Remove pip install --user suggestions

elastic-tube-1d/README.md

@@ -40,7 +40,7 @@ preCICE configuration (image generated using the [precice-config-visualizer](htt
 Both fluid and solid participant are supported in:
 
 - *C++*: example solvers using the intrinsic [C++ API of preCICE](https://precice.org/couple-your-code-api.html). The fluid solver also depends on LAPACK (e.g. on Ubuntu `sudo apt-get install liblapack-dev`)
-- *Python*: example solvers using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). Both solvers depend on `numpy`. The fluid solver additionally depends on the Python libraries `scipy matplotlib`. You can get these libraries from your system package manager or with `pip3 install --user <package>`.
+- *Python*: example solvers using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). The run script installs these automatically via pip in a virtual environment.
 - *Rust*: example solvers using the preCICE [Rust bindings](https://precice.org/installation-bindings-rust.html). They need `cargo` to be installed.
 
 ## Running the Simulation

flow-around-controlled-moving-cylinder/README.md

@@ -29,7 +29,7 @@ OpenFOAM is used for the `Fluid` participant. The spring-damper system is solved
 
 - *OpenFOAM*: To run this case, you need the preCICE [OpenFOAM Adapter](https://precice.org/adapter-openfoam-get.html). OpenFOAM is used to simulate the laminar flow around the cylinder with the solver `pimpleFoam`.
 - *FMI*: A solver using the [preCICE-FMI Runner](https://github.com/precice/fmi-runner) (requires at least v0.2). The Runner executes the FMU model `PIDcontroller.fmu` for computation. The provided run script (see below) builds this model if not already there. If you want to change the model parameters or simulation setup, have a look inside `fmi-settings.json` and `precice-settings.json` (see folder `controller-fmi`).
-- *Python*: A python script solving the spring damper system. It uses the preCICE [Python bindings](https://precice.org/installation-bindings-python.html) and depends on the Python library `numpy`. You can install `numpy` from your system package manager or with `pip3 install --user <package>`.
+- *Python*: A python script solving the spring damper system, using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). The run script installs the dependencies automatically via pip in a virtual environment.
 
 ## Running the simulation
 

oscillator-overlap/README.md

@@ -27,7 +27,7 @@ preCICE configuration (image generated using the [precice-config-visualizer](htt
 
 This tutorial is only available in Python. You need to have preCICE and the Python bindings installed on your system.
 
-- *Python*: An example solver using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). This solver also depends on the Python libraries `numpy`, which you can get from your system package manager or with `pip3 install --user <package>`.
+- *Python*: An example solver using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). The run script installs the dependencies automatically via pip in a virtual environment.
 
 ## Running the Simulation
 

oscillator/README.md

@@ -27,7 +27,7 @@ preCICE configuration (image generated using the [precice-config-visualizer](htt
 
 There are two different implementations:
 
-- *Python*: A solver using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). This solver also depends on the Python libraries `numpy`, which you can get from your system package manager or with `pip3 install --user <package>`. Using the option `-ts` allows you to pick the time stepping scheme being used. Available choices are Newmark beta, generalized alpha, explicit Runge Kutta 4, and implicit RadauIIA. The solver uses subcycling: Each participant performs 4 time steps in each time window. The data of these 4 substeps is then used by preCICE to create a third order B-spline interpolation (`waveform-degree="3"` in `precice-config.xml`).
+- *Python*: A solver using the preCICE [Python bindings](https://precice.org/installation-bindings-python.html). The run script installs the dependencies automatically via pip in a virtual environment. Using the option `-ts` allows you to pick the time stepping scheme being used. Available choices are Newmark beta, generalized alpha, explicit Runge Kutta 4, and implicit RadauIIA. The solver uses subcycling: Each participant performs 4 time steps in each time window. The data of these 4 substeps is then used by preCICE to create a third order B-spline interpolation (`waveform-degree="3"` in `precice-config.xml`).
 - *FMI*: A solver using the [preCICE-FMI runner](https://github.com/precice/fmi-runner) (requires at least v0.2). The Runner executes the FMU model `Oscillator.fmu` for computation. The provided run scripts (see below) build this model if not already there. For more information, please refer to [2].
 
 ## Running the simulation