echo-baze¶

API wrapper for Bazefield, allowing for easy interaction with the system within Python.

Installation¶

This package can be installed using pip by following the latest instructions on the main README of the Performance Echo organization in GitHub.

Documentation¶

The documentation of this module is available at echo-baze.pages.dev. It uses the mkdocs tool alongside mkdocs-material and mkdocstrings to generate a static website with all the information needed to use the package. All relevant configuration files are present in mkdocs.yml and the documentation files are in the docs folder.

To see the documentation while developing the package, run the command below and open the browser at the address http://localhost:8111. You can change the port if needed.

mkdocs serve -a localhost:8111

When pushing changes to the repository, the documentation will be automatically updated in Cloudfare Pages due to the connection configured in Cloudflare. This way, you don't need to worry about updating the documentation when pushing changes to the repository. The process of configuring the connection in Cloudflare Pages is explained in this link, but there are details were considered:

The deployment uses Cloudflare credentials bruno.macedo@echoenergia.com.br and 1cY&l@EZTx6e9d.
Add the requirements-cloudflare.txt file to the repository, containing the dependencies needed to build the documentation
Change the build command to pip install -r requirements-cloudflare.txt && mkdocs build
To avoid Cloudflare trying to install the requirements from the requirements.txt file, you should add environment variable SKIP_DEPENDENCY_INSTALL with the value 1 to the build settings.
Add the values below in the extra field of the mkdocs.yml file to avoid the page being indexed by search engines like Google and Bing.

```yaml extra: meta: - name: robots content: noindex
Specify the Python version to be used in the Cloudflare Pages build settings by adding .python-version file to the root of the repository. Don't forget to remove any mentions to this file in .gitignore file.

Usage¶

From version 2.0 onwards there is only one top level class that should be imported to use the functionalities of this package. The class is called Baze and should be imported as shown below.

from echo_baze import Baze

If by any means you need to import the entire package, it is recommended to call it e_bz for consistency. Below is an example of how to do it.

import echo_baze as e_bz

Legacy¶

Legacy code is still available in the package, but it should not be used for any new code as it will be deprecated in the future. All legacy code is inside the legacy folder, which is a sub-package of the main package. Regardless of that, currently the legacy code can be used as if nothing has changed, as shown below using the connect_api_key method.

import echo_baze as e_bz
conn = e_bz.connect_api_key()

Testing¶

Pytest¶

Configuration¶

To tell VS Code to use pytest as the testing framework, its recommended that you add the following configuration to the settings.json file in the .vscode folder of your project.

{
    "python.testing.pytestEnabled": true,
    "python.testing.unittestEnabled": false,
    "python.testing.autoTestDiscoverOnSaveEnabled": false,
}

Running Tests¶

Several pre-defined tests are configured in the tests/auto folder using pytest. There ae severeal ways to run these tests, like:

Using the command line, running:
```
pytest
```
Using the command line to run a specific test:
```
pytest -k <test_name>
```
Through the Visual Studio Code testing module. To do so, just open the icon on the left side of the screen that looks like a test tube and run or debug the tests using pytest.
Using the _run_pytest.py script, which is a convenience script that you can just run. In it you should specify the test you want to run. This is the best way to debug tests if you need to.

Local installation¶

During development the package can be installed from the local repository using the command below.

uv pip install . --no-deps --reinstall --no-cache

Improvements¶

Improvements to the package are highly encouraged! As more people work here the better functionality we will have. Regardless of that, please follow the rules below when updating or adding new functionality:

Type Hints: For all methods and classes, use type hints to make it easier to understand what the input and output types are. This is extremely important for the user to understand how to use the package.

It's also extremely recommended that you use Pydantic's validate_call decorator to validate the input types, ensuring that the user is passing the right types to the methods. This will make it easier to debug as we catch the errors earlier in the process, avoiding unnecessary manual type checking and improving code robustness.

Docstrings: For every method or class, keep a well documented docstring. This is extremely important for the user to understand how to use the package.
Documentation: Add or update the documentation present in the docs folder, giving enough explanation and examples to make it very clear to understand how the methods work and how to use them. Also validate if the documentation is nicely formatted using mkdocs serve -a localhost:8111 before pushing changes.
Add/Edit Tests: Add or update automatic tests present in the tests folder in a way that they are able to identify if the functionality is working as expected.
Run Tests: Run all the tests present in the tests folder to make sure that the new functionality is working as expected and did not break any existing functionality.
: Version: Update de version number of the package in the file __version__.py
Changelog: Write in more details what has been changed in the CHANGELOG file following the existing pattern.
Commit: Commit your changes to GitHub.

TODO - Future work¶

Below are listed some ideas for future work in this package. They are not a priority, but would be nice to have.

Remove the folders below and all it's contents after transition to version 2.0 is complete and fully tested.
- legacy
Add import method to PointValuesSeries class.
Add MTTR/MTBF functionality to Kpis class.