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1 | 1 | # Assumptions
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2 | 2 |
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3 |
| -## Hardware environments |
| 3 | +## Hardware and software environments |
4 | 4 |
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| 5 | +No assumptions on a specific hardware environment are made. It must be possible |
| 6 | +to create an array library adhering to this standard that runs (efficiently) on |
| 7 | +a variety of different hardware: CPUs with different architectures, GPUs, |
| 8 | +distributed systems and TPUs and other emerging accelerators. |
5 | 9 |
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| 10 | +The same applies to software environments: it must be possible to create an |
| 11 | +array library adhering to this standard that runs efficiently independent of |
| 12 | +what compilers, build-time or run-time execution environment, or distribution |
| 13 | +and install method is employed. Parallel execution, JIT compilation, and |
| 14 | +delayed (lazy) evaluation must all be possible. |
6 | 15 |
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7 |
| -## Software environments |
8 |
| - |
| 16 | +The variety of hardware and software environments puts _constraints_ on choices |
| 17 | +made in the API standard. For example, JIT compilers may require output dtypes |
| 18 | +of functions to be predictable from input dtypes only rather than input values. |
9 | 19 |
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10 | 20 |
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11 | 21 | ## Dependencies
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12 | 22 |
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| 23 | +The only dependency that's assumed in this standard is that on Python itself. |
| 24 | +Python >= 3.8 is assumed, motivated by the use of positional-only parameters |
| 25 | +(see [function and method signatures](API_specification/function_and_method_signatures.md)). |
| 26 | + |
| 27 | +Importantly, array libraries are not assumed to be aware of each other, or of |
| 28 | +a common array-specific layer. The [use cases](use_cases.md) do not require |
| 29 | +such a dependency, and building and evolving an array library is easier without |
| 30 | +such a coupling. Facilitation support of multiple array types in downstream |
| 31 | +libraries is an important use case however, the assumed dependency structure |
| 32 | +for that is: |
| 33 | + |
| 34 | + |
| 35 | + |
| 36 | +Array libraries may know how to interoperate with each other, for example by |
| 37 | +constructing their own array type from that of another library or by shared |
| 38 | +memory use of an array (see [Data interchange mechanisms](design_topics/data_interchange.md)). |
| 39 | +This can be done without a dependency though - only adherence to a protocol is |
| 40 | +enough. |
| 41 | + |
| 42 | +Array-consuming libraries will have to depend on one or more array libraries. |
| 43 | +That could be a "soft dependency" though, meaning retrieving an array library |
| 44 | +namespace from array instances that are passed in, but not explicitly doing |
| 45 | +`import arraylib_name`. |
| 46 | + |
| 47 | + |
| 48 | +## Backwards compatibility |
| 49 | + |
| 50 | +The assumption made during creation of this standard is that libraries are |
| 51 | +constrained by backwards compatibility guarantees to their users, and are |
| 52 | +likely unwilling to make significant backwards-incompatible changes for the |
| 53 | +purpose of conforming to this standard. Therefore it is assumed that the |
| 54 | +standard will be made available in a new namespace within each library, or the |
| 55 | +library will provide a way to retrieve a module or module-like object that |
| 56 | +adheres to this standard. See [How to adopt this API](purpose_and_scope.html#how-to-adopt-this-api) |
| 57 | +for more details. |
| 58 | + |
| 59 | + |
| 60 | +## Production code & interactive use |
13 | 61 |
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| 62 | +It is assumed that the primary use case is writing production code, for example |
| 63 | +in array-consuming libraries. As a consequence, making it easy to ensure that |
| 64 | +code is written as intended and has unambiguous semantics is preferred - and |
| 65 | +clear exceptions must be raised otherwise. |
14 | 66 |
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15 |
| -## Interactive use & production code |
| 67 | +It is also assumed that this does not significantly detract from the |
| 68 | +interactive user experience. However, in case existing libraries differ in |
| 69 | +behavior, the more strict version of that behavior is typically preferred. A |
| 70 | +good example is array inputs to functions - while NumPy accepts lists, tuples, |
| 71 | +generators, and anything else that could be turned into an array, most other |
| 72 | +libraries only accept their own array types. This standard follows the latter choice. |
| 73 | +It is likely always possible to put a thin "interactive use convenience layer" |
| 74 | +on top of a more strict behavior. |
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