Python Automation using Mouse and Keyboard, for the masses
pip install git+https://github.com/MihailCosmin/AutoMonkey
Main function to be used is "chain"
This will allow you to "chain" together most of the other functions of automonkey.
Which in turn will enable you to create sequences of mouse and/or keyboard actions in order to automate any given task.
A step can have this structure:
dict(
<action> = <target>, # action can be any of the automonkey functions, target on which the action will be performed
wait = 1, # wait is an optional parameter, which will wait for the given amount of seconds before executing the next step
skip = False, # if True, will skip this step
confidence = 0.9, # confidence is an optional parameter, Used only for actions on images. Confidence on locating the image.
v_offset = 0, # v_offset is an optional parameter, Used only for actions on images. Vertical offset from the center of the image.
h_offset = 0, # h_offset is an optional parameter, Used only for actions on images. Horizontal offset from the center of the image.
offset = 0, # offset is an optional parameter, Used only for actions on images. Offset from the center of the image.
monitor = 0, # monitor is an optional parameter, Used only for actions on images. Monitor on which to search for the image.
)
or
{
"<action>": "<target>", # action can be any of the automonkey functions, target on which the action will be performed
"wait": 1, # wait is an optional parameter, which will wait for the given amount of seconds before executing the next step
"skip": False, # if True, will skip this step
"confidence": 0.9, # confidence is an optional parameter, Used only for actions on images. Confidence on locating the image.
"v_offset": 0, # v_offset is an optional parameter, Used only for actions on images. Vertical offset from the center of the image.
"h_offset": 0, # h_offset is an optional parameter, Used only for actions on images. Horizontal offset from the center of the image.
"offset": 0, # offset is an optional parameter, Used only for actions on images. Offset from the center of the image.
"monitor": 0, # monitor is an optional parameter, Used only for actions on images. Monitor on which to search for the image.
}
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You can connect multiple mouse actions together by using the "chain" function. Just by doing this you can generally automate most of the tasks you would do on a daily basis.
There are 2 main ways to click, either by giving the coordinates of the position where to click or by giving the filename of the image you want to click on
1.1. Clicking by coordinates
1.1.1. In order to find the coordinates of a position on the screen you can use the "track_mouse" function or the PositionTracker class
from automonkey import track_mouse track_mouse()
from automonkey import PositionTracker PositionTracker()
1.2.1. Now that you have the coordinates of the position you want to click on, you can use the "chain" function to click on it
from automonkey import chain chain( dict(click=(780, 1175), wait=1), dict(click=(444, 194), wait=1), dict(click=(1892, 110), wait=1), debug=True )
1.2. Clicking by image
1.2.1. To click on an image you first need to make a screenshot of the area you want to click on and save it somewhere on your computer. For this you can use any screenshot tool you want, or you could use monkeyshot: https://github.com/MihailCosmin/monkeyshot For example you can make a screenshot of the Edge icon from your toolbar, then we can click on it by using the "chain" function.
1.2.2. Now that we have the image we want to click on, we can use the "chain" function to click on it
chain( dict(click="demo/edge_toolbar.jpg"), dict(click="demo/google_create_account", wait=1), dict(click="demo/personal_use", wait=1), debug=True )
1.3. All click actions:
* click * rightclick * leftclick * doubleclick * tripleclick * scrollup * scrolldown * scrollleft * scrollright
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You can also connect multiple keyboard actions together by using the "chain" function.
2.1. Write text - This doesn't work well with non-english character. For this you can use the "pastetext" function.
chain( dict(click="demo/notepad.jpg"), dict(write="Hello World!"), debug=True )
2.2. Paste text - This works well with non-english characters
chain( dict(click="demo/notepad.jpg"), dict(pastetext="Straße"), debug=True )
2.3. Key combinations
chain( dict(click="demo/notepad.jpg", wait=1), dict(write="Hello World!", wait=1), dict(keys2="ctrl+a", wait=1), dict(keys2="ctrl+x", wait=1), dict(keys2="alt+f4", wait=1), # close notepad debug=True )
2.4. All key actions:
* write * pastetext * keys * keys2 - best option overall for key combinations * keys3 * keys4 * copy * paste
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Wait actions: 3.1. Wait until an image appears on the screen This can used when you are waiting for a window to finish loading completely and you don't know exactly how long that would take.
chain( dict(click="demo/notepad.jpg"), dict(waituntil="demo/notepad_opened.jpg", wait=1), dict(write="Hello World!", wait=1), debug=True )
3.2. Wait while an image is on the screen
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App (window) actions:
4.1. Open an app
chain( dict(open_app="notepad++.exe", wait=1), dict(waituntil="demo/notepad_opened.jpg", wait=1), dict(write="Hello World!", wait=1), debug=True )
4.2. Close an app
chain( dict(open_app="notepad++.exe", wait=1), dict(write="Hello World!", wait=1), dict(close="Notepad", wait=1), debug=True )
4.3. Minimize an app
chain( dict(open_app="notepad++.exe", wait=1), dict(write="Hello World!", wait=1), dict(minimize="Notepad", wait=1), debug=True )
4.4. Maximize an app
chain( dict(open_app="notepad++.exe", wait=1), dict(write="Hello World!", wait=1), dict(maximize="Notepad", wait=1), debug=True )
4.5. Restore an app
chain( dict(open_app="notepad++.exe", wait=1), dict(write="Hello World!", wait=1), dict(minimize="Notepad", wait=1), dict(restore="Notepad", wait=1), debug=True )
4.6. All app actions:
* open_app * close * startfile * focus * minimize * maximize * restore * msoffice_replace * copy_from * copy_from_to
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Image actions
5.1 count_img. With this function you can count how many times one image appears on the screen.
chain( dict(count_img="demo/M.jpg", wait=1), # The result will be copied to the clipboard dict(open_app="notepad++.exe", wait=1), dict(paste="", wait=1), # with paste we can paste the text from the clipboard debug=True )
5.2. get_text_from_region
chain( dict(get_text_from_region=((136, 121), (189, 140)), wait=1), # The text will be copied to the clipboard dict(open_app="notepad++.exe", wait=1), dict(paste="", wait=1), # with paste we can paste the text from the clipboard debug=True )