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fix(overview): Add highlights for 'quick overview' with pretty_print.py
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docs/getting_started.md

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@@ -4,11 +4,10 @@ In this tutorial, we will guide you through the first steps to get started with
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The objective is to get a quick view of the capabilities of PowerAPI, by monitoring a process and getting a quick glimpse at the energy consumption.
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A few things are required before we start :
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- A compatible processor, you can see the compatible CPU architecture [here](./reference/sensors/hwpc-sensor.md#) and you can look on the following pages to find your CPU architecture :
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- For [Intel Processor](https://en.wikipedia.org/wiki/List_of_Intel_processors)
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- For [Intel Xeon Processor](https://en.wikipedia.org/wiki/List_of_Intel_Xeon_processors)
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- For [AMD Processor](https://en.wikipedia.org/wiki/Table_of_AMD_processors)
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- A compatible processor, you can see the compatible CPU architecture [here](./reference/sensors/hwpc-sensor.md#) and you can look on the following pages to find your CPU architecture :
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* For [Intel Processor](https://en.wikipedia.org/wiki/List_of_Intel_processors)
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* For [Intel Xeon Processor](https://en.wikipedia.org/wiki/List_of_Intel_Xeon_processors)
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* For [AMD Processor](https://en.wikipedia.org/wiki/Table_of_AMD_processors)
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- A python installation ready
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- Docker & Docker-Compose ready
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- Root access
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After the 2 minutes of monitoring, you will be able to see the result inside the **csv** directory.
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If you have trouble understanding the output, you can read the [Power Report documentation](./reference/reports/reports.md#power-Reports).
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Only in the context of this testing archive, after the monitoring, you can use the following command to get a pretty print of the result directly inside the terminal.
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!!! info "Quick results overview"
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Only in the context of this testing archive, after the monitoring, you can use the following command to get a pretty print of the result directly inside the terminal.
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```sh
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python3 pretty_print.py
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```
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```sh
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python3 pretty_print.py
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```

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