plpy_typeio.c

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/*
 * 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;
}