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Information that might be useful while implementing or maintaining a sequence type, based on things I discovered while trying to implement bytearray.

# Sequence Types

Jython provides some apparatus to support the implementation of sequence types.

## Helper class SequenceIndexDelegate

The range of things that can appear in Python as the "index" of a sequence type is a lot broader than in most languages. Consider

```>>> a=list(range(10))
>>> a
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> del a[2:7:3]
>>> a
[0, 1, 3, 4, 6, 7, 8, 9]
>>> b=list(range(20))
>>> b[30:-15:-3]
[19, 16, 13, 10, 7]
>>> b[30:-15:-3] = "abcde"
>>> b
[0, 1, 2, 3, 4, 5, 6, 'e', 8, 9, 'd', 11, 12, 'c', 14, 15, 'b', 17, 18, 'a']```

If you were the implementer of list, your implementation of __delitem__(self,key) would have to support not only a simple integer key, but a slice representing 2:7:3. Similarly, __getitem__ must synthesise a return list picked according to the slice, and __setitem__ must be able to assign these elements from a sequence. All this while observing the rules of extended slicing.

Jython provides a useful abstract class org.python.core.SequenceIndexDelegate that recognises whether the key was a simple integer or a slice, deals with illegal types and range checks, and in the case of a slice, converts it into indexes you can use safely in a for loop where you do the actual operation. To connect these goodies into your implementation, create a concrete inner class extending SequenceIndexDelegate by overriding the required 8 methods with call-back methods into your own implementation:

```   1     public abstract int len();
2     public abstract PyObject getItem(int idx);
3     public abstract void setItem(int idx, PyObject value);
4     public abstract void delItem(int idx);
5     public abstract PyObject getSlice(int start, int stop, int step);
6     public abstract void setSlice(int start, int stop, int step, PyObject value);
7     public abstract void delItems(int start, int stop);
8     public abstract String getTypeName();
```

Your implementations of the standard API, such as __setitem__, can delegate almost immediately to corresponding methods of this inner class, with all their arguments uninspected. The inner class will then call the right methods from these 8 to handle the actual work. There's still plenty for your code to deal with, but you can do it knowing the arguments are of well-defined type and have safe values.

## Base class PySequence

Jython provides further help in the form of org.python.core.PySequence, with the intention that an implementer of sequence types extend the class. This has been used as a base for Python types list and array.array, and soon bytearray.

PySequence uses the delegaion technique discussed in the previous section, however it cannot do all the work. Although it makes the delgate concrete, the implementations of most of the 8 callback methods themselves depend on abstract methods within PySequence. Here is an extract:

```   1     protected final SequenceIndexDelegate delegator = new SequenceIndexDelegate() {
2
3 ...
4         @Override
5         public void setItem(int idx, PyObject value) {
6             pyset(idx, value);
7         }
8
9         @Override
10         public void setSlice(int start, int stop, int step, PyObject value) {
11             setslice(start, stop, step, value);
12         }
13 ...
14     };
```

The methods pyset and setSlice referenced here are amongst 7 methods that extensions implementing sequence types are expected to override:

```   1     // These methods must be defined for any sequence
2     protected abstract PyObject pyget(int index);
3     protected abstract PyObject getslice(int start, int stop, int step);
4     protected abstract PyObject repeat(int count);
5
6     // These methods only apply to mutable sequences
7     protected void pyset(int index, PyObject value) {
8         throw Py.TypeError("can't assign to immutable object");
9     }
10     protected void setslice(int start, int stop, int step, PyObject value) {
11         throw Py.TypeError(String.format("'%s' object does not support item assignment",
12                                          getType().fastGetName()));
13     }
14     protected void del(int i) {
15         throw Py.TypeError(String.format("'%s' object does not support item deletion",
16                                          getType().fastGetName()));
17     }
18     protected void delRange(int start, int stop) {
19         throw Py.TypeError(String.format("'%s' object does not support item deletion",
20                                          getType().fastGetName()));
21     }
```

You can see that read-access methods are abstract, but methods that change content are provided with implementations that will throw an error if not overriden. These are ready for use by immutable sequence types.

PySequence also provides actual implementations for methods __setitem__ in terms of the delegate:

```   1     // Java API
2     @Override
3     public void __setitem__(int index, PyObject value) {
4         delegator.checkIdxAndSetItem(index, value);
5     }
6     @Override
7     public void __setitem__(PyObject index, PyObject value) {
8         seq___setitem__(index, value);
9     }
10     // Python API
11     final void seq___setitem__(PyObject index, PyObject value) {
12         delegator.checkIdxAndSetItem(index, value);
13     }
```

Although this last method PySequence.seq__setitem__(PyObject, PyObject) is essentially the entrypoint we need from Python, it cannot be exposed directly as (say) list.__setitem(self,key,value): it has the wrong name and is not directly in the implementing class. So in PyList we find:

```   1     @ExposedMethod(doc = BuiltinDocs.list___setitem___doc)
2     final synchronized void list___setitem__(PyObject o, PyObject def) {
3         seq___setitem__(o, def);
4     }
```

There is no need, however, to wrap the Java API method __setitem__(int, PyObject) any further. The inherited version is just fine.

When Python encounters

```b=list(range(20))
b[30:-15:-3] = "abcde"```

it will invoke something like

`b.list___setitem__(new PySlice(30,-25,-3), new PyString("abcde"))`

The sequence of method calls will then be like:

```b.list___setitem__(PySlice(30,-25,-3), PyString("abcde")) ->
b.seq___setitem__(PySlice(30,-25,-3), PyString("abcde")) ->
b.delegator.checkIdxAndSetItem(PySlice(30,-25,-3), PyString("abcde")) ->
b.delegator.checkIdxAndSetSlice(PySlice(30,-25,-3), PyString("abcde")) ->
b.delegator.setSlice(19, -1, -3, PyString("abcde")) ->
b.setslice(19, -1, -3, PyString("abcde"))```

Notice that the slice, ostensibly a bad fit for a length 20 sequence, was transformed into three integers that can validly index the sequence as:

```   1         for (int i=19; i>-1; i+=-3)
2                 b.myList.get(i);
```

which is both the correct meaning for the slice and runs no risk of access out of bounds. In this example the step of the slice was negative, and so the loop counts down. The final value of the loop is not used for access.

The case step==1 means a contiguous slice [start:stop]. Implementations usually deal with this as a special case either because it has different semantics (e.g. in __setitem__ or __delitem___), or because contiguous elements can be processed with an efficient block operation. A helper function PySequence.sliceLength(start, stop, step) exists to make the processing loop easier to get right. A typical idiom is:

```   1     if (step == 1) {
2         // Do something efficient with block start...stop-1
3     } else {
4         int n = sliceLength(start, stop, step);
5         for (int i = start, j = 0; j < n; i += step, j++) {
6             // Perform jth operation with element i
7         }
8     }
```

ImplementSequenceType (last edited 2012-02-24 20:59:16 by JeffAllen)