/*
 * transforming Datums to Python objects and vice versa
 *
 * src/pl/plpython/plpy_typeio.c
 */

#include "postgres.h"

#include "access/htup_details.h"
#include "access/transam.h"
#include "catalog/pg_type.h"
#include "funcapi.h"
#include "mb/pg_wchar.h"
#include "parser/parse_type.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/fmgroids.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"
#include "utils/numeric.h"
#include "utils/syscache.h"
#include "utils/typcache.h"

#include "plpython.h"

#include "plpy_typeio.h"

#include "plpy_elog.h"
#include "plpy_main.h"


/* I/O function caching */
static void PLy_input_datum_func2(PLyDatumToOb *arg, MemoryContext arg_mcxt, Oid typeOid, HeapTuple typeTup, Oid langid, List *trftypes);
static void PLy_output_datum_func2(PLyObToDatum *arg, MemoryContext arg_mcxt, HeapTuple typeTup, Oid langid, List *trftypes);

/* conversion from Datums to Python objects */
static PyObject *PLyBool_FromBool(PLyDatumToOb *arg, Datum d);
static PyObject *PLyFloat_FromFloat4(PLyDatumToOb *arg, Datum d);
static PyObject *PLyFloat_FromFloat8(PLyDatumToOb *arg, Datum d);
static PyObject *PLyDecimal_FromNumeric(PLyDatumToOb *arg, Datum d);
static PyObject *PLyInt_FromInt16(PLyDatumToOb *arg, Datum d);
static PyObject *PLyInt_FromInt32(PLyDatumToOb *arg, Datum d);
static PyObject *PLyLong_FromInt64(PLyDatumToOb *arg, Datum d);
static PyObject *PLyLong_FromOid(PLyDatumToOb *arg, Datum d);
static PyObject *PLyBytes_FromBytea(PLyDatumToOb *arg, Datum d);
static PyObject *PLyString_FromDatum(PLyDatumToOb *arg, Datum d);
static PyObject *PLyObject_FromTransform(PLyDatumToOb *arg, Datum d);
static PyObject *PLyList_FromArray(PLyDatumToOb *arg, Datum d);
static PyObject *PLyList_FromArray_recurse(PLyDatumToOb *elm, int *dims, int ndim, int dim,
						  char **dataptr_p, bits8 **bitmap_p, int *bitmask_p);

/* conversion from Python objects to Datums */
static Datum PLyObject_ToBool(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static Datum PLyObject_ToBytea(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static Datum PLyObject_ToComposite(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static Datum PLyObject_ToDatum(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static Datum PLyObject_ToTransform(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static Datum PLySequence_ToArray(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray);
static void PLySequence_ToArray_recurse(PLyObToDatum *elm, PyObject *list,
							int *dims, int ndim, int dim,
							Datum *elems, bool *nulls, int *currelem);

/* conversion from Python objects to composite Datums (used by triggers and SRFs) */
static Datum PLyString_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *string, bool inarray);
static Datum PLyMapping_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *mapping);
static Datum PLySequence_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *sequence);
static Datum PLyGenericObject_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *object, bool inarray);

void
PLy_typeinfo_init(PLyTypeInfo *arg, MemoryContext mcxt)
{
	arg->is_rowtype = -1;
	arg->in.r.natts = arg->out.r.natts = 0;
	arg->in.r.atts = NULL;
	arg->out.r.atts = NULL;
	arg->typ_relid = InvalidOid;
	arg->typrel_xmin = InvalidTransactionId;
	ItemPointerSetInvalid(&arg->typrel_tid);
	arg->mcxt = mcxt;
}

/*
 * Conversion functions.  Remember output from Python is input to
 * PostgreSQL, and vice versa.
 */
void
PLy_input_datum_func(PLyTypeInfo *arg, Oid typeOid, HeapTuple typeTup, Oid langid, List *trftypes)
{
	if (arg->is_rowtype > 0)
		elog(ERROR, "PLyTypeInfo struct is initialized for Tuple");
	arg->is_rowtype = 0;
	PLy_input_datum_func2(&(arg->in.d), arg->mcxt, typeOid, typeTup, langid, trftypes);
}

void
PLy_output_datum_func(PLyTypeInfo *arg, HeapTuple typeTup, Oid langid, List *trftypes)
{
	if (arg->is_rowtype > 0)
		elog(ERROR, "PLyTypeInfo struct is initialized for a Tuple");
	arg->is_rowtype = 0;
	PLy_output_datum_func2(&(arg->out.d), arg->mcxt, typeTup, langid, trftypes);
}

void
PLy_input_tuple_funcs(PLyTypeInfo *arg, TupleDesc desc)
{
	int			i;
	PLyExecutionContext *exec_ctx = PLy_current_execution_context();
	MemoryContext oldcxt;

	oldcxt = MemoryContextSwitchTo(arg->mcxt);

	if (arg->is_rowtype == 0)
		elog(ERROR, "PLyTypeInfo struct is initialized for a Datum");
	arg->is_rowtype = 1;

	if (arg->in.r.natts != desc->natts)
	{
		if (arg->in.r.atts)
			pfree(arg->in.r.atts);
		arg->in.r.natts = desc->natts;
		arg->in.r.atts = palloc0(desc->natts * sizeof(PLyDatumToOb));
	}

	/* Can this be an unnamed tuple? If not, then an Assert would be enough */
	if (desc->tdtypmod != -1)
		elog(ERROR, "received unnamed record type as input");

	Assert(OidIsValid(desc->tdtypeid));

	/*
	 * RECORDOID means we got called to create input functions for a tuple
	 * fetched by plpy.execute or for an anonymous record type
	 */
	if (desc->tdtypeid != RECORDOID)
	{
		HeapTuple	relTup;

		/* Get the pg_class tuple corresponding to the type of the input */
		arg->typ_relid = typeidTypeRelid(desc->tdtypeid);
		relTup = SearchSysCache1(RELOID, ObjectIdGetDatum(arg->typ_relid));
		if (!HeapTupleIsValid(relTup))
			elog(ERROR, "cache lookup failed for relation %u", arg->typ_relid);

		/* Remember XMIN and TID for later validation if cache is still OK */
		arg->typrel_xmin = HeapTupleHeaderGetRawXmin(relTup->t_data);
		arg->typrel_tid = relTup->t_self;

		ReleaseSysCache(relTup);
	}

	for (i = 0; i < desc->natts; i++)
	{
		HeapTuple	typeTup;

		if (desc->attrs[i]->attisdropped)
			continue;

		if (arg->in.r.atts[i].typoid == desc->attrs[i]->atttypid)
			continue;			/* already set up this entry */

		typeTup = SearchSysCache1(TYPEOID,
								  ObjectIdGetDatum(desc->attrs[i]->atttypid));
		if (!HeapTupleIsValid(typeTup))
			elog(ERROR, "cache lookup failed for type %u",
				 desc->attrs[i]->atttypid);

		PLy_input_datum_func2(&(arg->in.r.atts[i]), arg->mcxt,
							  desc->attrs[i]->atttypid,
							  typeTup,
							  exec_ctx->curr_proc->langid,
							  exec_ctx->curr_proc->trftypes);

		ReleaseSysCache(typeTup);
	}

	MemoryContextSwitchTo(oldcxt);
}

void
PLy_output_tuple_funcs(PLyTypeInfo *arg, TupleDesc desc)
{
	int			i;
	PLyExecutionContext *exec_ctx = PLy_current_execution_context();
	MemoryContext oldcxt;

	oldcxt = MemoryContextSwitchTo(arg->mcxt);

	if (arg->is_rowtype == 0)
		elog(ERROR, "PLyTypeInfo struct is initialized for a Datum");
	arg->is_rowtype = 1;

	if (arg->out.r.natts != desc->natts)
	{
		if (arg->out.r.atts)
			pfree(arg->out.r.atts);
		arg->out.r.natts = desc->natts;
		arg->out.r.atts = palloc0(desc->natts * sizeof(PLyObToDatum));
	}

	Assert(OidIsValid(desc->tdtypeid));

	/*
	 * RECORDOID means we got called to create output functions for an
	 * anonymous record type
	 */
	if (desc->tdtypeid != RECORDOID)
	{
		HeapTuple	relTup;

		/* Get the pg_class tuple corresponding to the type of the output */
		arg->typ_relid = typeidTypeRelid(desc->tdtypeid);
		relTup = SearchSysCache1(RELOID, ObjectIdGetDatum(arg->typ_relid));
		if (!HeapTupleIsValid(relTup))
			elog(ERROR, "cache lookup failed for relation %u", arg->typ_relid);

		/* Remember XMIN and TID for later validation if cache is still OK */
		arg->typrel_xmin = HeapTupleHeaderGetRawXmin(relTup->t_data);
		arg->typrel_tid = relTup->t_self;

		ReleaseSysCache(relTup);
	}

	for (i = 0; i < desc->natts; i++)
	{
		HeapTuple	typeTup;

		if (desc->attrs[i]->attisdropped)
			continue;

		if (arg->out.r.atts[i].typoid == desc->attrs[i]->atttypid)
			continue;			/* already set up this entry */

		typeTup = SearchSysCache1(TYPEOID,
								  ObjectIdGetDatum(desc->attrs[i]->atttypid));
		if (!HeapTupleIsValid(typeTup))
			elog(ERROR, "cache lookup failed for type %u",
				 desc->attrs[i]->atttypid);

		PLy_output_datum_func2(&(arg->out.r.atts[i]), arg->mcxt, typeTup,
							   exec_ctx->curr_proc->langid,
							   exec_ctx->curr_proc->trftypes);

		ReleaseSysCache(typeTup);
	}

	MemoryContextSwitchTo(oldcxt);
}

void
PLy_output_record_funcs(PLyTypeInfo *arg, TupleDesc desc)
{
	/*
	 * If the output record functions are already set, we just have to check
	 * if the record descriptor has not changed
	 */
	if ((arg->is_rowtype == 1) &&
		(arg->out.d.typmod != -1) &&
		(arg->out.d.typmod == desc->tdtypmod))
		return;

	/* bless the record to make it known to the typcache lookup code */
	BlessTupleDesc(desc);
	/* save the freshly generated typmod */
	arg->out.d.typmod = desc->tdtypmod;
	/* proceed with normal I/O function caching */
	PLy_output_tuple_funcs(arg, desc);

	/*
	 * it should change is_rowtype to 1, so we won't go through this again
	 * unless the output record description changes
	 */
	Assert(arg->is_rowtype == 1);
}

/*
 * Transform a tuple into a Python dict object.
 */
PyObject *
PLyDict_FromTuple(PLyTypeInfo *info, HeapTuple tuple, TupleDesc desc)
{
	PyObject   *volatile dict;
	PLyExecutionContext *exec_ctx = PLy_current_execution_context();
	MemoryContext scratch_context = PLy_get_scratch_context(exec_ctx);
	MemoryContext oldcontext = CurrentMemoryContext;

	if (info->is_rowtype != 1)
		elog(ERROR, "PLyTypeInfo structure describes a datum");

	dict = PyDict_New();
	if (dict == NULL)
		PLy_elog(ERROR, "could not create new dictionary");

	PG_TRY();
	{
		int			i;

		/*
		 * Do the work in the scratch context to avoid leaking memory from the
		 * datatype output function calls.
		 */
		MemoryContextSwitchTo(scratch_context);
		for (i = 0; i < info->in.r.natts; i++)
		{
			char	   *key;
			Datum		vattr;
			bool		is_null;
			PyObject   *value;

			if (desc->attrs[i]->attisdropped)
				continue;

			key = NameStr(desc->attrs[i]->attname);
			vattr = heap_getattr(tuple, (i + 1), desc, &is_null);

			if (is_null || info->in.r.atts[i].func == NULL)
				PyDict_SetItemString(dict, key, Py_None);
			else
			{
				value = (info->in.r.atts[i].func) (&info->in.r.atts[i], vattr);
				PyDict_SetItemString(dict, key, value);
				Py_DECREF(value);
			}
		}
		MemoryContextSwitchTo(oldcontext);
		MemoryContextReset(scratch_context);
	}
	PG_CATCH();
	{
		MemoryContextSwitchTo(oldcontext);
		Py_DECREF(dict);
		PG_RE_THROW();
	}
	PG_END_TRY();

	return dict;
}

/*
 *	Convert a Python object to a composite Datum, using all supported
 *	conversion methods: composite as a string, as a sequence, as a mapping or
 *	as an object that has __getattr__ support.
 */
Datum
PLyObject_ToCompositeDatum(PLyTypeInfo *info, TupleDesc desc, PyObject *plrv, bool inarray)
{
	Datum		datum;

	if (PyString_Check(plrv) || PyUnicode_Check(plrv))
		datum = PLyString_ToComposite(info, desc, plrv, inarray);
	else if (PySequence_Check(plrv))
		/* composite type as sequence (tuple, list etc) */
		datum = PLySequence_ToComposite(info, desc, plrv);
	else if (PyMapping_Check(plrv))
		/* composite type as mapping (currently only dict) */
		datum = PLyMapping_ToComposite(info, desc, plrv);
	else
		/* returned as smth, must provide method __getattr__(name) */
		datum = PLyGenericObject_ToComposite(info, desc, plrv, inarray);

	return datum;
}

static void
PLy_output_datum_func2(PLyObToDatum *arg, MemoryContext arg_mcxt, HeapTuple typeTup, Oid langid, List *trftypes)
{
	Form_pg_type typeStruct = (Form_pg_type) GETSTRUCT(typeTup);
	Oid			element_type;
	Oid			base_type;
	Oid			funcid;
	MemoryContext oldcxt;

	oldcxt = MemoryContextSwitchTo(arg_mcxt);

	fmgr_info_cxt(typeStruct->typinput, &arg->typfunc, arg_mcxt);
	arg->typoid = HeapTupleGetOid(typeTup);
	arg->typmod = -1;
	arg->typioparam = getTypeIOParam(typeTup);
	arg->typbyval = typeStruct->typbyval;

	element_type = get_base_element_type(arg->typoid);
	base_type = getBaseType(element_type ? element_type : arg->typoid);

	/*
	 * Select a conversion function to convert Python objects to PostgreSQL
	 * datums.
	 */

	if ((funcid = get_transform_tosql(base_type, langid, trftypes)))
	{
		arg->func = PLyObject_ToTransform;
		fmgr_info_cxt(funcid, &arg->typtransform, arg_mcxt);
	}
	else if (typeStruct->typtype == TYPTYPE_COMPOSITE)
	{
		arg->func = PLyObject_ToComposite;
	}
	else
		switch (base_type)
		{
			case BOOLOID:
				arg->func = PLyObject_ToBool;
				break;
			case BYTEAOID:
				arg->func = PLyObject_ToBytea;
				break;
			default:
				arg->func = PLyObject_ToDatum;
				break;
		}

	if (element_type)
	{
		char		dummy_delim;
		Oid			funcid;

		if (type_is_rowtype(element_type))
			arg->func = PLyObject_ToComposite;

		arg->elm = palloc0(sizeof(*arg->elm));
		arg->elm->func = arg->func;
		arg->elm->typtransform = arg->typtransform;
		arg->func = PLySequence_ToArray;

		arg->elm->typoid = element_type;
		arg->elm->typmod = -1;
		get_type_io_data(element_type, IOFunc_input,
						 &arg->elm->typlen, &arg->elm->typbyval, &arg->elm->typalign, &dummy_delim,
						 &arg->elm->typioparam, &funcid);
		fmgr_info_cxt(funcid, &arg->elm->typfunc, arg_mcxt);
	}

	MemoryContextSwitchTo(oldcxt);
}

static void
PLy_input_datum_func2(PLyDatumToOb *arg, MemoryContext arg_mcxt, Oid typeOid, HeapTuple typeTup, Oid langid, List *trftypes)
{
	Form_pg_type typeStruct = (Form_pg_type) GETSTRUCT(typeTup);
	Oid			element_type;
	Oid			base_type;
	Oid			funcid;
	MemoryContext oldcxt;

	oldcxt = MemoryContextSwitchTo(arg_mcxt);

	/* Get the type's conversion information */
	fmgr_info_cxt(typeStruct->typoutput, &arg->typfunc, arg_mcxt);
	arg->typoid = HeapTupleGetOid(typeTup);
	arg->typmod = -1;
	arg->typioparam = getTypeIOParam(typeTup);
	arg->typbyval = typeStruct->typbyval;
	arg->typlen = typeStruct->typlen;
	arg->typalign = typeStruct->typalign;

	/* Determine which kind of Python object we will convert to */

	element_type = get_base_element_type(typeOid);
	base_type = getBaseType(element_type ? element_type : typeOid);

	if ((funcid = get_transform_fromsql(base_type, langid, trftypes)))
	{
		arg->func = PLyObject_FromTransform;
		fmgr_info_cxt(funcid, &arg->typtransform, arg_mcxt);
	}
	else
		switch (base_type)
		{
			case BOOLOID:
				arg->func = PLyBool_FromBool;
				break;
			case FLOAT4OID:
				arg->func = PLyFloat_FromFloat4;
				break;
			case FLOAT8OID:
				arg->func = PLyFloat_FromFloat8;
				break;
			case NUMERICOID:
				arg->func = PLyDecimal_FromNumeric;
				break;
			case INT2OID:
				arg->func = PLyInt_FromInt16;
				break;
			case INT4OID:
				arg->func = PLyInt_FromInt32;
				break;
			case INT8OID:
				arg->func = PLyLong_FromInt64;
				break;
			case OIDOID:
				arg->func = PLyLong_FromOid;
				break;
			case BYTEAOID:
				arg->func = PLyBytes_FromBytea;
				break;
			default:
				arg->func = PLyString_FromDatum;
				break;
		}

	if (element_type)
	{
		char		dummy_delim;
		Oid			funcid;

		arg->elm = palloc0(sizeof(*arg->elm));
		arg->elm->func = arg->func;
		arg->elm->typtransform = arg->typtransform;
		arg->func = PLyList_FromArray;
		arg->elm->typoid = element_type;
		arg->elm->typmod = -1;
		get_type_io_data(element_type, IOFunc_output,
						 &arg->elm->typlen, &arg->elm->typbyval, &arg->elm->typalign, &dummy_delim,
						 &arg->elm->typioparam, &funcid);
		fmgr_info_cxt(funcid, &arg->elm->typfunc, arg_mcxt);
	}

	MemoryContextSwitchTo(oldcxt);
}

static PyObject *
PLyBool_FromBool(PLyDatumToOb *arg, Datum d)
{
	if (DatumGetBool(d))
		Py_RETURN_TRUE;
	Py_RETURN_FALSE;
}

static PyObject *
PLyFloat_FromFloat4(PLyDatumToOb *arg, Datum d)
{
	return PyFloat_FromDouble(DatumGetFloat4(d));
}

static PyObject *
PLyFloat_FromFloat8(PLyDatumToOb *arg, Datum d)
{
	return PyFloat_FromDouble(DatumGetFloat8(d));
}

static PyObject *
PLyDecimal_FromNumeric(PLyDatumToOb *arg, Datum d)
{
	static PyObject *decimal_constructor;
	char	   *str;
	PyObject   *pyvalue;

	/* Try to import cdecimal.  If it doesn't exist, fall back to decimal. */
	if (!decimal_constructor)
	{
		PyObject   *decimal_module;

		decimal_module = PyImport_ImportModule("cdecimal");
		if (!decimal_module)
		{
			PyErr_Clear();
			decimal_module = PyImport_ImportModule("decimal");
		}
		if (!decimal_module)
			PLy_elog(ERROR, "could not import a module for Decimal constructor");

		decimal_constructor = PyObject_GetAttrString(decimal_module, "Decimal");
		if (!decimal_constructor)
			PLy_elog(ERROR, "no Decimal attribute in module");
	}

	str = DatumGetCString(DirectFunctionCall1(numeric_out, d));
	pyvalue = PyObject_CallFunction(decimal_constructor, "s", str);
	if (!pyvalue)
		PLy_elog(ERROR, "conversion from numeric to Decimal failed");

	return pyvalue;
}

static PyObject *
PLyInt_FromInt16(PLyDatumToOb *arg, Datum d)
{
	return PyInt_FromLong(DatumGetInt16(d));
}

static PyObject *
PLyInt_FromInt32(PLyDatumToOb *arg, Datum d)
{
	return PyInt_FromLong(DatumGetInt32(d));
}

static PyObject *
PLyLong_FromInt64(PLyDatumToOb *arg, Datum d)
{
	/* on 32 bit platforms "long" may be too small */
	if (sizeof(int64) > sizeof(long))
		return PyLong_FromLongLong(DatumGetInt64(d));
	else
		return PyLong_FromLong(DatumGetInt64(d));
}

static PyObject *
PLyLong_FromOid(PLyDatumToOb *arg, Datum d)
{
	return PyLong_FromUnsignedLong(DatumGetObjectId(d));
}

static PyObject *
PLyBytes_FromBytea(PLyDatumToOb *arg, Datum d)
{
	text	   *txt = DatumGetByteaPP(d);
	char	   *str = VARDATA_ANY(txt);
	size_t		size = VARSIZE_ANY_EXHDR(txt);

	return PyBytes_FromStringAndSize(str, size);
}

static PyObject *
PLyString_FromDatum(PLyDatumToOb *arg, Datum d)
{
	char	   *x = OutputFunctionCall(&arg->typfunc, d);
	PyObject   *r = PyString_FromString(x);

	pfree(x);
	return r;
}

static PyObject *
PLyObject_FromTransform(PLyDatumToOb *arg, Datum d)
{
	return (PyObject *) DatumGetPointer(FunctionCall1(&arg->typtransform, d));
}

static PyObject *
PLyList_FromArray(PLyDatumToOb *arg, Datum d)
{
	ArrayType  *array = DatumGetArrayTypeP(d);
	PLyDatumToOb *elm = arg->elm;
	int			ndim;
	int		   *dims;
	char	   *dataptr;
	bits8	   *bitmap;
	int			bitmask;

	if (ARR_NDIM(array) == 0)
		return PyList_New(0);

	/* Array dimensions and left bounds */
	ndim = ARR_NDIM(array);
	dims = ARR_DIMS(array);
	Assert(ndim < MAXDIM);

	/*
	 * We iterate the SQL array in the physical order it's stored in the
	 * datum. For example, for a 3-dimensional array the order of iteration
	 * would be the following: [0,0,0] elements through [0,0,k], then [0,1,0]
	 * through [0,1,k] till [0,m,k], then [1,0,0] through [1,0,k] till
	 * [1,m,k], and so on.
	 *
	 * In Python, there are no multi-dimensional lists as such, but they are
	 * represented as a list of lists. So a 3-d array of [n,m,k] elements is a
	 * list of n m-element arrays, each element of which is k-element array.
	 * PLyList_FromArray_recurse() builds the Python list for a single
	 * dimension, and recurses for the next inner dimension.
	 */
	dataptr = ARR_DATA_PTR(array);
	bitmap = ARR_NULLBITMAP(array);
	bitmask = 1;

	return PLyList_FromArray_recurse(elm, dims, ndim, 0,
									 &dataptr, &bitmap, &bitmask);
}

static PyObject *
PLyList_FromArray_recurse(PLyDatumToOb *elm, int *dims, int ndim, int dim,
						  char **dataptr_p, bits8 **bitmap_p, int *bitmask_p)
{
	int			i;
	PyObject   *list;

	list = PyList_New(dims[dim]);

	if (dim < ndim - 1)
	{
		/* Outer dimension. Recurse for each inner slice. */
		for (i = 0; i < dims[dim]; i++)
		{
			PyObject   *sublist;

			sublist = PLyList_FromArray_recurse(elm, dims, ndim, dim + 1,
												dataptr_p, bitmap_p, bitmask_p);
			PyList_SET_ITEM(list, i, sublist);
		}
	}
	else
	{
		/*
		 * Innermost dimension. Fill the list with the values from the array
		 * for this slice.
		 */
		char	   *dataptr = *dataptr_p;
		bits8	   *bitmap = *bitmap_p;
		int			bitmask = *bitmask_p;

		for (i = 0; i < dims[dim]; i++)
		{
			/* checking for NULL */
			if (bitmap && (*bitmap & bitmask) == 0)
			{
				Py_INCREF(Py_None);
				PyList_SET_ITEM(list, i, Py_None);
			}
			else
			{
				Datum		itemvalue;

				itemvalue = fetch_att(dataptr, elm->typbyval, elm->typlen);
				PyList_SET_ITEM(list, i, elm->func(elm, itemvalue));
				dataptr = att_addlength_pointer(dataptr, elm->typlen, dataptr);
				dataptr = (char *) att_align_nominal(dataptr, elm->typalign);
			}

			/* advance bitmap pointer if any */
			if (bitmap)
			{
				bitmask <<= 1;
				if (bitmask == 0x100 /* (1<<8) */ )
				{
					bitmap++;
					bitmask = 1;
				}
			}
		}

		*dataptr_p = dataptr;
		*bitmap_p = bitmap;
		*bitmask_p = bitmask;
	}

	return list;
}

/*
 * Convert a Python object to a PostgreSQL bool datum.  This can't go
 * through the generic conversion function, because Python attaches a
 * Boolean value to everything, more things than the PostgreSQL bool
 * type can parse.
 */
static Datum
PLyObject_ToBool(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	Datum		rv;

	Assert(plrv != Py_None);
	rv = BoolGetDatum(PyObject_IsTrue(plrv));

	if (get_typtype(arg->typoid) == TYPTYPE_DOMAIN)
		domain_check(rv, false, arg->typoid, &arg->typfunc.fn_extra, arg->typfunc.fn_mcxt);

	return rv;
}

/*
 * Convert a Python object to a PostgreSQL bytea datum.  This doesn't
 * go through the generic conversion function to circumvent problems
 * with embedded nulls.  And it's faster this way.
 */
static Datum
PLyObject_ToBytea(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	PyObject   *volatile plrv_so = NULL;
	Datum		rv;

	Assert(plrv != Py_None);

	plrv_so = PyObject_Bytes(plrv);
	if (!plrv_so)
		PLy_elog(ERROR, "could not create bytes representation of Python object");

	PG_TRY();
	{
		char	   *plrv_sc = PyBytes_AsString(plrv_so);
		size_t		len = PyBytes_Size(plrv_so);
		size_t		size = len + VARHDRSZ;
		bytea	   *result = palloc(size);

		SET_VARSIZE(result, size);
		memcpy(VARDATA(result), plrv_sc, len);
		rv = PointerGetDatum(result);
	}
	PG_CATCH();
	{
		Py_XDECREF(plrv_so);
		PG_RE_THROW();
	}
	PG_END_TRY();

	Py_XDECREF(plrv_so);

	if (get_typtype(arg->typoid) == TYPTYPE_DOMAIN)
		domain_check(rv, false, arg->typoid, &arg->typfunc.fn_extra, arg->typfunc.fn_mcxt);

	return rv;
}


/*
 * Convert a Python object to a composite type. First look up the type's
 * description, then route the Python object through the conversion function
 * for obtaining PostgreSQL tuples.
 */
static Datum
PLyObject_ToComposite(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	Datum		rv;
	PLyTypeInfo info;
	TupleDesc	desc;
	MemoryContext cxt;

	if (typmod != -1)
		elog(ERROR, "received unnamed record type as input");

	/* Create a dummy PLyTypeInfo */
	cxt = AllocSetContextCreate(CurrentMemoryContext,
								"PL/Python temp context",
								ALLOCSET_DEFAULT_SIZES);
	MemSet(&info, 0, sizeof(PLyTypeInfo));
	PLy_typeinfo_init(&info, cxt);
	/* Mark it as needing output routines lookup */
	info.is_rowtype = 2;

	desc = lookup_rowtype_tupdesc(arg->typoid, arg->typmod);

	/*
	 * This will set up the dummy PLyTypeInfo's output conversion routines,
	 * since we left is_rowtype as 2. A future optimization could be caching
	 * that info instead of looking it up every time a tuple is returned from
	 * the function.
	 */
	rv = PLyObject_ToCompositeDatum(&info, desc, plrv, inarray);

	ReleaseTupleDesc(desc);

	MemoryContextDelete(cxt);

	return rv;
}


/*
 * Convert Python object to C string in server encoding.
 */
char *
PLyObject_AsString(PyObject *plrv)
{
	PyObject   *plrv_bo;
	char	   *plrv_sc;
	size_t		plen;
	size_t		slen;

	if (PyUnicode_Check(plrv))
		plrv_bo = PLyUnicode_Bytes(plrv);
	else if (PyFloat_Check(plrv))
	{
		/* use repr() for floats, str() is lossy */
#if PY_MAJOR_VERSION >= 3
		PyObject   *s = PyObject_Repr(plrv);

		plrv_bo = PLyUnicode_Bytes(s);
		Py_XDECREF(s);
#else
		plrv_bo = PyObject_Repr(plrv);
#endif
	}
	else
	{
#if PY_MAJOR_VERSION >= 3
		PyObject   *s = PyObject_Str(plrv);

		plrv_bo = PLyUnicode_Bytes(s);
		Py_XDECREF(s);
#else
		plrv_bo = PyObject_Str(plrv);
#endif
	}
	if (!plrv_bo)
		PLy_elog(ERROR, "could not create string representation of Python object");

	plrv_sc = pstrdup(PyBytes_AsString(plrv_bo));
	plen = PyBytes_Size(plrv_bo);
	slen = strlen(plrv_sc);

	Py_XDECREF(plrv_bo);

	if (slen < plen)
		ereport(ERROR,
				(errcode(ERRCODE_DATATYPE_MISMATCH),
				 errmsg("could not convert Python object into cstring: Python string representation appears to contain null bytes")));
	else if (slen > plen)
		elog(ERROR, "could not convert Python object into cstring: Python string longer than reported length");
	pg_verifymbstr(plrv_sc, slen, false);

	return plrv_sc;
}


/*
 * Generic conversion function: Convert PyObject to cstring and
 * cstring into PostgreSQL type.
 */
static Datum
PLyObject_ToDatum(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	char	   *str;

	Assert(plrv != Py_None);

	str = PLyObject_AsString(plrv);

	/*
	 * If we are parsing a composite type within an array, and the string
	 * isn't a valid record literal, there's a high chance that the function
	 * did something like:
	 *
	 * CREATE FUNCTION .. RETURNS comptype[] AS $$ return [['foo', 'bar']] $$
	 * LANGUAGE plpython;
	 *
	 * Before PostgreSQL 10, that was interpreted as a single-dimensional
	 * array, containing record ('foo', 'bar'). PostgreSQL 10 added support
	 * for multi-dimensional arrays, and it is now interpreted as a
	 * two-dimensional array, containing two records, 'foo', and 'bar'.
	 * record_in() will throw an error, because "foo" is not a valid record
	 * literal.
	 *
	 * To make that less confusing to users who are upgrading from older
	 * versions, try to give a hint in the typical instances of that. If we
	 * are parsing an array of composite types, and we see a string literal
	 * that is not a valid record literal, give a hint. We only want to give
	 * the hint in the narrow case of a malformed string literal, not any
	 * error from record_in(), so check for that case here specifically.
	 *
	 * This check better match the one in record_in(), so that we don't forbid
	 * literals that are actually valid!
	 */
	if (inarray && arg->typfunc.fn_oid == F_RECORD_IN)
	{
		char	   *ptr = str;

		/* Allow leading whitespace */
		while (*ptr && isspace((unsigned char) *ptr))
			ptr++;
		if (*ptr++ != '(')
			ereport(ERROR,
					(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
					 errmsg("malformed record literal: \"%s\"", str),
					 errdetail("Missing left parenthesis."),
					 errhint("To return a composite type in an array, return the composite type as a Python tuple, e.g., \"[('foo',)]\".")));
	}

	return InputFunctionCall(&arg->typfunc,
							 str,
							 arg->typioparam,
							 typmod);
}


static Datum
PLyObject_ToTransform(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	return FunctionCall1(&arg->typtransform, PointerGetDatum(plrv));
}


static Datum
PLySequence_ToArray(PLyObToDatum *arg, int32 typmod, PyObject *plrv, bool inarray)
{
	ArrayType  *array;
	int			i;
	Datum	   *elems;
	bool	   *nulls;
	int64		len;
	int			ndim;
	int			dims[MAXDIM];
	int			lbs[MAXDIM];
	int			currelem;
	Datum		rv;
	PyObject   *pyptr = plrv;
	PyObject   *next;

	Assert(plrv != Py_None);

	/*
	 * Determine the number of dimensions, and their sizes.
	 */
	ndim = 0;
	len = 1;

	Py_INCREF(plrv);

	for (;;)
	{
		if (!PyList_Check(pyptr))
			break;

		if (ndim == MAXDIM)
			PLy_elog(ERROR, "number of array dimensions exceeds the maximum allowed (%d)", MAXDIM);

		dims[ndim] = PySequence_Length(pyptr);
		if (dims[ndim] < 0)
			PLy_elog(ERROR, "cannot determine sequence length for function return value");

		if (dims[ndim] > MaxAllocSize)
			PLy_elog(ERROR, "array size exceeds the maximum allowed");

		len *= dims[ndim];
		if (len > MaxAllocSize)
			PLy_elog(ERROR, "array size exceeds the maximum allowed");

		if (dims[ndim] == 0)
		{
			/* empty sequence */
			break;
		}

		ndim++;

		next = PySequence_GetItem(pyptr, 0);
		Py_XDECREF(pyptr);
		pyptr = next;
	}
	Py_XDECREF(pyptr);

	/*
	 * Check for zero dimensions. This happens if the object is a tuple or a
	 * string, rather than a list, or is not a sequence at all. We don't map
	 * tuples or strings to arrays in general, but in the first level, be
	 * lenient, for historical reasons. So if the object is a sequence of any
	 * kind, treat it as a one-dimensional array.
	 */
	if (ndim == 0)
	{
		if (!PySequence_Check(plrv))
			PLy_elog(ERROR, "return value of function with array return type is not a Python sequence");

		ndim = 1;
		len = dims[0] = PySequence_Length(plrv);
	}

	/*
	 * Traverse the Python lists, in depth-first order, and collect all the
	 * elements at the bottom level into 'elems'/'nulls' arrays.
	 */
	elems = palloc(sizeof(Datum) * len);
	nulls = palloc(sizeof(bool) * len);
	currelem = 0;
	PLySequence_ToArray_recurse(arg->elm, plrv,
								dims, ndim, 0,
								elems, nulls, &currelem);

	for (i = 0; i < ndim; i++)
		lbs[i] = 1;

	array = construct_md_array(elems,
							   nulls,
							   ndim,
							   dims,
							   lbs,
							   get_base_element_type(arg->typoid),
							   arg->elm->typlen,
							   arg->elm->typbyval,
							   arg->elm->typalign);

	/*
	 * If the result type is a domain of array, the resulting array must be
	 * checked.
	 */
	rv = PointerGetDatum(array);
	if (get_typtype(arg->typoid) == TYPTYPE_DOMAIN)
		domain_check(rv, false, arg->typoid, &arg->typfunc.fn_extra, arg->typfunc.fn_mcxt);
	return rv;
}

/*
 * Helper function for PLySequence_ToArray. Traverse a Python list of lists in
 * depth-first order, storing the elements in 'elems'.
 */
static void
PLySequence_ToArray_recurse(PLyObToDatum *elm, PyObject *list,
							int *dims, int ndim, int dim,
							Datum *elems, bool *nulls, int *currelem)
{
	int			i;

	if (PySequence_Length(list) != dims[dim])
		PLy_elog(ERROR,
				 "multidimensional arrays must have array expressions with matching dimensions. "
				 "PL/Python function return value has sequence length %d while expected %d",
				 (int) PySequence_Length(list), dims[dim]);

	if (dim < ndim - 1)
	{
		for (i = 0; i < dims[dim]; i++)
		{
			PyObject   *sublist = PySequence_GetItem(list, i);

			PLySequence_ToArray_recurse(elm, sublist, dims, ndim, dim + 1,
										elems, nulls, currelem);
			Py_XDECREF(sublist);
		}
	}
	else
	{
		for (i = 0; i < dims[dim]; i++)
		{
			PyObject   *obj = PySequence_GetItem(list, i);

			if (obj == Py_None)
			{
				nulls[*currelem] = true;
				elems[*currelem] = (Datum) 0;
			}
			else
			{
				nulls[*currelem] = false;
				elems[*currelem] = elm->func(elm, -1, obj, true);
			}
			Py_XDECREF(obj);
			(*currelem)++;
		}
	}
}


static Datum
PLyString_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *string, bool inarray)
{
	Datum		result;
	HeapTuple	typeTup;
	PLyTypeInfo locinfo;
	PLyExecutionContext *exec_ctx = PLy_current_execution_context();
	MemoryContext cxt;

	/* Create a dummy PLyTypeInfo */
	cxt = AllocSetContextCreate(CurrentMemoryContext,
								"PL/Python temp context",
								ALLOCSET_DEFAULT_SIZES);
	MemSet(&locinfo, 0, sizeof(PLyTypeInfo));
	PLy_typeinfo_init(&locinfo, cxt);

	typeTup = SearchSysCache1(TYPEOID, ObjectIdGetDatum(desc->tdtypeid));
	if (!HeapTupleIsValid(typeTup))
		elog(ERROR, "cache lookup failed for type %u", desc->tdtypeid);

	PLy_output_datum_func2(&locinfo.out.d, locinfo.mcxt, typeTup,
						   exec_ctx->curr_proc->langid,
						   exec_ctx->curr_proc->trftypes);

	ReleaseSysCache(typeTup);

	result = PLyObject_ToDatum(&locinfo.out.d, desc->tdtypmod, string, inarray);

	MemoryContextDelete(cxt);

	return result;
}


static Datum
PLyMapping_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *mapping)
{
	Datum		result;
	HeapTuple	tuple;
	Datum	   *values;
	bool	   *nulls;
	volatile int i;

	Assert(PyMapping_Check(mapping));

	if (info->is_rowtype == 2)
		PLy_output_tuple_funcs(info, desc);
	Assert(info->is_rowtype == 1);

	/* Build tuple */
	values = palloc(sizeof(Datum) * desc->natts);
	nulls = palloc(sizeof(bool) * desc->natts);
	for (i = 0; i < desc->natts; ++i)
	{
		char	   *key;
		PyObject   *volatile value;
		PLyObToDatum *att;

		if (desc->attrs[i]->attisdropped)
		{
			values[i] = (Datum) 0;
			nulls[i] = true;
			continue;
		}

		key = NameStr(desc->attrs[i]->attname);
		value = NULL;
		att = &info->out.r.atts[i];
		PG_TRY();
		{
			value = PyMapping_GetItemString(mapping, key);
			if (value == Py_None)
			{
				values[i] = (Datum) NULL;
				nulls[i] = true;
			}
			else if (value)
			{
				values[i] = (att->func) (att, -1, value, false);
				nulls[i] = false;
			}
			else
				ereport(ERROR,
						(errcode(ERRCODE_UNDEFINED_COLUMN),
						 errmsg("key \"%s\" not found in mapping", key),
						 errhint("To return null in a column, "
								 "add the value None to the mapping with the key named after the column.")));

			Py_XDECREF(value);
			value = NULL;
		}
		PG_CATCH();
		{
			Py_XDECREF(value);
			PG_RE_THROW();
		}
		PG_END_TRY();
	}

	tuple = heap_form_tuple(desc, values, nulls);
	result = heap_copy_tuple_as_datum(tuple, desc);
	heap_freetuple(tuple);

	pfree(values);
	pfree(nulls);

	return result;
}


static Datum
PLySequence_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *sequence)
{
	Datum		result;
	HeapTuple	tuple;
	Datum	   *values;
	bool	   *nulls;
	volatile int idx;
	volatile int i;

	Assert(PySequence_Check(sequence));

	/*
	 * Check that sequence length is exactly same as PG tuple's. We actually
	 * can ignore exceeding items or assume missing ones as null but to avoid
	 * plpython developer's errors we are strict here
	 */
	idx = 0;
	for (i = 0; i < desc->natts; i++)
	{
		if (!desc->attrs[i]->attisdropped)
			idx++;
	}
	if (PySequence_Length(sequence) != idx)
		ereport(ERROR,
				(errcode(ERRCODE_DATATYPE_MISMATCH),
				 errmsg("length of returned sequence did not match number of columns in row")));

	if (info->is_rowtype == 2)
		PLy_output_tuple_funcs(info, desc);
	Assert(info->is_rowtype == 1);

	/* Build tuple */
	values = palloc(sizeof(Datum) * desc->natts);
	nulls = palloc(sizeof(bool) * desc->natts);
	idx = 0;
	for (i = 0; i < desc->natts; ++i)
	{
		PyObject   *volatile value;
		PLyObToDatum *att;

		if (desc->attrs[i]->attisdropped)
		{
			values[i] = (Datum) 0;
			nulls[i] = true;
			continue;
		}

		value = NULL;
		att = &info->out.r.atts[i];
		PG_TRY();
		{
			value = PySequence_GetItem(sequence, idx);
			Assert(value);
			if (value == Py_None)
			{
				values[i] = (Datum) NULL;
				nulls[i] = true;
			}
			else if (value)
			{
				values[i] = (att->func) (att, -1, value, false);
				nulls[i] = false;
			}

			Py_XDECREF(value);
			value = NULL;
		}
		PG_CATCH();
		{
			Py_XDECREF(value);
			PG_RE_THROW();
		}
		PG_END_TRY();

		idx++;
	}

	tuple = heap_form_tuple(desc, values, nulls);
	result = heap_copy_tuple_as_datum(tuple, desc);
	heap_freetuple(tuple);

	pfree(values);
	pfree(nulls);

	return result;
}


static Datum
PLyGenericObject_ToComposite(PLyTypeInfo *info, TupleDesc desc, PyObject *object, bool inarray)
{
	Datum		result;
	HeapTuple	tuple;
	Datum	   *values;
	bool	   *nulls;
	volatile int i;

	if (info->is_rowtype == 2)
		PLy_output_tuple_funcs(info, desc);
	Assert(info->is_rowtype == 1);

	/* Build tuple */
	values = palloc(sizeof(Datum) * desc->natts);
	nulls = palloc(sizeof(bool) * desc->natts);
	for (i = 0; i < desc->natts; ++i)
	{
		char	   *key;
		PyObject   *volatile value;
		PLyObToDatum *att;

		if (desc->attrs[i]->attisdropped)
		{
			values[i] = (Datum) 0;
			nulls[i] = true;
			continue;
		}

		key = NameStr(desc->attrs[i]->attname);
		value = NULL;
		att = &info->out.r.atts[i];
		PG_TRY();
		{
			value = PyObject_GetAttrString(object, key);
			if (value == Py_None)
			{
				values[i] = (Datum) NULL;
				nulls[i] = true;
			}
			else if (value)
			{
				values[i] = (att->func) (att, -1, value, false);
				nulls[i] = false;
			}
			else
			{
				/*
				 * No attribute for this column in the object.
				 *
				 * If we are parsing a composite type in an array, a likely
				 * cause is that the function contained something like "[[123,
				 * 'foo']]". Before PostgreSQL 10, that was interpreted as an
				 * array, with a composite type (123, 'foo') in it. But now
				 * it's interpreted as a two-dimensional array, and we try to
				 * interpret "123" as the composite type. See also similar
				 * heuristic in PLyObject_ToDatum().
				 */
				ereport(ERROR,
						(errcode(ERRCODE_UNDEFINED_COLUMN),
						 errmsg("attribute \"%s\" does not exist in Python object", key),
						 inarray ?
						 errhint("To return a composite type in an array, return the composite type as a Python tuple, e.g., \"[('foo',)]\".") :
						 errhint("To return null in a column, let the returned object have an attribute named after column with value None.")));
			}

			Py_XDECREF(value);
			value = NULL;
		}
		PG_CATCH();
		{
			Py_XDECREF(value);
			PG_RE_THROW();
		}
		PG_END_TRY();
	}

	tuple = heap_form_tuple(desc, values, nulls);
	result = heap_copy_tuple_as_datum(tuple, desc);
	heap_freetuple(tuple);

	pfree(values);
	pfree(nulls);

	return result;
}
