Skip to main content

Python Automation using Mouse and Keyboard, for the masses

Project description

Donate HitCount build Code Climate

AutoMonkey

AutoMonkey

Python Automation using Mouse and Keyboard, for the masses

Installation

  1. From pypi:
pip install AutoMonkey
  1. From github:
pip install git+https://github.com/MihailCosmin/AutoMonkey

Dependencies

Automonkey is based on:

Other dependencies:

  • PyScreeze
  • pyperclip
  • clipboard
  • keyboard
  • screeninfo
  • pywin32
  • pillow
  • opencv-python
  • numpy
  • pytesseract

Usage

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.
}
  1. 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()
    
    track_mouse
        from automonkey import PositionTracker
        tracker = PositionTracker()
        tracker.start()
    
    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  
        )
    
    click

    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.

    edge_toolbar

    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
        )
    
    click_image

    1.3. All mouse actions:

     * click
     * rightclick
     * leftclick
     * doubleclick
     * tripleclick
     * scrollup
     * scrolldown
     * scrollleft
     * scrollright
    
  2. 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
        )
    
    write

    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
        )
    
    keys

    2.4. All key actions:

     * write
     * pastetext
     * keys
     * keys2 - best option overall for key combinations
     * keys3
     * keys4
     * copy
     * paste
    
  3. 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

  4. 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
    
  5. 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
        )
    

Roadmap

  1. Check if possible to add pyautowin functionality

Frequently Asked Questions:

  1. I made an image but it doesn't click on it.

    A: Make sure you have not changed resolution of your screen or the theme (dark/light) of the window.

  2. Keys combination using "keys" function doesn't work.

    A: Try other keys functions. Preferably "keys2". Other options "keys3", "keys4".

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

AutoMonkey-0.2.1.tar.gz (24.3 kB view details)

Uploaded Source

File details

Details for the file AutoMonkey-0.2.1.tar.gz.

File metadata

  • Download URL: AutoMonkey-0.2.1.tar.gz
  • Upload date:
  • Size: 24.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for AutoMonkey-0.2.1.tar.gz
Algorithm Hash digest
SHA256 57ae48482d3945f1727f96daac77fad28deca7b0f8ba003992a6c19e7d32cdea
MD5 c72ff7d77902a24e994474fe534ea1df
BLAKE2b-256 460c46e9492e6792afc9b4e2f5ef3bc1b8f38f70fba16d95f7d96d4599caa7c8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page