def automation_example(rows, cols, value):
"""copies value to a range of rows x cols below the calling cell"""
# Get the address of the calling cell using xlfCaller
caller = pyxll.xlfCaller()
address = caller.address
# The update is done asynchronously so as not to block Excel by
# updating the worksheet from a worksheet function
def update_func():
# Get the Excel.Application COM object
xl = xl_app()
# Get an Excel.Range object from the XLCell instance
range = caller.to_range(com_package="win32com")
# get the cell below and expand it to rows x cols
range = xl.Range(range.Resize(2, 1), range.Resize(rows + 1, cols))
# and set the range's value
range.Value = value
# kick off the asynchronous call the update function
pyxll.async_call(update_func)
return address
def ml_zoo_predict(tree, features):
# Convert the features dictionary into a DataFrame with a single row
features = pd.DataFrame([features], columns=tree._feature_names)
# Get the prediction from the model
prediction = tree.predict(features)[0]
# Update the image in Excel
async_call(show_image_in_excel, prediction)
return _zoo_classifications[prediction]
def ml_zoo_predict(tree, features):
# Convert the features dictionary into a DataFrame with a single row
features = pd.DataFrame([features], columns=tree._feature_names)
# Get the prediction from the model
prediction = tree.predict(features)[0]
# Update the image in Excel
async_call(show_image_in_excel, prediction)
return _zoo_classifications[prediction]
def create_temporary_file(suffix=None):
"""Create a named temporary file that is deleted automatically."""
# Rather than delete the file when it's closed we delete it when the
# windows message loop next runs. This gives Excel enough time to
# load the image before the file disappears.
file = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
def try_delete(filename):
try:
os.unlink(filename)
except PermissionError:
# retry if Excel is still accessing it
async_call(os.unlink, filename)
# Make sure the file gets deleted after the function is complete
async_call(try_delete, file.name)
return file
def automation_example(rows, cols, value):
"""copies value to a range of rows x cols below the calling cell"""
# get the address of the calling cell using xlfCaller
caller = pyxll.xlfCaller()
address = caller.address
# the update is done asynchronously so as not to block some
# versions of Excel by updating the worksheet from a worksheet function
def update_func():
xl = xl_app()
range = xl.Range(address)
# get the cell below and expand it to rows x cols
range = xl.Range(range.Resize(2, 1), range.Resize(rows+1, cols))
# and set the range's value
range.Value = value
# kick off the asynchronous call the update function
pyxll.async_call(update_func)
return address
elif x.ndim == 2:
range = xl.Range(range.Resize(2, 1),
range.Resize(x.shape[0]+1, x.shape[1]))
y = x
else:
raise ValueError('Array rank must be 1 or 2.')
range.Value = y
except Exception, ex:
logger.info(ex)
#
#=======================================================================
# kick off the asynchronous call to the update function
pyxll.async_call(update_func, arr)
#==============================================================================
def draw_table(tbl):
"""
Renders a table = list of rows = list of lists.
We assume the CALLER did the proper type conversions!!!
(We can handle strings, int32, and float64 colums.)
"""
if not isinstance(tbl, list):
raise TypeError('List expected.')
def try_delete(filename):
try:
os.unlink(filename)
except PermissionError:
# retry if Excel is still accessing it
async_call(os.unlink, filename)