve dataset
if dataset_name != "":
dataset_file = constants.TMP_FOLDER + dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(user_id, knowage_address,
dataset_name, datastore_request)
df.to_pickle(dataset_file)
script = "import pandas as pd\n" + dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + script
#function executed by bokeh server
def modify_doc(doc):
# retrieve script from file
with open(script_file_name, "r") as bk_file:
bk_script = bk_file.read()
#replace curdoc() with keyword "curdoc_"
bk_script = bk_script.replace("curdoc()", "curdoc_")
# execute script
namespace = {'curdoc_': doc}
exec(bk_script, namespace)
#secondary thread function (bokeh server)
def bk_worker():
server = Server({'/bkapp' + str(widget_id): modify_doc},
io_loop=IOLoop(),
allow_websocket_origin=["localhost:8080"],
port=cuncurrency_manager.ports_dict[widget_id])
with cuncurrency_manager.lck:
cuncurrency_manager.active_servers.update(
{widget_id: server}) #{widget_id : bokeh_server}
server.start()
server.io_loop.start()
#flush script content to file so that modify_doc() can retrieve the code to be executed
with open(script_file_name, "w") as bokeh_file:
bokeh_file.write(script)
#instance a bokeh server for the widget if not instanciated yet
if not utils.serverExists(widget_id): #allocate bokeh server
t = Thread(target=bk_worker) #thread that hosts bokeh server
with cuncurrency_manager.lck:
cuncurrency_manager.active_threads.update(
{widget_id: t}) #{widget_id : thread}
cuncurrency_manager.ports_dict.update({
widget_id:
utils.findFreePort()
}) #{widget_id : port_number_of_bokeh_server}
t.start()
#serve plot
jscript = server_document("http://localhost:" +
str(cuncurrency_manager.ports_dict[widget_id]) +
"/bkapp" + str(widget_id))
return render_template("embed.html", script=jscript)
def python_bokeh():
# retrieve input parameters
document_id, widget_id = utils.retrieveWidgetInfo(request.get_json())
script_file_name = constants.TMP_FOLDER + "bokeh_script_" + str(
widget_id) + ".txt"
user_id, knowage_address = utils.retrieveKnowageInfo(
request.headers, request.get_json())
dataset_name, datastore_request = utils.retrieveDatasetInfo(
request.get_json())
drivers = utils.retrieveAnalyticalDriversInfo(request.get_json())
python_widget = PythonWidgetExecution(analytical_drivers=drivers,
user_id=user_id,
document_id=document_id,
widget_id=widget_id,
knowage_address=knowage_address,
dataset_name=dataset_name,
datastore_request=datastore_request)
python_widget.script = security.loadScriptFromDB(python_widget)
#destroy old bokeh server
if utils.serverExists(python_widget.widget_id):
utils.destroyServer(python_widget.widget_id)
# resolve analytical drivers
for d in drivers:
python_widget.script = python_widget.script.replace(
"$P{" + d + "}", "drivers_.get(\'" + d + "\')")
# retrieve dataset
if python_widget.dataset_name != "":
dataset_file = constants.TMP_FOLDER + python_widget.dataset_name + ".pckl"
df = utils.getDatasetAsDataframe(python_widget)
df.to_pickle(dataset_file)
python_widget.script = "import pandas as pd\n" + python_widget.dataset_name + " = pd.read_pickle(\"" + dataset_file + "\")\n" + python_widget.script
#function executed by bokeh server
def modify_doc(doc):
# retrieve script from file
with open(script_file_name, "r") as bk_file:
bk_script = bk_file.read()
#replace curdoc() with keyword "curdoc_"
bk_script = bk_script.replace("curdoc()", "curdoc_")
# execute script
namespace = {'curdoc_': doc, "drivers_": drivers}
exec(bk_script, namespace)
#secondary thread function (bokeh server)
def bk_worker():
server = Server(
{'/bkapp' + str(python_widget.widget_id): modify_doc},
io_loop=IOLoop(),
allow_websocket_origin=["localhost:8080"],
port=cuncurrency_manager.ports_dict[python_widget.widget_id])
with cuncurrency_manager.lck:
cuncurrency_manager.active_servers.update(
{python_widget.widget_id: server}) #{widget_id : bokeh_server}
server.start()
server.io_loop.start()
#flush script content to file so that modify_doc() can retrieve the code to be executed
with open(script_file_name, "w") as bokeh_file:
bokeh_file.write(python_widget.script)
#instance a bokeh server for the widget if not instanciated yet
if not utils.serverExists(python_widget.widget_id): #allocate bokeh server
t = Thread(target=bk_worker) #thread that hosts bokeh server
with cuncurrency_manager.lck:
cuncurrency_manager.active_threads.update(
{python_widget.widget_id: t}) #{widget_id : thread}
cuncurrency_manager.ports_dict.update({
python_widget.widget_id:
utils.findFreePort()
}) #{widget_id : port_number_of_bokeh_server}
t.start()
#serve plot
jscript = server_document(
"http://localhost:" +
str(cuncurrency_manager.ports_dict[python_widget.widget_id]) +
"/bkapp" + str(python_widget.widget_id))
return render_template("embed.html", script=jscript)
