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Jython is an implementation of the high-level, dynamic, object-oriented
language Python written in 100% Pure Java, and seamlessly integrated with
the Java platform. It thus allows you to run Python on any Java platform.
/*
* Jython Database Specification API 2.0
*
*
* Copyright (c) 2001 brian zimmer
*
*/
package com.ziclix.python.sql;
import org.python.core.Py;
import org.python.core.PyException;
import org.python.core.PyInteger;
import org.python.core.PyList;
import org.python.core.PyObject;
import org.python.core.PyTuple;
import java.sql.CallableStatement;
import java.sql.DatabaseMetaData;
import java.sql.ResultSet;
import java.sql.ResultSetMetaData;
import java.sql.SQLException;
import java.sql.SQLWarning;
import java.sql.Types;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;
import java.util.Set;
/**
* The responsibility of a Fetch instance is to manage the iteration of a
* ResultSet. Two different alogorithms are available: static or dynamic.
*
* Static The static variety iterates the entire set immediately,
* creating the necessary Jython objects and storing them. It is able to
* immediately close the ResultSet so a call to close() is essentially a no-op
* from a database resource perspective (it does clear the results list however).
* This approach also allows for the correct rowcount to be determined since
* the entire result set has been iterated.
*
* Dynamic The dynamic variety iterates the result set only as requested.
* This holds a bit truer to the intent of the API as the fetch*() methods actually
* fetch when instructed. This is especially useful for managing exeedingly large
* results, but is unable to determine the rowcount without having worked through
* the entire result set. The other disadvantage is the ResultSet remains open
* throughout the entire iteration. So the tradeoff is in open database resources
* versus JVM resources since the application can keep constant space if it doesn't
* require the entire result set be presented as one.
*
* @author brian zimmer
*/
abstract public class Fetch {
/**
* The total number of rows in the result set.
*
* Note: since JDBC provides no means to get this information without iterating
* the entire result set, only those fetches which build the result statically
* will have an accurate row count.
*/
protected int rowcount;
/**
* The current row of the cursor (-1 if off either end).
*/
protected int rownumber;
/**
* Field cursor
*/
private DataHandler datahandler;
/**
* Field description
*/
protected PyObject description;
/**
* A list of warning listeners.
*/
private List listeners;
/**
* Constructor Fetch
*
* @param datahandler
*/
protected Fetch(DataHandler datahandler) {
this.rowcount = -1;
this.rownumber = -1;
this.description = Py.None;
this.datahandler = datahandler;
this.listeners = new ArrayList(3);
}
/**
* Method newFetch
*
* @param datahandler
* @param dynamic
* @return Fetch
*/
public static Fetch newFetch(DataHandler datahandler, boolean dynamic) {
if (dynamic) {
return new DynamicFetch(datahandler);
} else {
return new StaticFetch(datahandler);
}
}
/**
* The number of rows in the current result set.
*/
public int getRowCount() {
return this.rowcount;
}
/**
* The description of each column, in order, for the data in the result
* set.
*/
public PyObject getDescription() {
return this.description;
}
/**
* Create the results after a successful execution and manages the result set.
*
* @param resultSet
*/
abstract public void add(ResultSet resultSet);
/**
* Create the results after a successful execution and manages the result set.
* Optionally takes a set of JDBC-indexed columns to automatically set to None
* primarily to support getTypeInfo() which sets a column type of a number but
* doesn't use the value so a driver is free to put anything it wants there.
*
* @param resultSet
* @param skipCols JDBC-indexed set of columns to be skipped
*/
abstract public void add(ResultSet resultSet, Set skipCols);
/**
* Method add
*
* @param callableStatement
* @param procedure
* @param params
*/
abstract public void add(CallableStatement callableStatement, Procedure procedure,
PyObject params);
/**
* Fetch the next row of a query result set, returning a single sequence,
* or None when no more data is available.
*
* An Error (or subclass) exception is raised if the previous call to
* executeXXX() did not produce any result set or no call was issued yet.
*
* @return a single sequence from the result set, or None when no more data is available
*/
public PyObject fetchone() {
PyObject sequence = fetchmany(1);
if (sequence.__len__() == 1) {
return sequence.__getitem__(0);
} else {
return Py.None;
}
}
/**
* Fetch all (remaining) rows of a query result, returning them as a sequence
* of sequences (e.g. a list of tuples). Note that the cursor's arraysize attribute
* can affect the performance of this operation.
*
* An Error (or subclass) exception is raised if the previous call to executeXXX()
* did not produce any result set or no call was issued yet.
*
* @return a sequence of sequences from the result set, or None when no more data is available
*/
public abstract PyObject fetchall();
/**
* Fetch the next set of rows of a query result, returning a sequence of
* sequences (e.g. a list of tuples). An empty sequence is returned when
* no more rows are available.
*
* The number of rows to fetch per call is specified by the parameter. If
* it is not given, the cursor's arraysize determines the number of rows
* to be fetched. The method should try to fetch as many rows as indicated
* by the size parameter. If this is not possible due to the specified number
* of rows not being available, fewer rows may be returned.
*
* An Error (or subclass) exception is raised if the previous call to executeXXX()
* did not produce any result set or no call was issued yet.
*
* Note there are performance considerations involved with the size parameter.
* For optimal performance, it is usually best to use the arraysize attribute.
* If the size parameter is used, then it is best for it to retain the same value
* from one fetchmany() call to the next.
*
* @return a sequence of sequences from the result set, or None when no more data is available
*/
public abstract PyObject fetchmany(int size);
/**
* Move the result pointer to the next set if available.
*
* @return true if more sets exist, else None
*/
public abstract PyObject nextset();
/**
* Scroll the cursor in the result set to a new position according
* to mode.
*
* If mode is 'relative' (default), value is taken as offset to
* the current position in the result set, if set to 'absolute',
* value states an absolute target position.
*
* An IndexError should be raised in case a scroll operation would
* leave the result set. In this case, the cursor position is left
* undefined (ideal would be to not move the cursor at all).
*
* Note: This method should use native scrollable cursors, if
* available, or revert to an emulation for forward-only
* scrollable cursors. The method may raise NotSupportedErrors to
* signal that a specific operation is not supported by the
* database (e.g. backward scrolling).
*
* @param value
* @param mode
*/
public abstract void scroll(int value, String mode);
/**
* Cleanup any resources.
*/
public void close() throws SQLException {
this.listeners.clear();
}
/**
* Builds a tuple containing the meta-information about each column.
*
* (name, type_code, display_size, internal_size, precision, scale, null_ok)
*
* precision and scale are only available for numeric types
*/
protected PyObject createDescription(ResultSetMetaData meta) throws SQLException {
PyObject metadata = new PyList();
for (int i = 1; i <= meta.getColumnCount(); i++) {
PyObject[] a = new PyObject[7];
a[0] = Py.newUnicode(meta.getColumnLabel(i));
a[1] = Py.newInteger(meta.getColumnType(i));
a[2] = Py.newInteger(meta.getColumnDisplaySize(i));
a[3] = Py.None;
switch (meta.getColumnType(i)) {
case Types.BIGINT:
case Types.BIT:
case Types.DECIMAL:
case Types.NUMERIC:
case Types.DOUBLE:
case Types.FLOAT:
case Types.INTEGER:
case Types.SMALLINT:
case Types.TINYINT:
a[4] = Py.newInteger(meta.getPrecision(i));
a[5] = Py.newInteger(meta.getScale(i));
break;
default :
a[4] = Py.None;
a[5] = Py.None;
break;
}
a[6] = Py.newInteger(meta.isNullable(i));
((PyList) metadata).append(new PyTuple(a));
}
return metadata;
}
/**
* Builds a tuple containing the meta-information about each column.
*
* (name, type_code, display_size, internal_size, precision, scale, null_ok)
*
* precision and scale are only available for numeric types
*/
protected PyObject createDescription(Procedure procedure) throws SQLException {
PyObject metadata = new PyList();
for (int i = 0, len = procedure.columns.__len__(); i < len; i++) {
PyObject column = procedure.columns.__getitem__(i);
int colType = column.__getitem__(Procedure.COLUMN_TYPE).asInt();
switch (colType) {
case DatabaseMetaData.procedureColumnReturn:
PyObject[] a = new PyObject[7];
a[0] = column.__getitem__(Procedure.NAME);
a[1] = column.__getitem__(Procedure.DATA_TYPE);
a[2] = Py.newInteger(-1);
a[3] = column.__getitem__(Procedure.LENGTH);
switch (a[1].asInt()) {
case Types.BIGINT:
case Types.BIT:
case Types.DECIMAL:
case Types.DOUBLE:
case Types.FLOAT:
case Types.INTEGER:
case Types.SMALLINT:
a[4] = column.__getitem__(Procedure.PRECISION);
a[5] = column.__getitem__(Procedure.SCALE);
break;
default :
a[4] = Py.None;
a[5] = Py.None;
break;
}
int nullable = column.__getitem__(Procedure.NULLABLE).asInt();
a[6] = (nullable == DatabaseMetaData.procedureNullable) ? Py.One : Py.Zero;
((PyList) metadata).append(new PyTuple(a));
break;
}
}
return metadata;
}
/**
* Method createResults
*
* @param callableStatement
* @param procedure
* @param params
* @return PyObject
* @throws SQLException
*/
protected PyObject createResults(CallableStatement callableStatement, Procedure procedure,
PyObject params) throws SQLException {
PyList results = new PyList();
for (int i = 0, j = 0, len = procedure.columns.__len__(); i < len; i++) {
PyObject obj = Py.None;
PyObject column = procedure.columns.__getitem__(i);
int colType = column.__getitem__(Procedure.COLUMN_TYPE).asInt();
int dataType = column.__getitem__(Procedure.DATA_TYPE).asInt();
switch (colType) {
case DatabaseMetaData.procedureColumnIn:
j++;
break;
case DatabaseMetaData.procedureColumnOut:
case DatabaseMetaData.procedureColumnInOut:
obj = datahandler.getPyObject(callableStatement, i + 1, dataType);
params.__setitem__(j++, obj);
break;
case DatabaseMetaData.procedureColumnReturn:
obj = datahandler.getPyObject(callableStatement, i + 1, dataType);
// Oracle sends ResultSets as a return value
Object rs = obj.__tojava__(ResultSet.class);
if (rs == Py.NoConversion) {
results.append(obj);
} else {
add((ResultSet) rs);
}
break;
}
}
if (results.__len__() == 0) {
return results;
}
PyList ret = new PyList();
ret.append(PyTuple.fromIterable(results));
return ret;
}
/**
* Creates the results of a query. Iterates through the list and builds the tuple.
*
* @param set result set
* @param skipCols set of JDBC-indexed columns to automatically set to None
* @return a list of tuples of the results
* @throws SQLException
*/
protected PyList createResults(ResultSet set, Set skipCols, PyObject metaData)
throws SQLException {
PyList res = new PyList();
while (set.next()) {
PyObject tuple = createResult(set, skipCols, metaData);
res.append(tuple);
}
return res;
}
/**
* Creates the individual result row from the current ResultSet row.
*
* @param set result set
* @param skipCols set of JDBC-indexed columns to automatically set to None
* @return a tuple of the results
* @throws SQLException
*/
protected PyTuple createResult(ResultSet set, Set skipCols, PyObject metaData)
throws SQLException {
int descriptionLength = metaData.__len__();
PyObject[] row = new PyObject[descriptionLength];
for (int i = 0; i < descriptionLength; i++) {
if (skipCols != null && skipCols.contains(i + 1)) {
row[i] = Py.None;
} else {
int type = ((PyInteger) metaData.__getitem__(i).__getitem__(1)).getValue();
row[i] = datahandler.getPyObject(set, i + 1, type);
}
}
SQLWarning warning = set.getWarnings();
if (warning != null) {
fireWarning(warning);
}
return new PyTuple(row);
}
protected void fireWarning(SQLWarning warning) {
WarningEvent event = new WarningEvent(this, warning);
for (WarningListener listener : listeners) {
try {
listener.warning(event);
} catch (Throwable t) {
// ok
}
}
}
public void addWarningListener(WarningListener listener) {
this.listeners.add(listener);
}
public boolean removeWarningListener(WarningListener listener) {
return this.listeners.remove(listener);
}
}
/**
* This version of fetch builds the results statically. This consumes more resources but
* allows for efficient closing of database resources because the contents of the result
* set are immediately consumed. It also allows for an accurate rowcount attribute, whereas
* a dynamic query is unable to provide this information until all the results have been
* consumed.
*/
class StaticFetch extends Fetch {
/**
* Field results
*/
protected List results;
/**
* Field descriptions
*/
protected List descriptions;
/**
* Construct a static fetch. The entire result set is iterated as it
* is added and the result set is immediately closed.
*/
public StaticFetch(DataHandler datahandler) {
super(datahandler);
this.results = new LinkedList();
this.descriptions = new LinkedList();
}
/**
* Method add
*
* @param resultSet
*/
@Override
public void add(ResultSet resultSet) {
this.add(resultSet, null);
}
/**
* Method add
*
* @param resultSet
* @param skipCols
*/
@Override
public void add(ResultSet resultSet, Set skipCols) {
try {
if (resultSet != null && resultSet.getMetaData() != null) {
PyObject metadata = this.createDescription(resultSet.getMetaData());
PyObject result = this.createResults(resultSet, skipCols, metadata);
this.results.add(result);
this.descriptions.add(metadata);
// we want the rowcount of the first result set
this.rowcount = this.results.get(0).__len__();
// we want the description of the first result set
this.description = this.descriptions.get(0);
// set the current rownumber
this.rownumber = 0;
}
} catch (PyException e) {
throw e;
} catch (Throwable e) {
throw zxJDBC.makeException(e);
} finally {
try {
resultSet.close();
} catch (Throwable e) {
}
}
}
/**
* Method add
*
* @param callableStatement
* @param procedure
* @param params
*/
@Override
public void add(CallableStatement callableStatement, Procedure procedure, PyObject params) {
try {
PyObject result = this.createResults(callableStatement, procedure, params);
if (result.__len__() > 0) {
this.results.add(result);
this.descriptions.add(this.createDescription(procedure));
// we want the rowcount of the first result set
this.rowcount = this.results.get(0).__len__();
// we want the description of the first result set
this.description = this.descriptions.get(0);
// set the current rownumber
this.rownumber = 0;
}
} catch (PyException e) {
throw e;
} catch (Throwable e) {
throw zxJDBC.makeException(e);
}
}
/**
* Fetch all (remaining) rows of a query result, returning them as a sequence
* of sequences (e.g. a list of tuples). Note that the cursor's arraysize attribute
* can affect the performance of this operation.
*
* An Error (or subclass) exception is raised if the previous call to executeXXX()
* did not produce any result set or no call was issued yet.
*
* @return a sequence of sequences from the result set, or an empty sequence when
* no more data is available
*/
@Override
public PyObject fetchall() {
return fetchmany(this.rowcount);
}
/**
* Fetch the next set of rows of a query result, returning a sequence of
* sequences (e.g. a list of tuples). An empty sequence is returned when
* no more rows are available.
*
* The number of rows to fetch per call is specified by the parameter. If
* it is not given, the cursor's arraysize determines the number of rows
* to be fetched. The method should try to fetch as many rows as indicated
* by the size parameter. If this is not possible due to the specified number
* of rows not being available, fewer rows may be returned.
*
* An Error (or subclass) exception is raised if the previous call to executeXXX()
* did not produce any result set or no call was issued yet.
*
* Note there are performance considerations involved with the size parameter.
* For optimal performance, it is usually best to use the arraysize attribute.
* If the size parameter is used, then it is best for it to retain the same value
* from one fetchmany() call to the next.
*
* @return a sequence of sequences from the result set, or an empty sequence when
* no more data is available
*/
@Override
public PyObject fetchmany(int size) {
if (results == null || results.size() == 0) {
throw zxJDBC.makeException(zxJDBC.DatabaseError, "no results");
}
PyObject res = new PyList();
PyObject current = results.get(0);
if (size <= 0) {
size = this.rowcount;
}
if (this.rownumber < this.rowcount) {
res = current.__getslice__(Py.newInteger(this.rownumber),
Py.newInteger(this.rownumber + size), Py.One);
this.rownumber += size;
}
return res;
}
/**
* Method scroll
*
* @param value
* @param mode 'relative' or 'absolute'
*/
@Override
public void scroll(int value, String mode) {
int pos;
if ("relative".equals(mode)) {
pos = this.rownumber + value;
} else if ("absolute".equals(mode)) {
pos = value;
} else {
throw zxJDBC.makeException(zxJDBC.ProgrammingError, "invalid cursor scroll mode ["
+ mode + "]");
}
if (pos >= 0 && pos < this.rowcount) {
this.rownumber = pos;
} else {
throw zxJDBC.makeException(Py.IndexError, "cursor index [" + pos + "] out of range");
}
}
/**
* Move the result pointer to the next set if available.
*
* @return true if more sets exist, else None
*/
@Override
public PyObject nextset() {
PyObject next = Py.None;
if (results != null && results.size() > 1) {
this.results.remove(0);
this.descriptions.remove(0);
next = this.results.get(0);
this.description = this.descriptions.get(0);
this.rowcount = next.__len__();
this.rownumber = 0;
}
return next == Py.None ? Py.None : Py.One;
}
/**
* Remove the results.
*/
@Override
public void close() throws SQLException {
super.close();
this.rownumber = -1;
this.results.clear();
}
}
/**
* Dynamically construct the results from an execute*(). The static version builds the entire
* result set immediately upon completion of the query, however in some circumstances, this
* requires far too many resources to be efficient. In this version of the fetch the resources
* remain constant. The dis-advantage to this approach from an API perspective is its impossible
* to generate an accurate rowcount since not all the rows have been consumed.
*/
class DynamicFetch extends Fetch {
/**
* Field skipCols
*/
protected Set skipCols;
/**
* Field resultSet
*/
protected ResultSet resultSet;
/**
* Construct a dynamic fetch.
*/
public DynamicFetch(DataHandler datahandler) {
super(datahandler);
}
/**
* Add the result set to the results. If more than one result
* set is attempted to be added, an Error is raised since JDBC
* requires that only one ResultSet be iterated for one Statement
* at any one time. Since this is a dynamic iteration, it precludes
* the addition of more than one result set.
*/
@Override
public void add(ResultSet resultSet) {
add(resultSet, null);
}
/**
* Add the result set to the results. If more than one result
* set is attempted to be added, an Error is raised since JDBC
* requires that only one ResultSet be iterated for one Statement
* at any one time. Since this is a dynamic iteration, it precludes
* the addition of more than one result set.
*/
@Override
public void add(ResultSet resultSet, Set skipCols) {
if (this.resultSet != null) {
throw zxJDBC.makeException(zxJDBC.getString("onlyOneResultSet"));
}
try {
if (resultSet != null && resultSet.getMetaData() != null) {
if (this.description == Py.None) {
this.description = this.createDescription(resultSet.getMetaData());
}
this.resultSet = resultSet;
this.skipCols = skipCols;
// it would be more compliant if we knew the resultSet actually
// contained some rows, but since we don't make a stab at it so
// everything else looks better
this.rowcount = 0;
this.rownumber = 0;
}
} catch (PyException e) {
throw e;
} catch (Throwable e) {
throw zxJDBC.makeException(e);
}
}
/**
* Method add
*
* @param callableStatement
* @param procedure
* @param params
*/
@Override
public void add(CallableStatement callableStatement, Procedure procedure, PyObject params) {
throw zxJDBC.makeException(zxJDBC.NotSupportedError,
zxJDBC.getString("nocallprocsupport"));
}
/**
* Iterate the remaining contents of the ResultSet and return.
*/
@Override
public PyObject fetchall() {
return fetch(0, true);
}
/**
* Iterate up to size rows remaining in the ResultSet and return.
*/
@Override
public PyObject fetchmany(int size) {
return fetch(size, false);
}
/**
* Internal use only. If all is true, return everything
* that's left in the result set, otherwise return up to size. Fewer
* than size may be returned if fewer than size results are left in
* the set.
*/
private PyObject fetch(int size, boolean all) {
PyList res = new PyList();
if (this.resultSet == null) {
throw zxJDBC.makeException(zxJDBC.DatabaseError, "no results");
}
try {
all = (size < 0) ? true : all;
while ((size-- > 0 || all) && this.resultSet.next()) {
PyTuple tuple = createResult(this.resultSet, this.skipCols, this.description);
res.append(tuple);
this.rowcount++;
this.rownumber = this.resultSet.getRow();
}
} catch (AbstractMethodError e) {
throw zxJDBC.makeException(zxJDBC.NotSupportedError,
zxJDBC.getString("nodynamiccursors"));
} catch (PyException e) {
throw e;
} catch (Throwable e) {
throw zxJDBC.makeException(e);
}
return res;
}
/**
* Always returns None.
*/
@Override
public PyObject nextset() {
return Py.None;
}
/**
* Method scroll
*
* @param value
* @param mode
*/
@Override
public void scroll(int value, String mode) {
try {
int type = this.resultSet.getType();
if (type != ResultSet.TYPE_FORWARD_ONLY || value > 0) {
if ("relative".equals(mode)) {
if (value < 0) {
value = Math.abs(this.rownumber + value);
} else if (value > 0) {
value = this.rownumber + value + 1;
}
} else if ("absolute".equals(mode)) {
if (value < 0) {
throw zxJDBC.makeException(Py.IndexError, "cursor index [" + value
+ "] out of range");
}
} else {
throw zxJDBC.makeException(zxJDBC.ProgrammingError,
"invalid cursor scroll mode [" + mode + "]");
}
if (value == 0) {
this.resultSet.beforeFirst();
} else {
if (!this.resultSet.absolute(value)) {
throw zxJDBC.makeException(Py.IndexError, "cursor index [" + value
+ "] out of range");
}
}
// since .rownumber is the *next* row, then the JDBC value suits us fine
this.rownumber = this.resultSet.getRow();
} else {
String msg = "dynamic result set of type [" + type
+ "] does not support scrolling";
throw zxJDBC.makeException(zxJDBC.NotSupportedError, msg);
}
} catch (AbstractMethodError e) {
throw zxJDBC.makeException(zxJDBC.NotSupportedError,
zxJDBC.getString("nodynamiccursors"));
} catch (SQLException e) {
throw zxJDBC.makeException(e);
} catch (Throwable t) {
throw zxJDBC.makeException(t);
}
}
/**
* Close the underlying ResultSet.
*/
@Override
public void close() throws SQLException {
super.close();
if (this.resultSet == null) {
return;
}
this.rownumber = -1;
try {
this.resultSet.close();
} finally {
this.resultSet = null;
}
}
}