Advanced concepts

Saving run results of flow

You can save an html log of the run and the flow run results to tagui/src/tagui_report.csv with the -report option (shortcut -r).

tagui my_flow.tag -report

The CSV file will show one line for each run, when it started, how long it took to complete, any error message during run, the link to the log file for that run, and the user’s workgroup\userid.

Handling exceptions and errors

There are 3 ways to handle exceptions in TagUI when things do not go as planned.

The first way is local error handling. This means using if conditions to check specifically for certain scenarios and handling the scenarios accordingly. For example, check if some UI element is missing, then do xyz steps. Using this way, a workflow can have multiple fine-grain exception handling.

The second way is workflow error handling. A workflow can be chained as follows to handle error or success accordingly. The workflow error.tag will run only if flow.tag errors out. The workflow success.tag will run only if flow.tag runs successfully. TagUI will automatically throw error when it detects an expected UI element missing (and autosave screenshot) or some other unknown errors.

Windows example from the command prompt:

call tagui flow.tag || tagui error.tag
call tagui flow.tag && tagui success.tag

macOS / Linux example from the terminal:

tagui flow.tag || tagui error.tag
tagui flow.tag && tagui success.tag

The third way is global error handling. Configuration can be done for TagUI such that after every run, special handling is done to send data or files generated from the report option to some target folder or API endpoint for error / success handling. For example, syncing all automation runs to central storage for auditing purpose. The special handling applies to all TagUI flows that are run.

Datatables

Datatables are csv files which can be used to run your flows multiple times with different inputs.

A datatable (trade_data.csv) could look like this:

# trade username password pair size direction
1 Trade USDSGD test_account 12345678 USDSGD 10000 BUY
2 Trade USDSGD test_account 12345678 USDJPY 1000 SELL
3 Trade EURUSD test_account 12345678 EURUSD 100000 BUY

To use it, you run your flow with tagui my_flow.tag trade_data.csv. TagUI will run my_flow.tag once for each row in the datatable (except for the header).

Within the flow, TagUI can use the variables trade, username, password, etc as if they were in the local object repository and the values will be from that run’s row.

To know which iteration your flow is in you can use the iteration variable:

echo current iteration: `iteration`
if iteration equals to 1
  // go to login URL and do the login steps
  www.xero.com

// do rest of the steps for every iteration

Object repositories

Object repositories are optional csv files which can store variables for use in flows. They help to separate your flows from your personal data (like login information for web flows), and allow you to share common information between multiple flows for easy updating.

Each flow has a local object repository and all flows share the global object repository. The local object repository is the tagui_local.csv in the same folder as the flow. The global object repository is the tagui_global.csv in the tagui/src/ folder.

An object repository could look like this:

object definition
email user-email-textbox
create account btn btn–green btn-xl signup-btn

Within the flow, TagUI can use the objects email, create account as variables and they will be replaced directly by the definitions before it is run. Local definitions take precedence over global definitions.

If user-email-textbox was the identifier for some web text input, then you could use the following in your flow:

type `email` as my_email@email.com

Running flows within a flow

A flow can run another flow, like this:

tagui login_crm.tag

Variables in the parent flow are accessible in the child flow and vice versa.

Turbo mode to run 10X faster

To run TagUI with turbo option (use with caution):

tagui flow.tag -turbo

or

tagui flow.tag -t

Most websites and desktop apps are not designed for the super-human speed user. If your RPA runs at a speed beyond what those websites are designed and tested for, you are surely going to run into problems with some apps. Problems could be fields and data not filling up properly, not triggering expected validations, form submissions with missing data, account being blocked etc.

And the problems might happen randomly, including working on your PC but not working on another PC due to difference in CPU speed. Because of this, using turbo mode option is not recommended. You may save some cheap computer time, but if something is broken or does not work, you may end up spending expensive human time (your time) to troubleshoot or fix.

However, this is very useful for some users for some specific scenarios. For eg, data collection from apps, data entry in web applications that can handle super-human speed reliably, as part of a chatbot doing backend RPA for user, for fast and rapid prototyping, perhaps taking part in RPA competitions and hackathons etc. Thoroughly test for your use case before using!

Visual automation tricks

For many steps, you can end the step with using ocr or using OCR to tell TagUI to interact on some UI element on the screen using OCR (optical character recognition). See the examples below. Steps which this can be done: click, rclick, dclick, hover, type, select, read, snap, exist(), present().

click Submit using ocr

if exist('Special Offer using ocr')
  click Add To Cart using OCR

// various usage combinations for select step
select Dress Color using OCR as Dark Blue using OCR
select dress_color.png as Bright Pink using ocr
select Dress Color using OCR as dark_black.png
select dress_color.png as bright_white.png

If you make the background of a UI element in a .png file 100% transparent using an image editor, TagUI will be able to target the element regardless of its background.

Conversely, you can also remove the foreground content near some anchor element like a frame, to allow you to OCR varying content in the empty area using the read step.

Writing Python within flows

You can write Python code in TagUI flows. Python needs to be installed separately.

The py step can be used to run commands in Python (TagUI will call python on the command line). You can pass string values back to TagUI with print(). The stdout will be stored in the py_result variable in TagUI.

py a=1
py b=2
py c=a+b
py print(c)
echo `py_result`

You can also use py begin and py finish before and after a Python code block:

py begin
a=1
b=2
c=a+b
print(c)
py finish
echo `py_result`

You can pass a variable to Python like this:

phone = 1234567
py_step('phone = ' + phone)
py print(phone)
echo `py_result`

name = 'Donald'
py_step('name = "' + name + '"')
py print(name)
echo `py_result`

To pass and return more complex data, for example multiple variables, you can use JavaScript and Python JSON libraries to send and receive back JSON strings. See an example here of passing 2 variables, doing some processing, and returning 2 variables.

Create log files for debugging

To do advanced debugging, you can create log files when running flows by creating an empty tagui_logging file in tagui/src/.

  • my_flow.log stores step-by-step output of the execution.
  • my_flow.js is the generated JavaScript file that was run.
  • my_flow.raw is the expanded flow after parsing modules.