Package with utilities and functional extensions for Selenium webdriver Python language bindings
Project description
SeleniumXP utilities for Python
Package with utilities and functional extensions for Selenium webdriver Python language bindings
Features
The package consist of various helpers and extensions to the Selenium webdriver:
- module for session handling especially a custom factory function to initialize a webdriver object
- module with additional methods for the webdriver class
- module with convenience functions for locators
- module with additional methods for the webelement class
- an extended event-firing webdriver and an extended listener abstract base class
- a sample event listener implementation based on the extended abstract base class
Different from other packages extending the Selenium webdriver class does not work with wrapping the original webdriver but providing a mixin class or alternatively directly setting additional methods via 'setattr' in the original webdriver class. This is done and controlled via a pretty versatile custom factory function initializing the webdriver.
The webelement extension are done via setattr only. Implementing a mixin class would require to modify webdriver methods to return the new class with the mixin. So benefit of the settattr approach is that extending the webelement class is independend from changes to the webdriver class.
Note: as I am coming from camel case notation I was struggling a little bit with the Python naming conventions. However, for publishing I tried to increase compliance with Python naming conventions and added snake case method stubs (at least for most important subroutines) as a compromise.
Development
To set up hatch and pre-commit for the first time:
- install hatch globally, e.g. with pipx, i.e.
pipx install hatch, - make sure
pre-commitis installed globally, e.g. withpipx install pre-commit.
A special feature that makes hatch very different from other familiar tools is that you almost never
activate, or enter, an environment. Instead, you use hatch run env_name:command and the default environment
is assumed for a command if there is no colon found. Thus you must always define your environment in a declarative
way and hatch makes sure that the environment reflects your declaration by updating it whenever you issue
a hatch run .... This helps with reproducability and avoids forgetting to specify dependencies since the
hatch workflow is to specify everything directly in pyproject.toml. Only in rare cases, you
will use hatch shell to enter the default environment, which is similar to what you may know from other tools.
To get you started, use hatch run test:cov or hatch run test:no-cov to run the unitest with or without coverage reports,
respectively. Use hatch run lint:all to run all kinds of typing and linting checks. Try to automatically fix linting
problems with hatch run lint:fix and use hatch run docs:serve to build and serve your documentation.
You can also easily define your own environments and commands. Check out the environment setup of hatch
in pyproject.toml for more commands as well as the package, build and tool configuration.
To support versioning and changelog generation please refer to the toolchain selected during package
generation (see also pyproject.toml). If not deselected, the toolchain includes a pre-commit hook
for linting commit messages to ensure commit messages are compliant with the conventional commit format and
support an automated changelog generation.
Credits
This package was created with The Hatchlor Enhanced project template. This template is based on The Hatchlor but was substantially improved.
Project details
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