### Docs

* 📝 Fix a typo in `docs/en/docs/virtual-environments.md`. PR [#12064](https://github.com/fastapi/fastapi/pull/12064) by [@aymenkrifa](https://github.com/aymenkrifa).
* 📝 Add docs about Environment Variables and Virtual Environments. PR [#12054](https://github.com/fastapi/fastapi/pull/12054) by [@tiangolo](https://github.com/tiangolo).

    /**
     * Get the value for the key 'virtual.host.headers'. <br>
     * The value is, e.g.  <br>
     * comment: Virtual Host: Host:fess.codelibs.org=fess
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getVirtualHostHeaders();

    /**
     * Get the value for the key 'virtual.host.headers' as {@link Integer}. <br>

    built with Visual Studio 2019 version 16.4 in order to take advantage of the
    new `/d2ReducedOptimizeHugeFunctions` compiler flag. To use these new
    packages, you must install "Microsoft Visual C++ Redistributable for Visual
    Studio 2015, 2017 and 2019", available from Microsoft's website
    [here](https://support.microsoft.com/help/2977003/the-latest-supported-visual-c-downloads).

- Feat: support [Azure shared disk](https://docs.microsoft.com/en-us/azure/virtual-machines/windows/disks-shared-enable), added a new field(`maxShares`) in azure disk storage class:
  
  - kind: StorageClass
  - apiVersion: storage.k8s.io/v1
  - metadata:
    - name: shared-disk

the result of Step 1 is computed during the next loop. This is // possible because each iteration only uses T[i] in Step 2 and then // discards it in Step 6. d := bLimbs[i] c1 := addMulVVW(T[i:n+i], aLimbs, d) // Step 6 is replaced by shifting the virtual window we operate // over: T of the algorithm is T[i:] for us. That means that T1 in // Step 2 (T mod 2^_W) is simply T[i]. k0 in Step 3 is our m0inv. Y := T[i] * m.m0inv // Step 4 and 5 add Y × m to T, which as mentioned above is stored // at T[i:]....

the result of Step 1 is computed during the next loop. This is // possible because each iteration only uses T[i] in Step 2 and then // discards it in Step 6. d := bLimbs[i] c1 := addMulVVW(T[i:n+i], aLimbs, d) // Step 6 is replaced by shifting the virtual window we operate // over: T of the algorithm is T[i:] for us. That means that T1 in // Step 2 (T mod 2^_W) is simply T[i]. k0 in Step 3 is our m0inv. Y := T[i] * m.m0inv // Step 4 and 5 add Y × m to T, which as mentioned above is stored // at T[i:]....

box-shadow($custom-select-box-shadow, $custom-select-focus-box-shadow);\n    } @else {\n      // Avoid using mixin so we can pass custom focus shadow properly\n      box-shadow: $custom-select-focus-box-shadow;\n    }\n\n    &::-ms-value {\n      // For visual consistency with other platforms/browsers,\n      // suppress the default white text on blue background highlight given to\n      // the selected option text when the (still closed) <select> receives focus\n      // in IE and (under certain conditions)...