#!/usr/bin/env python
# coding: utf-8

# # Adding plugins to your computation stack
# 
# A plugin is a tool which can be link to a QPU to make the computation stack more powerful. A plugin is used to pre-process batches sended to a QPU and/or post-process results of a QPU.
# When a Plugin is linked to a QPU, a new QPU is created. For instance, the following code defines a new QPU where each batch sended to this object is pre-processed and each result is post-processed by the plugin "*Plugin()*":
# 
# > `my_qpu = Plugin() | QPU()`
# 
# The QLM provides classes to define your own plugin, an example of custom plugin is presented in [**this tutorial**](plugins.ipynb).
# 
# Moreover, some plugins are already implemented in the QLM:
#  - [**Quameleon plugin**](./emulating_custom_hardware_specs.ipynb): this plugin is used to simulate hardware specs for any QPU
#  - the [**observable splitter plugin**](./observable_splitter.ipynb) can be used to tranform observable sampling into computational basis sampling
#  - the [**circuit inliner**](./circuit_inliner.ipynb) can be used to inline the content of a circuit in its main (in case some other Plugin needs to access the inlined circuit)
# 
# Finally, [**this**](./plugins.ipynb) notebook shows how to write your own QLM compatible plugin.

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