# Source code for sqlalchemy_utils.functions.database

    import collections
    import itertools
    import os
    from copy import copy

    import sqlalchemy as sa
    from sqlalchemy.engine.url import make_url
    from sqlalchemy.exc import OperationalError, ProgrammingError

    from ..expressions import explain_analyze
    from ..utils import starts_with
    from .orm import quote

    class PlanAnalysis(object):
        def __init__(self, plan):
            self.plan = plan

        @property
        def node_types(self):
            types = [self.plan['Node Type']]
            if 'Plans' in self.plan:
                for plan in self.plan['Plans']:
                    analysis = PlanAnalysis(plan)
                    types.extend(analysis.node_types)
            return types

    class QueryAnalysis(object):
        def __init__(self, result_set):
            self.plan = result_set[0]['Plan']
            if 'Total Runtime' in result_set[0]:
                # PostgreSQL versions < 9.4
                self.runtime = result_set[0]['Total Runtime']
            else:
                # PostgreSQL versions >= 9.4
                self.runtime = (
                    result_set[0]['Execution Time'] +
                    result_set[0]['Planning Time']
                )

        @property
        def node_types(self):
            return list(PlanAnalysis(self.plan).node_types)

        def __repr__(self):
            return '<QueryAnalysis runtime=%r>' % self.runtime

    def analyze(conn, query):
        """
        Analyze query using given connection and return :class:`QueryAnalysis`
        object. Analysis is performed using database specific EXPLAIN ANALYZE
        construct and then examining the results into structured format. Currently
        only PostgreSQL is supported.

        Getting query runtime (in database level) ::

            from sqlalchemy_utils import analyze

            analysis = analyze(conn, 'SELECT * FROM article')
            analysis.runtime  # runtime as milliseconds

        Analyze can be very useful when testing that query doesn't issue a
        sequential scan (scanning all rows in table). You can for example write
        simple performance tests this way.::

            query = (
                session.query(Article.name)
                .order_by(Article.name)
                .limit(10)
            )
            analysis = analyze(self.connection, query)
            analysis.node_types  # [u'Limit', u'Index Only Scan']

            assert 'Seq Scan' not in analysis.node_types

        .. versionadded: 0.26.17

        :param conn: SQLAlchemy Connection object
        :param query: SQLAlchemy Query object or query as a string
        """
        return QueryAnalysis(
            conn.execute(
                explain_analyze(query, buffers=True, format='json')
            ).scalar()
        )

    def escape_like(string, escape_char='*'):
        """
        Escape the string paremeter used in SQL LIKE expressions.

        ::

            from sqlalchemy_utils import escape_like

            query = session.query(User).filter(
                User.name.ilike(escape_like('John'))
            )

        :param string: a string to escape
        :param escape_char: escape character
        """
        return (
            string
            .replace(escape_char, escape_char * 2)
            .replace('%', escape_char + '%')
            .replace('_', escape_char + '_')
        )

    def json_sql(value, scalars_to_json=True):
        """
        Convert python data structures to PostgreSQL specific SQLAlchemy JSON
        constructs. This function is extremly useful if you need to build
        PostgreSQL JSON on python side.

        .. note::

            This function needs PostgreSQL >= 9.4

        Scalars are converted to to_json SQLAlchemy function objects

        ::

            json_sql(1)     # Equals SQL: to_json(1)

            json_sql('a')   # to_json('a')

        Mappings are converted to json_build_object constructs

        ::

            json_sql({'a': 'c', '2': 5})  # json_build_object('a', 'c', '2', 5)

        Sequences (other than strings) are converted to json_build_array constructs

        ::

            json_sql([1, 2, 3])  # json_build_array(1, 2, 3)

        You can also nest these data structures

        ::

            json_sql({'a': [1, 2, 3]})
            # json_build_object('a', json_build_array[1, 2, 3])

        :param value:
            value to be converted to SQLAlchemy PostgreSQL function constructs
        """
        scalar_convert = sa.text
        if scalars_to_json:
            def scalar_convert(a):
                return sa.func.to_json(sa.text(a))

        if isinstance(value, collections.Mapping):
            return sa.func.json_build_object(
                *(
                    json_sql(v, scalars_to_json=False)
                    for v in itertools.chain(*value.items())
                )
            )
        elif isinstance(value, str):
            return scalar_convert("'{0}'".format(value))
        elif isinstance(value, collections.Sequence):
            return sa.func.json_build_array(
                *(
                    json_sql(v, scalars_to_json=False)
                    for v in value
                )
            )
        elif isinstance(value, (int, float)):
            return scalar_convert(str(value))
        return value

    def has_index(column_or_constraint):
        """
        Return whether or not given column or the columns of given foreign key
        constraint have an index. A column has an index if it has a single column
        index or it is the first column in compound column index.

        A foreign key constraint has an index if the constraint columns are the
        first columns in compound column index.

        :param column_or_constraint:
            SQLAlchemy Column object or SA ForeignKeyConstraint object

        .. versionadded: 0.26.2

        .. versionchanged: 0.30.18
            Added support for foreign key constaints.

        ::

            from sqlalchemy_utils import has_index

            class Article(Base):
                __tablename__ = 'article'
                id = sa.Column(sa.Integer, primary_key=True)
                title = sa.Column(sa.String(100))
                is_published = sa.Column(sa.Boolean, index=True)
                is_deleted = sa.Column(sa.Boolean)
                is_archived = sa.Column(sa.Boolean)

                __table_args__ = (
                    sa.Index('my_index', is_deleted, is_archived),
                )

            table = Article.__table__

            has_index(table.c.is_published) # True
            has_index(table.c.is_deleted)   # True
            has_index(table.c.is_archived)  # False

        Also supports primary key indexes

        ::

            from sqlalchemy_utils import has_index

            class ArticleTranslation(Base):
                __tablename__ = 'article_translation'
                id = sa.Column(sa.Integer, primary_key=True)
                locale = sa.Column(sa.String(10), primary_key=True)
                title = sa.Column(sa.String(100))

            table = ArticleTranslation.__table__

            has_index(table.c.locale)   # False
            has_index(table.c.id)       # True

        This function supports foreign key constraints as well

        ::

            class User(Base):
                __tablename__ = 'user'
                first_name = sa.Column(sa.Unicode(255), primary_key=True)
                last_name = sa.Column(sa.Unicode(255), primary_key=True)

            class Article(Base):
                __tablename__ = 'article'
                id = sa.Column(sa.Integer, primary_key=True)
                author_first_name = sa.Column(sa.Unicode(255))
                author_last_name = sa.Column(sa.Unicode(255))
                __table_args__ = (
                    sa.ForeignKeyConstraint(
                        [author_first_name, author_last_name],
                        [User.first_name, User.last_name]
                    ),
                    sa.Index(
                        'my_index',
                        author_first_name,
                        author_last_name
                    )
                )

            table = Article.__table__
            constraint = list(table.foreign_keys)[0].constraint

            has_index(constraint)  # True
        """
        table = column_or_constraint.table
        if not isinstance(table, sa.Table):
            raise TypeError(
                'Only columns belonging to Table objects are supported. Given '
                'column belongs to %r.' % table
            )
        primary_keys = table.primary_key.columns.values()
        if isinstance(column_or_constraint, sa.ForeignKeyConstraint):
            columns = list(column_or_constraint.columns.values())
        else:
            columns = [column_or_constraint]

        return (
            (primary_keys and starts_with(primary_keys, columns)) or
            any(
                starts_with(index.columns.values(), columns)
                for index in table.indexes
            )
        )

    def has_unique_index(column_or_constraint):
        """
        Return whether or not given column or given foreign key constraint has a
        unique index.

        A column has a unique index if it has a single column primary key index or
        it has a single column UniqueConstraint.

        A foreign key constraint has a unique index if the columns of the
        constraint are the same as the columns of table primary key or the coluns
        of any unique index or any unique constraint of the given table.

        :param column: SQLAlchemy Column object

        .. versionadded: 0.27.1

        .. versionchanged: 0.30.18
            Added support for foreign key constaints.

            Fixed support for unique indexes (previously only worked for unique
            constraints)

        ::

            from sqlalchemy_utils import has_unique_index

            class Article(Base):
                __tablename__ = 'article'
                id = sa.Column(sa.Integer, primary_key=True)
                title = sa.Column(sa.String(100))
                is_published = sa.Column(sa.Boolean, unique=True)
                is_deleted = sa.Column(sa.Boolean)
                is_archived = sa.Column(sa.Boolean)

            table = Article.__table__

            has_unique_index(table.c.is_published) # True
            has_unique_index(table.c.is_deleted)   # False
            has_unique_index(table.c.id)           # True

        This function supports foreign key constraints as well

        ::

            class User(Base):
                __tablename__ = 'user'
                first_name = sa.Column(sa.Unicode(255), primary_key=True)
                last_name = sa.Column(sa.Unicode(255), primary_key=True)

            class Article(Base):
                __tablename__ = 'article'
                id = sa.Column(sa.Integer, primary_key=True)
                author_first_name = sa.Column(sa.Unicode(255))
                author_last_name = sa.Column(sa.Unicode(255))
                __table_args__ = (
                    sa.ForeignKeyConstraint(
                        [author_first_name, author_last_name],
                        [User.first_name, User.last_name]
                    ),
                    sa.Index(
                        'my_index',
                        author_first_name,
                        author_last_name,
                        unique=True
                    )
                )

            table = Article.__table__
            constraint = list(table.foreign_keys)[0].constraint

            has_unique_index(constraint)  # True

        :raises TypeError: if given column does not belong to a Table object
        """
        table = column_or_constraint.table
        if not isinstance(table, sa.Table):
            raise TypeError(
                'Only columns belonging to Table objects are supported. Given '
                'column belongs to %r.' % table
            )
        primary_keys = list(table.primary_key.columns.values())
        if isinstance(column_or_constraint, sa.ForeignKeyConstraint):
            columns = list(column_or_constraint.columns.values())
        else:
            columns = [column_or_constraint]

        return (
            (columns == primary_keys) or
            any(
                columns == list(constraint.columns.values())
                for constraint in table.constraints
                if isinstance(constraint, sa.sql.schema.UniqueConstraint)
            ) or
            any(
                columns == list(index.columns.values())
                for index in table.indexes
                if index.unique
            )
        )

    def is_auto_assigned_date_column(column):
        """
        Returns whether or not given SQLAlchemy Column object's is auto assigned
        DateTime or Date.

        :param column: SQLAlchemy Column object
        """
        return (
            (
                isinstance(column.type, sa.DateTime) or
                isinstance(column.type, sa.Date)
            ) and
            (
                column.default or
                column.server_default or
                column.onupdate or
                column.server_onupdate
            )
        )

    def database_exists(url):
        """Check if a database exists.

        :param url: A SQLAlchemy engine URL.

        Performs backend-specific testing to quickly determine if a database
        exists on the server. ::

            database_exists('postgres://postgres@localhost/name')  #=> False
            create_database('postgres://postgres@localhost/name')
            database_exists('postgres://postgres@localhost/name')  #=> True

        Supports checking against a constructed URL as well. ::

            engine = create_engine('postgres://postgres@localhost/name')
            database_exists(engine.url)  #=> False
            create_database(engine.url)
            database_exists(engine.url)  #=> True

        """

        def get_scalar_result(engine, sql):
            result_proxy = engine.execute(sql)
            result = result_proxy.scalar()
            result_proxy.close()
            engine.dispose()
            return result

        url = copy(make_url(url))
        database = url.database
        if url.drivername.startswith('postgres'):
            url.database = 'template1'
        else:
            url.database = None

        engine = sa.create_engine(url)

        if engine.dialect.name == 'postgresql':
            text = "SELECT 1 FROM pg_database WHERE datname='%s'" % database
            return bool(get_scalar_result(engine, text))

        elif engine.dialect.name == 'mysql':
            text = ("SELECT SCHEMA_NAME FROM INFORMATION_SCHEMA.SCHEMATA "
                    "WHERE SCHEMA_NAME = '%s'" % database)
            return bool(get_scalar_result(engine, text))

        elif engine.dialect.name == 'sqlite':
            if database:
                return database == ':memory:' or os.path.exists(database)
            else:
                # The default SQLAlchemy database is in memory,
                # and :memory is not required, thus we should support that use-case
                return True

        else:
            engine.dispose()
            engine = None
            text = 'SELECT 1'
            try:
                url.database = database
                engine = sa.create_engine(url)
                result = engine.execute(text)
                result.close()
                return True

            except (ProgrammingError, OperationalError):
                return False
            finally:
                if engine is not None:
                    engine.dispose()

    def create_database(url, encoding='utf8', template=None):
        """Issue the appropriate CREATE DATABASE statement.

        :param url: A SQLAlchemy engine URL.
        :param encoding: The encoding to create the database as.
        :param template:
            The name of the template from which to create the new database. At the
            moment only supported by PostgreSQL driver.

        To create a database, you can pass a simple URL that would have
        been passed to ``create_engine``. ::

            create_database('postgres://postgres@localhost/name')

        You may also pass the url from an existing engine. ::

            create_database(engine.url)

        Has full support for mysql, postgres, and sqlite. In theory,
        other database engines should be supported.
        """

        url = copy(make_url(url))

        database = url.database

        if url.drivername.startswith('postgres'):
            url.database = 'template1'
        elif not url.drivername.startswith('sqlite'):
            url.database = None

        engine = sa.create_engine(url)
        result_proxy = None

        if engine.dialect.name == 'postgresql':
            if engine.driver == 'psycopg2':
                from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
                engine.raw_connection().set_isolation_level(
                    ISOLATION_LEVEL_AUTOCOMMIT
                )

            if not template:
                template = 'template0'

            text = "CREATE DATABASE {0} ENCODING '{1}' TEMPLATE {2}".format(
                quote(engine, database),
                encoding,
                quote(engine, template)
            )
            result_proxy = engine.execute(text)

        elif engine.dialect.name == 'mysql':
            text = "CREATE DATABASE {0} CHARACTER SET = '{1}'".format(
                quote(engine, database),
                encoding
            )
            result_proxy = engine.execute(text)

        elif engine.dialect.name == 'sqlite' and database != ':memory:':
            if database:
                open(database, 'w').close()

        else:
            text = 'CREATE DATABASE {0}'.format(quote(engine, database))
            result_proxy = engine.execute(text)

        if result_proxy is not None:
            result_proxy.close()
        engine.dispose()

    def drop_database(url):
        """Issue the appropriate DROP DATABASE statement.

        :param url: A SQLAlchemy engine URL.

        Works similar to the :ref:`create_database` method in that both url text
        and a constructed url are accepted. ::

            drop_database('postgres://postgres@localhost/name')
            drop_database(engine.url)

        """

        url = copy(make_url(url))

        database = url.database

        if url.drivername.startswith('postgres'):
            url.database = 'template1'
        elif not url.drivername.startswith('sqlite'):
            url.database = None

        engine = sa.create_engine(url)
        conn_resource = None

        if engine.dialect.name == 'sqlite' and database != ':memory:':
            if database:
                os.remove(database)

        elif engine.dialect.name == 'postgresql' and engine.driver == 'psycopg2':
            from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT

            connection = engine.connect()
            connection.connection.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)

            # Disconnect all users from the database we are dropping.
            version = connection.dialect.server_version_info
            pid_column = (
                'pid' if (version >= (9, 2)) else 'procpid'
            )
            text = '''
            SELECT pg_terminate_backend(pg_stat_activity.%(pid_column)s)
            FROM pg_stat_activity
            WHERE pg_stat_activity.datname = '%(database)s'
              AND %(pid_column)s <> pg_backend_pid();
            ''' % {'pid_column': pid_column, 'database': database}
            connection.execute(text)

            # Drop the database.
            text = 'DROP DATABASE {0}'.format(quote(connection, database))
            connection.execute(text)
            conn_resource = connection
        else:
            text = 'DROP DATABASE {0}'.format(quote(engine, database))
            conn_resource = engine.execute(text)

        if conn_resource is not None:
            conn_resource.close()
        engine.dispose()