Make Location-Allocation Analysis Layer (Network Analyst)

Summary

Makes a location-allocation network analysis layer and sets its analysis properties. A location-allocation analysis layer is useful for choosing a given number of facilities from a set of potential locations so that a demand will be allocated to facilities in an optimal and efficient manner. The layer can be created using a local network dataset or a service hosted online or in a portal.

Usage

• After creating the analysis layer with this tool, you can add network analysis objects to it using the Add Locations tool, solve the analysis using the Solve tool, and save the results on disk using the Save To Layer File tool.

• When using this tool in geoprocessing models, if the model is run as a tool, the output network analysis layer must be made a model parameter; otherwise, the output layer is not added to the contents of the map.

• In ArcGIS AllSource, network analysis layer data is stored on disk in file geodatabase feature classes. When creating a network analysis layer in a project, the layer's data will be created in a new feature dataset in the Current Workspace environment. When creating a network analysis layer in a Python script, you must first explicitly set the workspace environment to a file geodatabase where you want the layer's data to be stored using arcpy.env.workspace = "<path to file gdb>". When the layer is created, a new feature dataset containing the appropriate sublayer feature classes will be added to this file geodatabase.

Parameters

Dialog

Label	Explanation	Data Type
Network Data Source	The network dataset or service on which the network analysis will be performed. Use the portal URL for a service.	Network Dataset Layer;String
Layer Name (Optional)	The name of the network analysis layer to create.	String
Travel Mode (Optional)	The name of the travel mode to use in the analysis. The travel mode represents a collection of network settings, such as travel restrictions and U-turn policies, that determine how a pedestrian, car, truck, or other medium of transportation moves through the network. Travel modes are defined on your network data source. An arcpy.na.TravelMode object and a string containing the valid JSON representation of a travel mode can also be used as input to the parameter.	String
Travel Direction (Optional)	Specifies the direction of travel between facilities and demand points when calculating the network costs. The direction of travel may affect the allocation of the demand points to the facilities on a network with one-way restrictions and different impedances based on direction of travel. For instance, it may take 15 minutes to drive from the demand point to the facility but only 10 minutes when driving from the facility to the demand point. Away from facilities—Direction of travel is from facilities to demand points. This is the default. Fire departments commonly use this setting, since they are concerned with the time it takes to travel from the fire station to the location of the emergency. Toward facilities—Direction of travel is from demand points to facilities. Retail stores commonly use this setting, since they are concerned with the time it takes the shoppers to reach the store.	String
Problem Type (Optional)	The problem type that will be solved. The choice of the problem type depends on the kind of facility being located. Different kinds of facilities have different priorities and constraints. Minimize impedance—This option solves the warehouse location problem. It selects a set of facilities so that the total sum of weighted impedances (demand at a location times the impedance to the closest facility) is minimized. This problem type is often known as the P-Median problem. This is the default problem type. Maximize coverage—This option solves the fire station location problem. It selects facilities so that all or the greatest amount of demand is within a specified impedance cutoff. Maximize capacitated coverage—This option solves the location problem in which facilities have a finite capacity. It selects facilities so that all or the greatest amount of demand can be served without exceeding the capacity of any facility. In addition to honoring capacity, it selects facilities so that the total sum of weighted impedance (demand allocated to a facility multiplied by the impedance to or from the facility) is minimized. Minimize facilities—This option solves the fire station location problem. It selects the minimum number of facilities needed to cover all or the greatest amount of demand within a specified impedance cutoff. Maximize attendance—This option solves the neighborhood store location problem in which the proportion of demand allocated to the nearest chosen facility falls with increasing distance. The set of facilities that maximize the total allocated demand is selected. Demand greater than the specified impedance cutoff does not affect the selected set of facilities. Maximize market share—This option solves the competitive facility location problem. It selects facilities to maximize market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The set of facilities that maximizes the total allocated demand is selected. Target market share—This option solves the competitive facility location problem. It selects facilities to reach a specified target market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The minimum number of facilities needed to reach the specified target market share is selected.	String
Cutoff (Optional)	The maximum impedance at which a demand point can be allocated to a facility in the units of the impedance attribute used by the specified Travel Mode value. The maximum impedance is measured by the least-cost path along the network. If a demand point is outside the cutoff, it is left unallocated. This parameter can be used to model the maximum distance that people are willing to travel to visit stores or the maximum time that is permitted for a fire department to reach anyone in the community. This cutoff value can be overridden on a per-demand-point basis by specifying individual cutoff values in the demand points sublayer in the Cutoff_[Impedance] property. For example, it may show that people in rural areas are willing to travel up to 10 miles to reach a facility, while people in the city are only willing to travel up to 2 miles. You can model this behavior by setting the cutoff value of the analysis layer to 10 and setting the Cutoff_Miles value of each demand point in urban areas to 2. By default, no cutoff value is used for the analysis.	Double
Number of Facilities to Find (Optional)	The number of facilities that the solver will locate. The default value is 1. The facilities with a FacilityType value of Required are always part of the solution when there are more facilities to find than required facilities; any excess facilities to choose are picked from candidate facilities. Any facilities that have a FacilityType value of Chosen before solving are treated as candidate facilities at solve time. This parameter value is not considered for the Minimize facilities problem type since the solver searches for the minimum number of facilities to locate to maximize coverage. This parameter value is overridden for the Target market share problem type because the solver searches for the minimum number of facilities required to capture the specified market share.	Long
Decay Function Type (Optional)	The equation that will be used for transforming the network cost between facilities and demand points. This parameter, along with the Decay Function Parameter Value parameter, specifies how severely the network impedance between facilities and demand points influences the solver's selection of facilities. Demand points have an ImpedanceTransformation property, which, if set, overrides the Decay Function Parameter Value parameter of the analysis layer on a per-demand-point basis. You may determine that the decay function should be different for urban and rural residents. You can model this by setting the impedance transformation for the analysis layer to match that of rural residents and setting the impedance transformation for the individual demand points located in urban areas to match that of urbanites. Linear—The transformed network impedance between the facility and the demand point is the same as the shortest-path network impedance between them. With this option, the impedance parameter is always set to 1. This is the default. Power—The transformed network impedance between the facility and the demand point is equal to the shortest-path network impedance raised to the power specified by the impedance parameter. Use this option with a positive impedance parameter to specify higher weight to nearby facilities. Exponential—The transformed network impedance between the facility and the demand point is equal to the mathematical constant e raised to the power specified by the shortest-path network impedance multiplied with the impedance parameter. Use this option with a positive impedance parameter to specify a very high weight to nearby facilities.Exponential transformations are commonly used in conjunction with an impedance cutoff.	String
Decay Function Parameter Value (Optional)	A parameter value for the equations specified in the Decay Function Type parameter. This parameter value is ignored when the Decay Function Type parameter is set to Linear. For the Power and Exponential options, the value should not be zero. Demand points have an ImpedanceTransformation property, which, if set, overrides the Decay Function Parameter Value parameter of the analysis layer on a per-demand-point basis. You may determine that the decay function should be different for urban and rural residents. You can model this by setting the impedance transformation for the analysis layer to match that of rural residents and setting the impedance transformation for the individual demand points located in urban areas to match that of urbanites.	Double
Target Market Share (Optional)	The target market share, as a percentage, to solve for when the Problem Type parameter is set to Target market share. It is the percentage of the total demand weight that you want the solution facilities to capture. The solver selects the minimum number of facilities required to capture the target market share specified by this numeric value.	Double
Capacity (Optional)	The default capacity of facilities when the Problem Type parameter is set to Maximize capacitated coverage. This parameter is ignored for all other problem types. Facilities have a Capacity property, which, if set to a nonnull value, overrides the Capacity parameter value for that facility.	Double
Time of Day (Optional)	The time and date of departure. The departure time can be from facilities or demand points, depending on whether Travel Direction is set to Toward facilities or Away from facilities. If you chose a traffic-based impedance attribute, the solution will be generated given dynamic traffic conditions at the time of day specified here. A date and time can be specified as 5/14/2012 10:30 AM. Configure your analysis to use one of the following special dates to model a day of the week or the current date instead of a specific, static date: Today—12/30/1899 Sunday—12/31/1899 Monday—1/1/1900 Tuesday—1/2/1900 Wednesday—1/3/1900 Thursday—1/4/1900 Friday—1/5/1900 Saturday—1/6/1900 Learn more about how dates and times are used and interpreted in a network analysis	Date
Time Zone (Optional)	The time zone of the Time of Day parameter. Local time at locations—The time of day parameter refers to the time zone in which the facilities or demand points are located. If the travel direction is facilities to demand points, this is the time zone of the facilities. If the travel direction is demand points to facilities, this is the time zone of the demand points. This is the default. UTC—The time of day parameter refers to coordinated universal time (UTC). Choose this option if you want the best location for a specific time, such as now, but aren't certain in which time zone the facilities or demand points will be located.	String
Line Shape (Optional)	Specifies the output line shape. Regardless of the output shape type specified, the best route is always determined by the network impedance, never Euclidean distance. This means that only the route shapes are different, not the underlying traversal of the network. No lines—No shape will be generated for the output of the analysis. This is useful if you are solving a very large problem and are interested only in a solution table and are not interested in visualizing the results on a map. Straight lines—The output line shapes will be straight lines connecting the solution facilities to their allocated demand points. This is the default.	String
Accumulate Attributes (Optional)	A list of cost attributes to be accumulated during analysis. These accumulated attributes are for reference only; the solver only uses the cost attribute used by the designated travel mode when solving the analysis. For each cost attribute that is accumulated, a Total_[Impedance] property is populated in the network analysis output features. This parameter is not available if the network data source is an ArcGIS Online service or the network data source is a service on a version of Portal for ArcGIS that does not support accumulation.	String
Ignore Invalid Locations at Solve Time (Optional)	Specifies whether invalid input locations will be ignored. Typically, locations are invalid if they cannot be located on the network. When invalid locations are ignored, the solver will skip them and attempt to perform the analysis using the remaining locations. Checked—Invalid input locations will be ignored and only valid locations will be used. This is the default. Unchecked—All input locations will be used. Invalid locations will cause the analysis to fail.	Boolean

Derived Output

Label	Explanation	Data Type
Network Analyst Layer	The newly created network analysis layer.	Network Analyst Layer

Python

arcpy.management.MakeLocationAllocationAnalysisLayer(network_data_source, {layer_name}, {travel_mode}, {travel_direction}, {problem_type}, {cutoff}, {number_of_facilities_to_find}, {decay_function_type}, {decay_function_parameter_value}, {target_market_share}, {capacity}, {time_of_day}, {time_zone}, {line_shape}, {accumulate_attributes}, {ignore_invalid_locations})

Name	Explanation	Data Type
network_data_source	The network dataset or service on which the network analysis will be performed. Use the portal URL for a service.	Network Dataset Layer;String
layer_name (Optional)	The name of the network analysis layer to create.	String
travel_mode (Optional)	The name of the travel mode to use in the analysis. The travel mode represents a collection of network settings, such as travel restrictions and U-turn policies, that determine how a pedestrian, car, truck, or other medium of transportation moves through the network. Travel modes are defined on your network data source. An arcpy.na.TravelMode object and a string containing the valid JSON representation of a travel mode can also be used as input to the parameter.	String
travel_direction (Optional)	Specifies the direction of travel between facilities and demand points when calculating the network costs. FROM_FACILITIES—Direction of travel is from facilities to demand points. This is the default. Fire departments commonly use this setting, since they are concerned with the time it takes to travel from the fire station to the location of the emergency. TO_FACILITIES—Direction of travel is from demand points to facilities. Retail stores commonly use this setting, since they are concerned with the time it takes the shoppers to reach the store. The direction of travel may affect the allocation of the demand points to the facilities on a network with one-way restrictions and different impedances based on direction of travel. For instance, it may take 15 minutes to drive from the demand point to the facility but only 10 minutes when driving from the facility to the demand point.	String
problem_type (Optional)	The problem type that will be solved. The choice of the problem type depends on the kind of facility being located. Different kinds of facilities have different priorities and constraints. MINIMIZE_IMPEDANCE—This option solves the warehouse location problem. It selects a set of facilities so that the total sum of weighted impedances (demand at a location times the impedance to the closest facility) is minimized. This problem type is often known as the P-Median problem. This is the default problem type. MAXIMIZE_COVERAGE—This option solves the fire station location problem. It selects facilities so that all or the greatest amount of demand is within a specified impedance cutoff. MAXIMIZE_CAPACITATED_COVERAGE—This option solves the location problem in which facilities have a finite capacity. It selects facilities so that all or the greatest amount of demand can be served without exceeding the capacity of any facility. In addition to honoring capacity, it selects facilities so that the total sum of weighted impedance (demand allocated to a facility multiplied by the impedance to or from the facility) is minimized. MINIMIZE_FACILITIES—This option solves the fire station location problem. It selects the minimum number of facilities needed to cover all or the greatest amount of demand within a specified impedance cutoff. MAXIMIZE_ATTENDANCE—This option solves the neighborhood store location problem in which the proportion of demand allocated to the nearest chosen facility falls with increasing distance. The set of facilities that maximize the total allocated demand is selected. Demand greater than the specified impedance cutoff does not affect the selected set of facilities. MAXIMIZE_MARKET_SHARE—This option solves the competitive facility location problem. It selects facilities to maximize market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The set of facilities that maximizes the total allocated demand is selected. TARGET_MARKET_SHARE—This option solves the competitive facility location problem. It selects facilities to reach a specified target market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The minimum number of facilities needed to reach the specified target market share is selected.	String
cutoff (Optional)	The maximum impedance at which a demand point can be allocated to a facility in the units of the impedance attribute used by the specified Travel Mode value. The maximum impedance is measured by the least-cost path along the network. If a demand point is outside the cutoff, it is left unallocated. This parameter can be used to model the maximum distance that people are willing to travel to visit stores or the maximum time that is permitted for a fire department to reach anyone in the community. This cutoff value can be overridden on a per-demand-point basis by specifying individual cutoff values in the demand points sublayer in the Cutoff_[Impedance] property. For example, it may show that people in rural areas are willing to travel up to 10 miles to reach a facility, while people in the city are only willing to travel up to 2 miles. You can model this behavior by setting the cutoff value of the analysis layer to 10 and setting the Cutoff_Miles value of each demand point in urban areas to 2. By default, no cutoff value is used for the analysis.	Double
number_of_facilities_to_find (Optional)	The number of facilities that the solver will locate. The default value is 1. The facilities with a FacilityType value of Required are always part of the solution when there are more facilities to find than required facilities; any excess facilities to choose are picked from candidate facilities. Any facilities that have a FacilityType value of Chosen before solving are treated as candidate facilities at solve time. This parameter value is not considered for the MINIMIZE_FACILITIES problem type since the solver searches for the minimum number of facilities to locate to maximize coverage. This parameter value is overridden for the TARGET_MARKET_SHARE problem type because the solver searches for the minimum number of facilities required to capture the specified market share.	Long
decay_function_type (Optional)	The equation that will be used for transforming the network cost between facilities and demand points. This parameter, along with the Decay Function Parameter Value parameter, specifies how severely the network impedance between facilities and demand points influences the solver's selection of facilities. LINEAR—The transformed network impedance between the facility and the demand point is the same as the shortest-path network impedance between them. With this option, the impedance parameter is always set to 1. This is the default. POWER—The transformed network impedance between the facility and the demand point is equal to the shortest-path network impedance raised to the power specified by the impedance parameter. Use this option with a positive impedance parameter to specify higher weight to nearby facilities. EXPONENTIAL—The transformed network impedance between the facility and the demand point is equal to the mathematical constant e raised to the power specified by the shortest-path network impedance multiplied with the impedance parameter. Use this option with a positive impedance parameter to specify a very high weight to nearby facilities.Exponential transformations are commonly used in conjunction with an impedance cutoff. Demand points have an ImpedanceTransformation property, which, if set, overrides the Decay Function Parameter Value parameter of the analysis layer on a per-demand-point basis. You may determine that the decay function should be different for urban and rural residents. You can model this by setting the impedance transformation for the analysis layer to match that of rural residents and setting the impedance transformation for the individual demand points located in urban areas to match that of urbanites.	String
decay_function_parameter_value (Optional)	A parameter value for the equations specified in the decay_function_type parameter. This parameter value is ignored when the decay_function_type parameter is set to LINEAR. For the POWER and EXPONENTIAL options, the value should not be zero. Demand points have an ImpedanceTransformation property, which, if set, overrides the decay_function_parameter_value parameter of the analysis layer on a per-demand-point basis. You may determine that the decay function should be different for urban and rural residents. You can model this by setting the impedance transformation for the analysis layer to match that of rural residents and setting the impedance transformation for the individual demand points located in urban areas to match that of urbanites.	Double
target_market_share (Optional)	The target market share, as a percentage, to solve for when the problem_type parameter is set to TARGET_MARKET_SHARE. It is the percentage of the total demand weight that you want the solution facilities to capture. The solver selects the minimum number of facilities required to capture the target market share specified by this numeric value.	Double
capacity (Optional)	The default capacity of facilities when the problem_type parameter is set to MAXIMIZE_CAPACITATED_COVERAGE. This parameter is ignored for all other problem types. Facilities have a Capacity property, which, if set to a nonnull value, overrides the capacity parameter value for that facility.	Double
time_of_day (Optional)	The time and date of departure. The departure time can be from facilities or demand points, depending on whether travel_direction is set to TO_FACILITIES or FROM_FACILITIES. If you chose a traffic-based impedance attribute, the solution will be generated given dynamic traffic conditions at the time of day specified here. A date and time can be specified as 5/14/2012 10:30 AM. Configure your analysis to use one of the following special dates to model a day of the week or the current date instead of a specific, static date: Today—12/30/1899 Sunday—12/31/1899 Monday—1/1/1900 Tuesday—1/2/1900 Wednesday—1/3/1900 Thursday—1/4/1900 Friday—1/5/1900 Saturday—1/6/1900 Learn more about how dates and times are used and interpreted in a network analysis	Date
time_zone (Optional)	The time zone of the Time of Day parameter. LOCAL_TIME_AT_LOCATIONS—The time of day parameter refers to the time zone in which the facilities or demand points are located. If the travel direction is facilities to demand points, this is the time zone of the facilities. If the travel direction is demand points to facilities, this is the time zone of the demand points. This is the default. UTC—The time of day parameter refers to coordinated universal time (UTC). Choose this option if you want the best location for a specific time, such as now, but aren't certain in which time zone the facilities or demand points will be located.	String
line_shape (Optional)	Specifies the output line shape. NO_LINES—No shape will be generated for the output of the analysis. This is useful if you are solving a very large problem and are interested only in a solution table and are not interested in visualizing the results on a map. STRAIGHT_LINES—The output line shapes will be straight lines connecting the solution facilities to their allocated demand points. This is the default. Regardless of the output shape type specified, the best route is always determined by the network impedance, never Euclidean distance. This means that only the route shapes are different, not the underlying traversal of the network.	String
accumulate_attributes [accumulate_attributes,...] (Optional)	A list of cost attributes to be accumulated during analysis. These accumulated attributes are for reference only; the solver only uses the cost attribute used by the designated travel mode when solving the analysis. For each cost attribute that is accumulated, a Total_[Impedance] property is populated in the network analysis output features. This parameter is not available if the network data source is an ArcGIS Online service or the network data source is a service on a version of Portal for ArcGIS that does not support accumulation.	String
ignore_invalid_locations (Optional)	Specifies whether invalid input locations will be ignored. Typically, locations are invalid if they cannot be located on the network. When invalid locations are ignored, the solver will skip them and attempt to perform the analysis using the remaining locations. SKIP—Invalid input locations will be ignored and only valid locations will be used. This is the default. HALT—All input locations will be used. Invalid locations will cause the analysis to fail.	Boolean

Derived Output

Name	Explanation	Data Type
out_network_analysis_layer	The newly created network analysis layer.	Network Analyst Layer

Code sample

MakeLocationAllocationAnalysisLayer example 1 (Python window)

Run the tool using only the required parameters.

network = "C:/Data/SanFrancisco.gdb/Transportation/Streets_ND"
arcpy.na.MakeLocationAllocationAnalysisLayer(network, "StoreLocations")

MakeLocationAllocationAnalysisLayer example 2 (Python window)

Run the tool using all parameters.

network = "C:/Data/SanFrancisco.gdb/Transportation/Streets_ND"
arcpy.na.MakeLocationAllocationAnalysisLayer(network, "NewStores",
                                    "Driving Time", "TO_FACILITIES",
                                    "MAXIMIZE_ATTENDANCE", 3, 5, "POWER", 2, "",
                                    "", "1/1/1900 9:00 AM", "UTC",
                                    "STRAIGHT_LINES", ["TravelTime", "Meters"])

MakeLocationAllocationAnalysisLayer example 3 (workflow)

The following stand-alone Python script demonstrates how the MakeLocationAllocationAnalysisLayer function can be used to choose the store locations that will generate the most business for a retail chain.

# Name: MakeLocationAllocationAnalysisLayer_Workflow.py
# Description: Choose the store locations that would generate the most business
#              for a retail chain. For this scenario, we will perform the
#              location-Allocation analysis using the maximize attendance
#              problem type.
# Requirements: Network Analyst Extension

#Import system modules
import arcpy
from arcpy import env
import os

try:
    #Check out Network Analyst license if available. Fail if the Network Analyst license is not available.
    if arcpy.CheckExtension("network") == "Available":
        arcpy.CheckOutExtension("network")
    else:
        raise arcpy.ExecuteError("Network Analyst Extension license is not available.")
    
    #Set environment settings
    output_dir = "C:/Data"
    #The NA layer's data will be saved to the workspace specified here
    env.workspace = os.path.join(output_dir, "Output.gdb")
    env.overwriteOutput = True

    #Set local variables
    input_gdb = "C:/Data/SanFrancisco.gdb"
    network = os.path.join(input_gdb, "Transportation", "Streets_ND")
    layer_name = "NewStoreLocations"
    travel_mode = "Driving Time"
    facilities = os.path.join(input_gdb, "Analysis", "CandidateStores")
    required_facility = os.path.join(input_gdb, "Analysis", "ExistingStore")
    demand_points = os.path.join(input_gdb, "Analysis", "TractCentroids")
    output_layer_file = os.path.join(output_dir, layer_name + ".lyrx")

    #Create a new location-allocation layer. In this case, the demand travels to
    #the facility. We wish to find 3 potential store locations out of all the
    #candidate store locations using the maximize attendance model.
    result_object = arcpy.na.MakeLocationAllocationAnalysisLayer(network,
                                    layer_name, travel_mode, "TO_FACILITIES",
                                    "MAXIMIZE_ATTENDANCE", cutoff=20,
                                    number_of_facilities_to_find=3)

    #Get the layer object from the result object. The location-allocation layer
    #can now be referenced using the layer object.
    layer_object = result_object.getOutput(0)

    #Get the names of all the sublayers within the location-allocation layer.
    sublayer_names = arcpy.na.GetNAClassNames(layer_object)
    #Stores the layer names that we will use later
    facilities_layer_name = sublayer_names["Facilities"]
    demand_points_layer_name = sublayer_names["DemandPoints"]

    #Load the candidate store locations as facilities using default search
    #tolerance and field mappings.
    arcpy.na.AddLocations(layer_object, facilities_layer_name, facilities, "",
                                                                            "")

    #Load the existing store location as the required facility. Use the field
    #mappings to set the facility type to requried. We need to append this
    #required facility to existing facilities.
    field_mappings = arcpy.na.NAClassFieldMappings(layer_object,
                                                    facilities_layer_name)
    field_mappings["FacilityType"].defaultValue = 1
    arcpy.na.AddLocations(layer_object, facilities_layer_name,
                            required_facility, field_mappings, "",
                            append="APPEND")

    #Load the tract centroids as demand points using default search tolerance
    #Use the field mappings to map the Weight property from POP2000 field.
    demand_field_mappings = arcpy.na.NAClassFieldMappings(layer_object,
                                                    demand_points_layer_name)
    demand_field_mappings["Weight"].mappedFieldName = "POP2000"
    arcpy.na.AddLocations(layer_object, demand_points_layer_name, demand_points,
                          demand_field_mappings, "")

    #Solve the location-allocation layer
    arcpy.na.Solve(layer_object)

    #Save the solved location-allocation layer as a layer file on disk
    layer_object.saveACopy(output_layer_file)

    print("Script completed successfully")

except Exception as e:
    # If an error occurred, print line number and error message
    import traceback, sys
    tb = sys.exc_info()[2]
    print("An error occurred on line %i" % tb.tb_lineno)
    print(str(e))

Environments

Current Workspace