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README.md

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+# Pylint
+We utilized the Pylint tool to conduct a comprehensive code cleanup process aimed at achieving a more refined, robust, and readable Python codebase. This effort was directed at minimizing errors and streamlining long-term maintenance.
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+Through the analyses performed using Pylint, the predominant issues identified were related to indentation errors, extraneous whitespace, lack of module and function-level documentation, overlapping variable names used both locally and globally, as well as instances of excessively long lines. 
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+Additionally, in order to streamline the analysis process and focus on the most critical aspects, we made a deliberate choice to disable specific pylint error flags. Notably, we disabled 'import-error' flags associated with module imports and errors related to an excessive number of local variables flagged under 'too-many-locals'.
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+This approach allowed us to concentrate on addressing the most crucial code quality aspects while improving readability, maintainability, and adherence to coding standards within the project.
 
 # Grafana
 We used the Grafana tool to be able to graphically display some values ​​obtained from Prometheus metrics by performing queries.