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mwydmuch committed Aug 19, 2024
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## Python quick start

#### At the moment ViZDoom does not work with numpy 2.0. Using ViZDoom with numpy 2.0 results in a silent bug - all the state buffers containing all data. At the moment, please use ViZDoom with numpy 1.26.
#### Versions 1.2.3 and below does not work correctly with numpy 2.0+. Please upgrade ViZDoom to the newest version or downgrade numpy to the last 1.21+ version.

### Linux
To install the latest release of ViZDoom, just run:
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### macOS
To install the latest release of ViZDoom, just run (it may take a few minutes as it will build ViZDoom from source on M1/M2 chips):
To install the latest release of ViZDoom, just run:
```sh
brew install cmake boost sdl2 openal-soft
pip install vizdoom
```
Both Intel and Apple Silicon CPUs are supported.
Pre-build wheels are available for Intel macOS 12.0+ and Apple Silicon macOS 14.0+.

If Python wheel is not available for your platform (Python version <3.8, older macOS version), pip will try to install (build) ViZDoom from the source.
In this case, install the required dependencies using Homebrew:
```sh
brew install cmake boost sdl2
```
We recommend using at least macOS High Sierra 10.13+ with Python 3.8+.
On Apple Silicon (M1, M2, and M3), make sure you are using Python/Pip for Apple Silicon.

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- [Python](https://github.com/Farama-Foundation/ViZDoom/blob/master/examples/python) (contain learning examples implemented in PyTorch, TensorFlow, and Theano)
- [C++](https://github.com/Farama-Foundation/ViZDoom/blob/master/examples/c%2B%2B)

Python examples are currently the richest, so we recommend looking at them, even if you plan to use C++.
Python examples are currently the richest, so we recommend looking at them, even if you plan to use C++.
The API is almost identical between the languages, with the only difference being that Python uses snake_case and C++ camelCase for methods and functions.


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