robocorp-tasks 2.1.0

The automation framework for Python

robocorp-tasks

robocorp-tasks is a Python framework designed to simplify the development of Python automations.

Note: The current version (2.0.0) is now in beta. Semantic versioning is used in the project.

Why

While Python is widely used in the automation world, many solutions end up being ad-hoc, making it difficult to navigate different projects and keep up with the features required for analysing the results of such automations afterwards.

How

robocorp-tasks provides a runner for running tasks that offers logging out of the box for Python code (showing method calls, arguments, assigns, etc) by leveraging robocorp-log, and managing the lifecycle for running such tasks.

Installation

To install robocorp-tasks, use the following command:

pip install robocorp-tasks

Usage

Replace the code in your __main__ with a method that has the name of your task (which should not have parameters) and decorate it with the @task decorator, like this:

i.e.:

from robocorp.tasks import task

@task
def my_task():
    ...
    

2. Call your task using the command line below, customizing the directory and task name as needed:

python -m robocorp.tasks run <path/to/file.py or directory> -t <task_name>

Note: if you have only one defined task in your target, the -t <task_name> option is not needed.

Note: the task name is the name of the method decorated with @task.

Note: if a directory is given, only files named *task*.py will be used for collection.

Note: in the current version only one task can be run per invocation. If more than one task is found an error will be given and no tasks will be run.

3. View the log results in output/log.html.

Auto logging customization

Following the initial steps outlined above should be sufficient to get comprehensive logging for all user code executed. However, note that it won't log calls from libraries by default, as it may be difficult to separate the libraries that are important for a project from those that are just noise.

To add custom logging for libraries like rpaframework, Selenium and others, create a pyproject.toml file and place it in the root of your project. Then, customize the [tool.robocorp.log] section to add log_filter_rules.

log_filter_rules is a list of dictionaries where entries may be added to specify how to handle logging for a particular module.

There are three different logging configurations that may be applied:

• exclude: skips logging a module.
• full_log (default for user code): logs a module with full information, such as method calls, arguments, yields, local assigns, and more.
• log_on_project_call (default for library code -- since 2.0): logs only method calls, arguments, return values and exceptions, but only when a library method is called from user code. This configuration is meant to be used for library logging.

Note that the default for the library code may be configured through default_library_filter_kind.

Example of pyproject.toml where the rpaframework and selenium libraries are configured to be logged and all other libraries are excluded by default:

[tool.robocorp.log]

log_filter_rules = [
    {name = "RPA", kind = "log_on_project_call"},
    {name = "selenium", kind = "log_on_project_call"},
    {name = "SeleniumLibrary", kind = "log_on_project_call"},
]

default_library_filter_kind = "exclude"

Note that when specifying a module name to match in log_filter_rules, the name may either match exactly or the module name must start with the name followed by a dot.

This means that, for example, RPA would match RPA.Browser, but not RPAmodule nor another.RPA.

Also, as of robocorp-tasks 2.0, it's also possible to use fnmatch style names.

i.e.:

[tool.robocorp.log]

log_filter_rules = [
    {name = "proj.*", kind = "full_log"},
    {name = "proj[AB]", kind = "full_log"},
]

Note that the order of the rules is important as rules which appear first are matched before the ones that appear afterwards.

Log output customization

By default, the log output will be saved to an output directory, where each file can be up to 1MB and up to 5 files are kept before old ones are deleted. When the run finishes, a log.html file will be created in the output directory containing the log viewer with the log contents embedded.

However, you can customize the log output by changing the output directory, maximum number of log files to keep, and maximum size of each output file. You can do this through the command line by passing the appropriate arguments when running python -m robocorp.tasks run.

For example, to change the output directory to my_output, run:

python -m robocorp.tasks run path/to/tasks.py -o my_output

You can also set the maximum number of output files to keep by passing --max-log-files followed by a number. For example, to keep up to 10 log files, run:

python -m robocorp.tasks run path/to/tasks.py --max-log-files 10

Finally, you can set the maximum size of each output file by passing --max-log-file-size followed by a size in megabytes (e.g.: 2MB or 1000kb).

For example, to set the maximum size of each output file to 500kb, run:

python -m robocorp.tasks run path/to/tasks.py --max-log-file-size 500kb

License: Apache 2.0

Copyright: Robocorp Technologies, Inc.