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 "catalog/pg_type.h"
#include "funcapi.h"
#include "mb/pg_wchar.h"
#include "miscadmin.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/fmgroids.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"

#include "plpython.h"

#include "plpy_typeio.h"

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


/* 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_FromScalar(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);
static PyObject *PLyDict_FromComposite(PLyDatumToOb *arg, Datum d);
static PyObject *PLyDict_FromTuple(PLyDatumToOb *arg, HeapTuple tuple, TupleDesc desc);

/* conversion from Python objects to Datums */
static Datum PLyObject_ToBool(PLyObToDatum *arg, PyObject *plrv,
                 bool *isnull, bool inarray);
static Datum PLyObject_ToBytea(PLyObToDatum *arg, PyObject *plrv,
                  bool *isnull, bool inarray);
static Datum PLyObject_ToComposite(PLyObToDatum *arg, PyObject *plrv,
                      bool *isnull, bool inarray);
static Datum PLyObject_ToScalar(PLyObToDatum *arg, PyObject *plrv,
                   bool *isnull, bool inarray);
static Datum PLyObject_ToDomain(PLyObToDatum *arg, PyObject *plrv,
                   bool *isnull, bool inarray);
static Datum PLyObject_ToTransform(PLyObToDatum *arg, PyObject *plrv,
                      bool *isnull, bool inarray);
static Datum PLySequence_ToArray(PLyObToDatum *arg, PyObject *plrv,
                    bool *isnull, 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 */
static Datum PLyString_ToComposite(PLyObToDatum *arg, PyObject *string, bool inarray);
static Datum PLyMapping_ToComposite(PLyObToDatum *arg, TupleDesc desc, PyObject *mapping);
static Datum PLySequence_ToComposite(PLyObToDatum *arg, TupleDesc desc, PyObject *sequence);
static Datum PLyGenericObject_ToComposite(PLyObToDatum *arg, TupleDesc desc, PyObject *object, bool inarray);


/*
 * Conversion functions.  Remember output from Python is input to
 * PostgreSQL, and vice versa.
 */

/*
 * Perform input conversion, given correctly-set-up state information.
 *
 * This is the outer-level entry point for any input conversion.  Internally,
 * the conversion functions recurse directly to each other.
 */
PyObject *
PLy_input_convert(PLyDatumToOb *arg, Datum val)
{
    PyObject   *result;
    PLyExecutionContext *exec_ctx = PLy_current_execution_context();
    MemoryContext scratch_context = PLy_get_scratch_context(exec_ctx);
    MemoryContext oldcontext;

    /*
     * Do the work in the scratch context to avoid leaking memory from the
     * datatype output function calls.  (The individual PLyDatumToObFunc
     * functions can't reset the scratch context, because they recurse and an
     * inner one might clobber data an outer one still needs.  So we do it
     * once at the outermost recursion level.)
     *
     * We reset the scratch context before, not after, each conversion cycle.
     * This way we aren't on the hook to release a Python refcount on the
     * result object in case MemoryContextReset throws an error.
     */
    MemoryContextReset(scratch_context);

    oldcontext = MemoryContextSwitchTo(scratch_context);

    result = arg->func(arg, val);

    MemoryContextSwitchTo(oldcontext);

    return result;
}

/*
 * Perform output conversion, given correctly-set-up state information.
 *
 * This is the outer-level entry point for any output conversion.  Internally,
 * the conversion functions recurse directly to each other.
 *
 * The result, as well as any cruft generated along the way, are in the
 * current memory context.  Caller is responsible for cleanup.
 */
Datum
PLy_output_convert(PLyObToDatum *arg, PyObject *val, bool *isnull)
{
    /* at outer level, we are not considering an array element */
    return arg->func(arg, val, isnull, false);
}

/*
 * Transform a tuple into a Python dict object.
 *
 * Note: the tupdesc must match the one used to set up *arg.  We could
 * insist that this function lookup the tupdesc from what is in *arg,
 * but in practice all callers have the right tupdesc available.
 */
PyObject *
PLy_input_from_tuple(PLyDatumToOb *arg, HeapTuple tuple, TupleDesc desc)
{
    PyObject   *dict;
    PLyExecutionContext *exec_ctx = PLy_current_execution_context();
    MemoryContext scratch_context = PLy_get_scratch_context(exec_ctx);
    MemoryContext oldcontext;

    /*
     * As in PLy_input_convert, do the work in the scratch context.
     */
    MemoryContextReset(scratch_context);

    oldcontext = MemoryContextSwitchTo(scratch_context);

    dict = PLyDict_FromTuple(arg, tuple, desc);

    MemoryContextSwitchTo(oldcontext);

    return dict;
}

/*
 * Initialize, or re-initialize, per-column input info for a composite type.
 *
 * This is separate from PLy_input_setup_func() because in cases involving
 * anonymous record types, we need to be passed the tupdesc explicitly.
 * It's caller's responsibility that the tupdesc has adequate lifespan
 * in such cases.  If the tupdesc is for a named composite or registered
 * record type, it does not need to be long-lived.
 */
void
PLy_input_setup_tuple(PLyDatumToOb *arg, TupleDesc desc, PLyProcedure *proc)
{
    int         i;

    /* We should be working on a previously-set-up struct */
    Assert(arg->func == PLyDict_FromComposite);

    /* Save pointer to tupdesc, but only if this is an anonymous record type */
    if (arg->typoid == RECORDOID && arg->typmod < 0)
        arg->u.tuple.recdesc = desc;

    /* (Re)allocate atts array as needed */
    if (arg->u.tuple.natts != desc->natts)
    {
        if (arg->u.tuple.atts)
            pfree(arg->u.tuple.atts);
        arg->u.tuple.natts = desc->natts;
        arg->u.tuple.atts = (PLyDatumToOb *)
            MemoryContextAllocZero(arg->mcxt,
                                   desc->natts * sizeof(PLyDatumToOb));
    }

    /* Fill the atts entries, except for dropped columns */
    for (i = 0; i < desc->natts; i++)
    {
        Form_pg_attribute attr = TupleDescAttr(desc, i);
        PLyDatumToOb *att = &arg->u.tuple.atts[i];

        if (attr->attisdropped)
            continue;

        if (att->typoid == attr->atttypid && att->typmod == attr->atttypmod)
            continue;           /* already set up this entry */

        PLy_input_setup_func(att, arg->mcxt,
                             attr->atttypid, attr->atttypmod,
                             proc);
    }
}

/*
 * Initialize, or re-initialize, per-column output info for a composite type.
 *
 * This is separate from PLy_output_setup_func() because in cases involving
 * anonymous record types, we need to be passed the tupdesc explicitly.
 * It's caller's responsibility that the tupdesc has adequate lifespan
 * in such cases.  If the tupdesc is for a named composite or registered
 * record type, it does not need to be long-lived.
 */
void
PLy_output_setup_tuple(PLyObToDatum *arg, TupleDesc desc, PLyProcedure *proc)
{
    int         i;

    /* We should be working on a previously-set-up struct */
    Assert(arg->func == PLyObject_ToComposite);

    /* Save pointer to tupdesc, but only if this is an anonymous record type */
    if (arg->typoid == RECORDOID && arg->typmod < 0)
        arg->u.tuple.recdesc = desc;

    /* (Re)allocate atts array as needed */
    if (arg->u.tuple.natts != desc->natts)
    {
        if (arg->u.tuple.atts)
            pfree(arg->u.tuple.atts);
        arg->u.tuple.natts = desc->natts;
        arg->u.tuple.atts = (PLyObToDatum *)
            MemoryContextAllocZero(arg->mcxt,
                                   desc->natts * sizeof(PLyObToDatum));
    }

    /* Fill the atts entries, except for dropped columns */
    for (i = 0; i < desc->natts; i++)
    {
        Form_pg_attribute attr = TupleDescAttr(desc, i);
        PLyObToDatum *att = &arg->u.tuple.atts[i];

        if (attr->attisdropped)
            continue;

        if (att->typoid == attr->atttypid && att->typmod == attr->atttypmod)
            continue;           /* already set up this entry */

        PLy_output_setup_func(att, arg->mcxt,
                              attr->atttypid, attr->atttypmod,
                              proc);
    }
}

/*
 * Set up output info for a PL/Python function returning record.
 *
 * Note: the given tupdesc is not necessarily long-lived.
 */
void
PLy_output_setup_record(PLyObToDatum *arg, TupleDesc desc, PLyProcedure *proc)
{
    /* Makes no sense unless RECORD */
    Assert(arg->typoid == RECORDOID);
    Assert(desc->tdtypeid == RECORDOID);

    /*
     * Bless the record type if not already done.  We'd have to do this anyway
     * to return a tuple, so we might as well force the issue so we can use
     * the known-record-type code path.
     */
    BlessTupleDesc(desc);

    /*
     * Update arg->typmod, and clear the recdesc link if it's changed. The
     * next call of PLyObject_ToComposite will look up a long-lived tupdesc
     * for the record type.
     */
    arg->typmod = desc->tdtypmod;
    if (arg->u.tuple.recdesc &&
        arg->u.tuple.recdesc->tdtypmod != arg->typmod)
        arg->u.tuple.recdesc = NULL;

    /* Update derived data if necessary */
    PLy_output_setup_tuple(arg, desc, proc);
}

/*
 * Recursively initialize the PLyObToDatum structure(s) needed to construct
 * a SQL value of the specified typeOid/typmod from a Python value.
 * (But note that at this point we may have RECORDOID/-1, ie, an indeterminate
 * record type.)
 * proc is used to look up transform functions.
 */
void
PLy_output_setup_func(PLyObToDatum *arg, MemoryContext arg_mcxt,
                      Oid typeOid, int32 typmod,
                      PLyProcedure *proc)
{
    TypeCacheEntry *typentry;
    char        typtype;
    Oid         trfuncid;
    Oid         typinput;

    /* Since this is recursive, it could theoretically be driven to overflow */
    check_stack_depth();

    arg->typoid = typeOid;
    arg->typmod = typmod;
    arg->mcxt = arg_mcxt;

    /*
     * Fetch typcache entry for the target type, asking for whatever info
     * we'll need later.  RECORD is a special case: just treat it as composite
     * without bothering with the typcache entry.
     */
    if (typeOid != RECORDOID)
    {
        typentry = lookup_type_cache(typeOid, TYPECACHE_DOMAIN_BASE_INFO);
        typtype = typentry->typtype;
        arg->typbyval = typentry->typbyval;
        arg->typlen = typentry->typlen;
        arg->typalign = typentry->typalign;
    }
    else
    {
        typentry = NULL;
        typtype = TYPTYPE_COMPOSITE;
        /* hard-wired knowledge about type RECORD: */
        arg->typbyval = false;
        arg->typlen = -1;
        arg->typalign = 'd';
    }

    /*
     * Choose conversion method.  Note that transform functions are checked
     * for composite and scalar types, but not for arrays or domains.  This is
     * somewhat historical, but we'd have a problem allowing them on domains,
     * since we drill down through all levels of a domain nest without looking
     * at the intermediate levels at all.
     */
    if (typtype == TYPTYPE_DOMAIN)
    {
        /* Domain */
        arg->func = PLyObject_ToDomain;
        arg->u.domain.domain_info = NULL;
        /* Recursively set up conversion info for the element type */
        arg->u.domain.base = (PLyObToDatum *)
            MemoryContextAllocZero(arg_mcxt, sizeof(PLyObToDatum));
        PLy_output_setup_func(arg->u.domain.base, arg_mcxt,
                              typentry->domainBaseType,
                              typentry->domainBaseTypmod,
                              proc);
    }
    else if (typentry &&
             OidIsValid(typentry->typelem) && typentry->typlen == -1)
    {
        /* Standard varlena array (cf. get_element_type) */
        arg->func = PLySequence_ToArray;
        /* Get base type OID to insert into constructed array */
        /* (note this might not be the same as the immediate child type) */
        arg->u.array.elmbasetype = getBaseType(typentry->typelem);
        /* Recursively set up conversion info for the element type */
        arg->u.array.elm = (PLyObToDatum *)
            MemoryContextAllocZero(arg_mcxt, sizeof(PLyObToDatum));
        PLy_output_setup_func(arg->u.array.elm, arg_mcxt,
                              typentry->typelem, typmod,
                              proc);
    }
    else if ((trfuncid = get_transform_tosql(typeOid,
                                             proc->langid,
                                             proc->trftypes)))
    {
        arg->func = PLyObject_ToTransform;
        fmgr_info_cxt(trfuncid, &arg->u.transform.typtransform, arg_mcxt);
    }
    else if (typtype == TYPTYPE_COMPOSITE)
    {
        /* Named composite type, or RECORD */
        arg->func = PLyObject_ToComposite;
        /* We'll set up the per-field data later */
        arg->u.tuple.recdesc = NULL;
        arg->u.tuple.typentry = typentry;
        arg->u.tuple.tupdescid = INVALID_TUPLEDESC_IDENTIFIER;
        arg->u.tuple.atts = NULL;
        arg->u.tuple.natts = 0;
        /* Mark this invalid till needed, too */
        arg->u.tuple.recinfunc.fn_oid = InvalidOid;
    }
    else
    {
        /* Scalar type, but we have a couple of special cases */
        switch (typeOid)
        {
            case BOOLOID:
                arg->func = PLyObject_ToBool;
                break;
            case BYTEAOID:
                arg->func = PLyObject_ToBytea;
                break;
            default:
                arg->func = PLyObject_ToScalar;
                getTypeInputInfo(typeOid, &typinput, &arg->u.scalar.typioparam);
                fmgr_info_cxt(typinput, &arg->u.scalar.typfunc, arg_mcxt);
                break;
        }
    }
}

/*
 * Recursively initialize the PLyDatumToOb structure(s) needed to construct
 * a Python value from a SQL value of the specified typeOid/typmod.
 * (But note that at this point we may have RECORDOID/-1, ie, an indeterminate
 * record type.)
 * proc is used to look up transform functions.
 */
void
PLy_input_setup_func(PLyDatumToOb *arg, MemoryContext arg_mcxt,
                     Oid typeOid, int32 typmod,
                     PLyProcedure *proc)
{
    TypeCacheEntry *typentry;
    char        typtype;
    Oid         trfuncid;
    Oid         typoutput;
    bool        typisvarlena;

    /* Since this is recursive, it could theoretically be driven to overflow */
    check_stack_depth();

    arg->typoid = typeOid;
    arg->typmod = typmod;
    arg->mcxt = arg_mcxt;

    /*
     * Fetch typcache entry for the target type, asking for whatever info
     * we'll need later.  RECORD is a special case: just treat it as composite
     * without bothering with the typcache entry.
     */
    if (typeOid != RECORDOID)
    {
        typentry = lookup_type_cache(typeOid, TYPECACHE_DOMAIN_BASE_INFO);
        typtype = typentry->typtype;
        arg->typbyval = typentry->typbyval;
        arg->typlen = typentry->typlen;
        arg->typalign = typentry->typalign;
    }
    else
    {
        typentry = NULL;
        typtype = TYPTYPE_COMPOSITE;
        /* hard-wired knowledge about type RECORD: */
        arg->typbyval = false;
        arg->typlen = -1;
        arg->typalign = 'd';
    }

    /*
     * Choose conversion method.  Note that transform functions are checked
     * for composite and scalar types, but not for arrays or domains.  This is
     * somewhat historical, but we'd have a problem allowing them on domains,
     * since we drill down through all levels of a domain nest without looking
     * at the intermediate levels at all.
     */
    if (typtype == TYPTYPE_DOMAIN)
    {
        /* Domain --- we don't care, just recurse down to the base type */
        PLy_input_setup_func(arg, arg_mcxt,
                             typentry->domainBaseType,
                             typentry->domainBaseTypmod,
                             proc);
    }
    else if (typentry &&
             OidIsValid(typentry->typelem) && typentry->typlen == -1)
    {
        /* Standard varlena array (cf. get_element_type) */
        arg->func = PLyList_FromArray;
        /* Recursively set up conversion info for the element type */
        arg->u.array.elm = (PLyDatumToOb *)
            MemoryContextAllocZero(arg_mcxt, sizeof(PLyDatumToOb));
        PLy_input_setup_func(arg->u.array.elm, arg_mcxt,
                             typentry->typelem, typmod,
                             proc);
    }
    else if ((trfuncid = get_transform_fromsql(typeOid,
                                               proc->langid,
                                               proc->trftypes)))
    {
        arg->func = PLyObject_FromTransform;
        fmgr_info_cxt(trfuncid, &arg->u.transform.typtransform, arg_mcxt);
    }
    else if (typtype == TYPTYPE_COMPOSITE)
    {
        /* Named composite type, or RECORD */
        arg->func = PLyDict_FromComposite;
        /* We'll set up the per-field data later */
        arg->u.tuple.recdesc = NULL;
        arg->u.tuple.typentry = typentry;
        arg->u.tuple.tupdescid = INVALID_TUPLEDESC_IDENTIFIER;
        arg->u.tuple.atts = NULL;
        arg->u.tuple.natts = 0;
    }
    else
    {
        /* Scalar type, but we have a couple of special cases */
        switch (typeOid)
        {
            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_FromScalar;
                getTypeOutputInfo(typeOid, &typoutput, &typisvarlena);
                fmgr_info_cxt(typoutput, &arg->u.scalar.typfunc, arg_mcxt);
                break;
        }
    }
}


/*
 * Special-purpose input converters.
 */

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)
{
    return PyLong_FromLongLong(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);
}


/*
 * Generic input conversion using a SQL type's output function.
 */
static PyObject *
PLyString_FromScalar(PLyDatumToOb *arg, Datum d)
{
    char       *x = OutputFunctionCall(&arg->u.scalar.typfunc, d);
    PyObject   *r = PyString_FromString(x);

    pfree(x);
    return r;
}

/*
 * Convert using a from-SQL transform function.
 */
static PyObject *
PLyObject_FromTransform(PLyDatumToOb *arg, Datum d)
{
    Datum       t;

    t = FunctionCall1(&arg->u.transform.typtransform, d);
    return (PyObject *) DatumGetPointer(t);
}

/*
 * Convert a SQL array to a Python list.
 */
static PyObject *
PLyList_FromArray(PLyDatumToOb *arg, Datum d)
{
    ArrayType  *array = DatumGetArrayTypeP(d);
    PLyDatumToOb *elm = arg->u.array.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 (!list)
        return NULL;

    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 composite SQL value to a Python dict.
 */
static PyObject *
PLyDict_FromComposite(PLyDatumToOb *arg, Datum d)
{
    PyObject   *dict;
    HeapTupleHeader td;
    Oid         tupType;
    int32       tupTypmod;
    TupleDesc   tupdesc;
    HeapTupleData tmptup;

    td = DatumGetHeapTupleHeader(d);
    /* Extract rowtype info and find a tupdesc */
    tupType = HeapTupleHeaderGetTypeId(td);
    tupTypmod = HeapTupleHeaderGetTypMod(td);
    tupdesc = lookup_rowtype_tupdesc(tupType, tupTypmod);

    /* Set up I/O funcs if not done yet */
    PLy_input_setup_tuple(arg, tupdesc,
                          PLy_current_execution_context()->curr_proc);

    /* Build a temporary HeapTuple control structure */
    tmptup.t_len = HeapTupleHeaderGetDatumLength(td);
    tmptup.t_data = td;

    dict = PLyDict_FromTuple(arg, &tmptup, tupdesc);

    ReleaseTupleDesc(tupdesc);

    return dict;
}

/*
 * Transform a tuple into a Python dict object.
 */
static PyObject *
PLyDict_FromTuple(PLyDatumToOb *arg, HeapTuple tuple, TupleDesc desc)
{
    PyObject   *volatile dict;

    /* Simple sanity check that desc matches */
    Assert(desc->natts == arg->u.tuple.natts);

    dict = PyDict_New();
    if (dict == NULL)
        return NULL;

    PG_TRY();
    {
        int         i;

        for (i = 0; i < arg->u.tuple.natts; i++)
        {
            PLyDatumToOb *att = &arg->u.tuple.atts[i];
            Form_pg_attribute attr = TupleDescAttr(desc, i);
            char       *key;
            Datum       vattr;
            bool        is_null;
            PyObject   *value;

            if (attr->attisdropped)
                continue;

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

            if (is_null)
                PyDict_SetItemString(dict, key, Py_None);
            else
            {
                value = att->func(att, vattr);
                PyDict_SetItemString(dict, key, value);
                Py_DECREF(value);
            }
        }
    }
    PG_CATCH();
    {
        Py_DECREF(dict);
        PG_RE_THROW();
    }
    PG_END_TRY();

    return dict;
}

/*
 * 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, PyObject *plrv,
                 bool *isnull, bool inarray)
{
    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;
    return BoolGetDatum(PyObject_IsTrue(plrv));
}

/*
 * 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, PyObject *plrv,
                  bool *isnull, bool inarray)
{
    PyObject   *volatile plrv_so = NULL;
    Datum       rv;

    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;

    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);

    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, PyObject *plrv,
                      bool *isnull, bool inarray)
{
    Datum       rv;
    TupleDesc   desc;

    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;

    /*
     * The string conversion case doesn't require a tupdesc, nor per-field
     * conversion data, so just go for it if that's the case to use.
     */
    if (PyString_Check(plrv) || PyUnicode_Check(plrv))
        return PLyString_ToComposite(arg, plrv, inarray);

    /*
     * If we're dealing with a named composite type, we must look up the
     * tupdesc every time, to protect against possible changes to the type.
     * RECORD types can't change between calls; but we must still be willing
     * to set up the info the first time, if nobody did yet.
     */
    if (arg->typoid != RECORDOID)
    {
        desc = lookup_rowtype_tupdesc(arg->typoid, arg->typmod);
        /* We should have the descriptor of the type's typcache entry */
        Assert(desc == arg->u.tuple.typentry->tupDesc);
        /* Detect change of descriptor, update cache if needed */
        if (arg->u.tuple.tupdescid != arg->u.tuple.typentry->tupDesc_identifier)
        {
            PLy_output_setup_tuple(arg, desc,
                                   PLy_current_execution_context()->curr_proc);
            arg->u.tuple.tupdescid = arg->u.tuple.typentry->tupDesc_identifier;
        }
    }
    else
    {
        desc = arg->u.tuple.recdesc;
        if (desc == NULL)
        {
            desc = lookup_rowtype_tupdesc(arg->typoid, arg->typmod);
            arg->u.tuple.recdesc = desc;
        }
        else
        {
            /* Pin descriptor to match unpin below */
            PinTupleDesc(desc);
        }
    }

    /* Simple sanity check on our caching */
    Assert(desc->natts == arg->u.tuple.natts);

    /*
     * Convert, using the appropriate method depending on the type of the
     * supplied Python object.
     */
    if (PySequence_Check(plrv))
        /* composite type as sequence (tuple, list etc) */
        rv = PLySequence_ToComposite(arg, desc, plrv);
    else if (PyMapping_Check(plrv))
        /* composite type as mapping (currently only dict) */
        rv = PLyMapping_ToComposite(arg, desc, plrv);
    else
        /* returned as smth, must provide method __getattr__(name) */
        rv = PLyGenericObject_ToComposite(arg, desc, plrv, inarray);

    ReleaseTupleDesc(desc);

    return rv;
}


/*
 * Convert Python object to C string in server encoding.
 *
 * Note: this is exported for use by add-on transform modules.
 */
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 output conversion function: convert PyObject to cstring and
 * cstring into PostgreSQL type.
 */
static Datum
PLyObject_ToScalar(PLyObToDatum *arg, PyObject *plrv,
                   bool *isnull, bool inarray)
{
    char       *str;

    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;

    str = PLyObject_AsString(plrv);

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


/*
 * Convert to a domain type.
 */
static Datum
PLyObject_ToDomain(PLyObToDatum *arg, PyObject *plrv,
                   bool *isnull, bool inarray)
{
    Datum       result;
    PLyObToDatum *base = arg->u.domain.base;

    result = base->func(base, plrv, isnull, inarray);
    domain_check(result, *isnull, arg->typoid,
                 &arg->u.domain.domain_info, arg->mcxt);
    return result;
}


/*
 * Convert using a to-SQL transform function.
 */
static Datum
PLyObject_ToTransform(PLyObToDatum *arg, PyObject *plrv,
                      bool *isnull, bool inarray)
{
    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;
    return FunctionCall1(&arg->u.transform.typtransform, PointerGetDatum(plrv));
}


/*
 * Convert Python sequence to SQL array.
 */
static Datum
PLySequence_ToArray(PLyObToDatum *arg, PyObject *plrv,
                    bool *isnull, bool inarray)
{
    ArrayType  *array;
    int         i;
    Datum      *elems;
    bool       *nulls;
    int64       len;
    int         ndim;
    int         dims[MAXDIM];
    int         lbs[MAXDIM];
    int         currelem;
    PyObject   *pyptr = plrv;
    PyObject   *next;

    if (plrv == Py_None)
    {
        *isnull = true;
        return (Datum) 0;
    }
    *isnull = false;

    /*
     * 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, "could not 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->u.array.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,
                               arg->u.array.elmbasetype,
                               arg->u.array.elm->typlen,
                               arg->u.array.elm->typbyval,
                               arg->u.array.elm->typalign);

    return PointerGetDatum(array);
}

/*
 * 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])
        ereport(ERROR,
                (errmsg("wrong length of inner sequence: has length %d, but %d was expected",
                        (int) PySequence_Length(list), dims[dim]),
                 (errdetail("To construct a multidimensional array, the inner sequences must all have the same length."))));

    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);

            elems[*currelem] = elm->func(elm, obj, &nulls[*currelem], true);
            Py_XDECREF(obj);
            (*currelem)++;
        }
    }
}


/*
 * Convert a Python string to composite, using record_in.
 */
static Datum
PLyString_ToComposite(PLyObToDatum *arg, PyObject *string, bool inarray)
{
    char       *str;

    /*
     * Set up call data for record_in, if we didn't already.  (We can't just
     * use DirectFunctionCall, because record_in needs a fn_extra field.)
     */
    if (!OidIsValid(arg->u.tuple.recinfunc.fn_oid))
        fmgr_info_cxt(F_RECORD_IN, &arg->u.tuple.recinfunc, arg->mcxt);

    str = PLyObject_AsString(string);

    /*
     * 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)
    {
        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->u.tuple.recinfunc,
                             str,
                             arg->typoid,
                             arg->typmod);
}


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

    Assert(PyMapping_Check(mapping));

    /* 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;
        Form_pg_attribute attr = TupleDescAttr(desc, i);

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

        key = NameStr(attr->attname);
        value = NULL;
        att = &arg->u.tuple.atts[i];
        PG_TRY();
        {
            value = PyMapping_GetItemString(mapping, key);
            if (!value)
                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.")));

            values[i] = att->func(att, value, &nulls[i], false);

            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(PLyObToDatum *arg, 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 (!TupleDescAttr(desc, 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")));

    /* 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 (TupleDescAttr(desc, i)->attisdropped)
        {
            values[i] = (Datum) 0;
            nulls[i] = true;
            continue;
        }

        value = NULL;
        att = &arg->u.tuple.atts[i];
        PG_TRY();
        {
            value = PySequence_GetItem(sequence, idx);
            Assert(value);

            values[i] = att->func(att, value, &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(PLyObToDatum *arg, TupleDesc desc, PyObject *object, bool inarray)
{
    Datum       result;
    HeapTuple   tuple;
    Datum      *values;
    bool       *nulls;
    volatile int i;

    /* 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;
        Form_pg_attribute attr = TupleDescAttr(desc, i);

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

        key = NameStr(attr->attname);
        value = NULL;
        att = &arg->u.tuple.atts[i];
        PG_TRY();
        {
            value = PyObject_GetAttrString(object, key);
            if (!value)
            {
                /*
                 * 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_ToScalar().
                 */
                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.")));
            }

            values[i] = att->func(att, value, &nulls[i], false);

            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;
}