import wrf
from netCDF4 import Dataset
import proplot as plot
import cartopy.crs as crs
# Download the dataset from https://www.unidata.ucar.edu/software/netcdf/examples/wrfout_v2_Lambert.nc
# Load the dataset
ncfile = Dataset('wrfout_v2_Lambert.nc')
# Get the variable
slp = wrf.getvar(ncfile, "slp")
# Get the latitude and longitude points
lats, lons = wrf.latlon_coords(slp)
# Get the cartopy mapping object
cart_proj = wrf.get_cartopy(slp)
#Plotting
fig, axs = plot.subplots(proj=cart_proj)
# Define extents
lat = [lats.min(), lats.max()]
lon = [lons.min(), lons.max()]
#format the plot
axs.format(
    lonlim=lon, latlim=lat,
    labels=True, innerborders=True
#Plot using contourf
m = axs.contourf(wrf.to_np(lons), wrf.to_np(lats), wrf.to_np(slp), 
                      transform=crs.PlateCarree(), cmap='roma_r')
#Adding colorbar with label
cbar = fig.colorbar(m, loc='b', label='Sea Level Pressure (hPa)') 
#Saving the figure
fig.savefig('slp.png')
Output
Explanation
  
Basic import stuff for Python
    
import wrf
from netCDF4 import Dataset
import proplot as plot
import cartopy.crs as crs
  
Loading the dataset
    
ncfile = Dataset('wrfout_v2_Lambert.nc')
  
Extracting the varibale of your choice. Here it is sea level pressure (SLP).
    
slp = wrf.getvar(ncfile, "slp")
  
Get the lat/lon and projection of the WRF file. Here the projection is LCC.
    
lats, lons = wrf.latlon_coords(slp)
cart_proj = wrf.get_cartopy(slp)
  
Create the plot and define projection using proj.
fig, axs = plot.subplots(proj=cart_proj)
  
Setting up the extent of the plot by getting the maximum and minimum lat and long.
    
lat = [lats.min(), lats.max()]
lon = [lons.min(), lons.max()]
  
Format the plot aesthetics.
    
axs.format(
 lonlim=lon, latlim=lat,
 labels=True, innerborders=True
  
Plot the filled contour of the variable.
    
m = axs.contourf(wrf.to_np(lons), wrf.to_np(lats), wrf.to_np(slp), 
                   transform=crs.PlateCarree(), cmap='roma_r')
  
Adding the colorbar at the bottom of the plot.
    
cbar = fig.colorbar(m, loc='b', label='Sea Level Pressure (hPa)') 
  
Finally, saving the figure.
    
fig.savefig('slp.png')
Additional Information
If you do not like the LCC projection then you can change the following line:
fig, axs = plot.subplots(proj='cyl')
Output