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Execute the given SQL query using the provided connection object.
|
|
Parameters
|
----------
|
sql : string
|
SQL query to be executed.
|
con : SQLAlchemy connection or sqlite3 connection
|
If a DBAPI2 object, only sqlite3 is supported.
|
params : list or tuple, optional, default: None
|
List of parameters to pass to execute method.
|
|
Returns
|
-------
|
Results Iterable
|
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Read SQL database table into a DataFrame.
|
|
Given a table name and a SQLAlchemy connectable, returns a DataFrame.
|
This function does not support DBAPI connections.
|
|
Parameters
|
----------
|
table_name : str
|
Name of SQL table in database.
|
con : SQLAlchemy connectable or str
|
A database URI could be provided as str.
|
SQLite DBAPI connection mode not supported.
|
schema : str, default None
|
Name of SQL schema in database to query (if database flavor
|
supports this). Uses default schema if None (default).
|
index_col : str or list of str, optional, default: None
|
Column(s) to set as index(MultiIndex).
|
coerce_float : bool, default True
|
Attempts to convert values of non-string, non-numeric objects (like
|
decimal.Decimal) to floating point. Can result in loss of Precision.
|
parse_dates : list or dict, default None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
|
to the keyword arguments of :func:`pandas.to_datetime`
|
Especially useful with databases without native Datetime support,
|
such as SQLite.
|
columns : list, default None
|
List of column names to select from SQL table.
|
chunksize : int, default None
|
If specified, returns an iterator where `chunksize` is the number of
|
rows to include in each chunk.
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
Returns
|
-------
|
DataFrame or Iterator[DataFrame]
|
A SQL table is returned as two-dimensional data structure with labeled
|
axes.
|
|
See Also
|
--------
|
read_sql_query : Read SQL query into a DataFrame.
|
read_sql : Read SQL query or database table into a DataFrame.
|
|
Notes
|
-----
|
Any datetime values with time zone information will be converted to UTC.
|
|
Examples
|
--------
|
>>> pd.read_sql_table('table_name', 'postgres:///db_name') # doctest:+SKIP
|
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|
Read SQL query into a DataFrame.
|
|
Returns a DataFrame corresponding to the result set of the query
|
string. Optionally provide an `index_col` parameter to use one of the
|
columns as the index, otherwise default integer index will be used.
|
|
Parameters
|
----------
|
sql : str SQL query or SQLAlchemy Selectable (select or text object)
|
SQL query to be executed.
|
con : SQLAlchemy connectable, str, or sqlite3 connection
|
Using SQLAlchemy makes it possible to use any DB supported by that
|
library. If a DBAPI2 object, only sqlite3 is supported.
|
index_col : str or list of str, optional, default: None
|
Column(s) to set as index(MultiIndex).
|
coerce_float : bool, default True
|
Attempts to convert values of non-string, non-numeric objects (like
|
decimal.Decimal) to floating point. Useful for SQL result sets.
|
params : list, tuple or mapping, optional, default: None
|
List of parameters to pass to execute method. The syntax used
|
to pass parameters is database driver dependent. Check your
|
database driver documentation for which of the five syntax styles,
|
described in PEP 249's paramstyle, is supported.
|
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}.
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
|
to the keyword arguments of :func:`pandas.to_datetime`
|
Especially useful with databases without native Datetime support,
|
such as SQLite.
|
chunksize : int, default None
|
If specified, return an iterator where `chunksize` is the number of
|
rows to include in each chunk.
|
dtype : Type name or dict of columns
|
Data type for data or columns. E.g. np.float64 or
|
{'a': np.float64, 'b': np.int32, 'c': 'Int64'}.
|
|
.. versionadded:: 1.3.0
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
Returns
|
-------
|
DataFrame or Iterator[DataFrame]
|
|
See Also
|
--------
|
read_sql_table : Read SQL database table into a DataFrame.
|
read_sql : Read SQL query or database table into a DataFrame.
|
|
Notes
|
-----
|
Any datetime values with time zone information parsed via the `parse_dates`
|
parameter will be converted to UTC.
|
|
Examples
|
--------
|
>>> from sqlalchemy import create_engine # doctest: +SKIP
|
>>> engine = create_engine("sqlite:///database.db") # doctest: +SKIP
|
>>> with engine.connect() as conn, conn.begin(): # doctest: +SKIP
|
... data = pd.read_sql_table("data", conn) # doctest: +SKIP
|
rf )r r rh r8 r rR ri N)r r r§ r Ú
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read_query)
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Read SQL query or database table into a DataFrame.
|
|
This function is a convenience wrapper around ``read_sql_table`` and
|
``read_sql_query`` (for backward compatibility). It will delegate
|
to the specific function depending on the provided input. A SQL query
|
will be routed to ``read_sql_query``, while a database table name will
|
be routed to ``read_sql_table``. Note that the delegated function might
|
have more specific notes about their functionality not listed here.
|
|
Parameters
|
----------
|
sql : str or SQLAlchemy Selectable (select or text object)
|
SQL query to be executed or a table name.
|
con : ADBC Connection, SQLAlchemy connectable, str, or sqlite3 connection
|
ADBC provides high performance I/O with native type support, where available.
|
Using SQLAlchemy makes it possible to use any DB supported by that
|
library. If a DBAPI2 object, only sqlite3 is supported. The user is responsible
|
for engine disposal and connection closure for the ADBC connection and
|
SQLAlchemy connectable; str connections are closed automatically. See
|
`here <https://docs.sqlalchemy.org/en/20/core/connections.html>`_.
|
index_col : str or list of str, optional, default: None
|
Column(s) to set as index(MultiIndex).
|
coerce_float : bool, default True
|
Attempts to convert values of non-string, non-numeric objects (like
|
decimal.Decimal) to floating point, useful for SQL result sets.
|
params : list, tuple or dict, optional, default: None
|
List of parameters to pass to execute method. The syntax used
|
to pass parameters is database driver dependent. Check your
|
database driver documentation for which of the five syntax styles,
|
described in PEP 249's paramstyle, is supported.
|
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}.
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
|
to the keyword arguments of :func:`pandas.to_datetime`
|
Especially useful with databases without native Datetime support,
|
such as SQLite.
|
columns : list, default: None
|
List of column names to select from SQL table (only used when reading
|
a table).
|
chunksize : int, default None
|
If specified, return an iterator where `chunksize` is the
|
number of rows to include in each chunk.
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
dtype : Type name or dict of columns
|
Data type for data or columns. E.g. np.float64 or
|
{'a': np.float64, 'b': np.int32, 'c': 'Int64'}.
|
The argument is ignored if a table is passed instead of a query.
|
|
.. versionadded:: 2.0.0
|
|
Returns
|
-------
|
DataFrame or Iterator[DataFrame]
|
|
See Also
|
--------
|
read_sql_table : Read SQL database table into a DataFrame.
|
read_sql_query : Read SQL query into a DataFrame.
|
|
Examples
|
--------
|
Read data from SQL via either a SQL query or a SQL tablename.
|
When using a SQLite database only SQL queries are accepted,
|
providing only the SQL tablename will result in an error.
|
|
>>> from sqlite3 import connect
|
>>> conn = connect(':memory:')
|
>>> df = pd.DataFrame(data=[[0, '10/11/12'], [1, '12/11/10']],
|
... columns=['int_column', 'date_column'])
|
>>> df.to_sql(name='test_data', con=conn)
|
2
|
|
>>> pd.read_sql('SELECT int_column, date_column FROM test_data', conn)
|
int_column date_column
|
0 0 10/11/12
|
1 1 12/11/10
|
|
>>> pd.read_sql('test_data', 'postgres:///db_name') # doctest:+SKIP
|
|
Apply date parsing to columns through the ``parse_dates`` argument
|
The ``parse_dates`` argument calls ``pd.to_datetime`` on the provided columns.
|
Custom argument values for applying ``pd.to_datetime`` on a column are specified
|
via a dictionary format:
|
|
>>> pd.read_sql('SELECT int_column, date_column FROM test_data',
|
... conn,
|
... parse_dates={"date_column": {"format": "%d/%m/%y"}})
|
int_column date_column
|
0 0 2012-11-10
|
1 1 2010-11-12
|
|
.. versionadded:: 2.2.0
|
|
pandas now supports reading via ADBC drivers
|
|
>>> from adbc_driver_postgresql import dbapi # doctest:+SKIP
|
>>> with dbapi.connect('postgres:///db_name') as conn: # doctest:+SKIP
|
... pd.read_sql('SELECT int_column FROM test_data', conn)
|
int_column
|
0 0
|
1 1
|
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r r r§ r rL ÚSQLiteDatabaser° r¨ Ú Exceptionr© ) r r r rh r r8 rm r ri rR r Ú_is_table_names r9 r³ r³ < s" ôB Ô&ØÑ&Ø Ø ¤§¡Ñ .Ð.Ð .ä 3Ó ð ' :Ü j¤.Ô 1Ø ×(Ñ(ØØ#Ø Ø )Ø 'Ø#Ø +Øð )ó ÷'ñ 'ð #Ø '× 1Ñ 1°#Ó 6Nñ
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|
d| ¤cddd« S # 1 sw Y yxY w) aµ
|
Write records stored in a DataFrame to a SQL database.
|
|
Parameters
|
----------
|
frame : DataFrame, Series
|
name : str
|
Name of SQL table.
|
con : ADBC Connection, SQLAlchemy connectable, str, or sqlite3 connection
|
or sqlite3 DBAPI2 connection
|
ADBC provides high performance I/O with native type support, where available.
|
Using SQLAlchemy makes it possible to use any DB supported by that
|
library.
|
If a DBAPI2 object, only sqlite3 is supported.
|
schema : str, optional
|
Name of SQL schema in database to write to (if database flavor
|
supports this). If None, use default schema (default).
|
if_exists : {'fail', 'replace', 'append'}, default 'fail'
|
- fail: If table exists, do nothing.
|
- replace: If table exists, drop it, recreate it, and insert data.
|
- append: If table exists, insert data. Create if does not exist.
|
index : bool, default True
|
Write DataFrame index as a column.
|
index_label : str or sequence, optional
|
Column label for index column(s). If None is given (default) and
|
`index` is True, then the index names are used.
|
A sequence should be given if the DataFrame uses MultiIndex.
|
chunksize : int, optional
|
Specify the number of rows in each batch to be written at a time.
|
By default, all rows will be written at once.
|
dtype : dict or scalar, optional
|
Specifying the datatype for columns. If a dictionary is used, the
|
keys should be the column names and the values should be the
|
SQLAlchemy types or strings for the sqlite3 fallback mode. If a
|
scalar is provided, it will be applied to all columns.
|
method : {None, 'multi', callable}, optional
|
Controls the SQL insertion clause used:
|
|
- None : Uses standard SQL ``INSERT`` clause (one per row).
|
- ``'multi'``: Pass multiple values in a single ``INSERT`` clause.
|
- callable with signature ``(pd_table, conn, keys, data_iter) -> int | None``.
|
|
Details and a sample callable implementation can be found in the
|
section :ref:`insert method <io.sql.method>`.
|
engine : {'auto', 'sqlalchemy'}, default 'auto'
|
SQL engine library to use. If 'auto', then the option
|
``io.sql.engine`` is used. The default ``io.sql.engine``
|
behavior is 'sqlalchemy'
|
|
.. versionadded:: 1.3.0
|
|
**engine_kwargs
|
Any additional kwargs are passed to the engine.
|
|
Returns
|
-------
|
None or int
|
Number of rows affected by to_sql. None is returned if the callable
|
passed into ``method`` does not return an integer number of rows.
|
|
.. versionadded:: 1.4.0
|
|
Notes
|
-----
|
The returned rows affected is the sum of the ``rowcount`` attribute of ``sqlite3.Cursor``
|
or SQLAlchemy connectable. If using ADBC the returned rows are the result
|
of ``Cursor.adbc_ingest``. The returned value may not reflect the exact number of written
|
rows as stipulated in the
|
`sqlite3 <https://docs.python.org/3/library/sqlite3.html#sqlite3.Cursor.rowcount>`__ or
|
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|
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Check if DataBase has named table.
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table_name: string
|
Name of SQL table.
|
con: ADBC Connection, SQLAlchemy connectable, str, or sqlite3 connection
|
ADBC provides high performance I/O with native type support, where available.
|
Using SQLAlchemy makes it possible to use any DB supported by that
|
library.
|
If a DBAPI2 object, only sqlite3 is supported.
|
schema : string, default None
|
Name of SQL schema in database to write to (if database flavor supports
|
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|
|
Returns
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t « S t d« # t $ r}|dt |« z z }Y d}~Ud}~ww xY w) zreturn our implementationr¶ z io.sql.engineÚ z
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This class enables conversion between DataFrame and SQL databases
|
using SQLAlchemy to handle DataBase abstraction.
|
|
Parameters
|
----------
|
con : SQLAlchemy Connectable or URI string.
|
Connectable to connect with the database. Using SQLAlchemy makes it
|
possible to use any DB supported by that library.
|
schema : string, default None
|
Name of SQL schema in database to write to (if database flavor
|
supports this). If None, use default schema (default).
|
need_transaction : bool, default False
|
If True, SQLDatabase will create a transaction.
|
|
Nc óØ ddl m} ddlm} ddlm} t « | _ t |t « r- ||« }| j j |j « t ||« r)| j j |j « « }|r9|j « s)| j j |j « « || _ ||¬« | _ d| _ y )Nr )Ú create_engine)r rU rÉ F)r rÖ Úsqlalchemy.enginer rå rV r r9 rL r ÚcallbackÚdisposeÚ enter_contextÚconnectÚin_transactionÚbeginr rì Úreturns_generator)rÝ r r r rÖ r rV s r9 rß zSQLDatabase.__init__` s§ õ -Ý,Ý.ô $+Ü c3Ô Ù Ó$CØ OO× $Ñ $ S§[¡[Ô 1Ü c6Ô "Ø//×/Ñ/°· ± ³ Ó>CÙ C×$6Ñ$6Ô$8Ø OO× )Ñ )¨#¯)©)«+Ô 6ØÙ FÔ+ Ø!&Õ r; c óR | j s| j j « y y r )rÞ r9 Úcloser£ s r9 r¥ zSQLDatabase.__exit__w s Ø×%Ò%Ø OO× !Ñ !Õ #ð &r; c # óØ K | j j « s2| j j « 5 | j d d d « y | j y # 1 sw Y y xY wwr )r rÜ rÝ rá s r9 rí zSQLDatabase.run_transaction{ sQ è ø àxx×&Ñ&Ô(Ø Ó!ñ Øhh÷ ð ð ((N÷ ð üs 5A*·A ÁA*Á A'Á#A*c ó¤ |g n|g}t |t « r | j j |g|¢ S | j j |g|¢ S )z,Simple passthrough to SQLAlchemy connectable)rL r r Úexec_driver_sqlr )rÝ r r r¤ s r9 r zSQLDatabase.execute sQ à^r¨&¨Ü c3Ô Ø+488×+Ñ+¨CÐ7°$Ò7Ð 7Ø txx× Ñ Ð+ dÒ+Ð+r; c óÆ | j j | j |gd¬« t || ||¬« } |d| _ | j | j |||||¬« S )ap
|
Read SQL database table into a DataFrame.
|
|
Parameters
|
----------
|
table_name : str
|
Name of SQL table in database.
|
index_col : string, optional, default: None
|
Column to set as index.
|
coerce_float : bool, default True
|
Attempts to convert values of non-string, non-numeric objects
|
(like decimal.Decimal) to floating point. This can result in
|
loss of precision.
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg}``, where the arg corresponds
|
to the keyword arguments of :func:`pandas.to_datetime`.
|
Especially useful with databases without native Datetime support,
|
such as SQLite.
|
columns : list, default: None
|
List of column names to select from SQL table.
|
schema : string, default None
|
Name of SQL schema in database to query (if database flavor
|
supports this). If specified, this overwrites the default
|
schema of the SQL database object.
|
chunksize : int, default None
|
If specified, return an iterator where `chunksize` is the number
|
of rows to include in each chunk.
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
Returns
|
-------
|
DataFrame
|
|
See Also
|
--------
|
pandas.read_sql_table
|
SQLDatabase.read_query
|
|
T)rê ÚonlyÚviews)rÀ r )rh r8 rm r ri )rì Úreflectr rÕ rÞ rE r9 )
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rÝ r r rh r8 rm r r ri rª s
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|
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||||||¬« A ddd« y# 1 sw Y yxY ww)ú+Return generator through chunked result setFT©r rh r8 rR ri N)r6 r
) rú r9 r rm r rh r8 rR ri r: rv s r9 r; zSQLDatabase._query_iteratorÖ s è ø ð Ø ñ ØØ ×'Ñ'¨ Ó2ÙÙ(Ü *Ø Ø #Ø&/Ø)5Ø(3Ø"'Ø*7ô ò ð à $ Ü"ØØØ 'Ø!-Ø +Ø Ø"/ôò ð! ð ÷ ÷ ñ üs A AAÁ A ÁA ÁA c óè | j ||« } | j « }
|
|+d| _ | j | | j ||
|
|||||¬« S | j « } t | |
|
|||||¬« } | S )aé
|
Read SQL query into a DataFrame.
|
|
Parameters
|
----------
|
sql : str
|
SQL query to be executed.
|
index_col : string, optional, default: None
|
Column name to use as index for the returned DataFrame object.
|
coerce_float : bool, default True
|
Attempt to convert values of non-string, non-numeric objects (like
|
decimal.Decimal) to floating point, useful for SQL result sets.
|
params : list, tuple or dict, optional, default: None
|
List of parameters to pass to execute method. The syntax used
|
to pass parameters is database driver dependent. Check your
|
database driver documentation for which of the five syntax styles,
|
described in PEP 249's paramstyle, is supported.
|
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg dict}``, where the arg dict
|
corresponds to the keyword arguments of
|
:func:`pandas.to_datetime` Especially useful with databases
|
without native Datetime support, such as SQLite.
|
chunksize : int, default None
|
If specified, return an iterator where `chunksize` is the number
|
of rows to include in each chunk.
|
dtype : Type name or dict of columns
|
Data type for data or columns. E.g. np.float64 or
|
{'a': np.float64, 'b': np.int32, 'c': 'Int64'}
|
|
.. versionadded:: 1.3.0
|
|
Returns
|
-------
|
DataFrame
|
|
See Also
|
--------
|
read_sql_table : Read SQL database table into a DataFrame.
|
read_sql
|
|
Trê )r rÚ rÞ r; r9 r@ r
) rÝ r r rh r8 r r rR ri rú rm rv r s r9 r° zSQLDatabase.read_queryÿ s ðr c 6Ó*Ø++-à Ð Ø%)DÔ "Ø×'Ñ'ØØØØØ#Ø )Ø 'ØØ +ð (ó
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|
Prepares table in the database for data insertion. Creates it if needed, etc.
|
r )Ú
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TypeEnginez The type of z is not a SQLAlchemy type)r rÀ r¿ rÁ r rR ) r r rM r rí r] rL rS rQ rP rÕ rî ) rÝ r rÆ r¿ rÀ rÁ r rR rb rí rW Úmy_typerª s r9 Ú
|
prep_tablezSQLDatabase.prep_tableW sÄ ñ Ü Ô&ð :?Ö?¨X 5 Ð?Ñ?ä T 5Ó)å 3à %§ ¡ £ ò T WÜ g¤tÔ,´¸GÀZÔ1PØÜ ¨Ô4Øä$ |°C°5Ð8QÐ%RÓSÐSð Tô Ø Ø ØØØ Ø#ØØô
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B*c ó* |j « s|j « srddlm} || j « }|j |xs | j j ¬« }||vr+d| d}t j |t t « ¬« yyyy)zv
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Checks table name for issues with case-sensitivity.
|
Method is called after data is inserted.
|
r ©ÚinspectrÉ zThe provided table name 'z' is not found exactly as such in the database after writing the table, possibly due to case sensitivity issues. Consider using lower case table names.r N) ÚisdigitÚislowerr rò r Úget_table_namesrì r r r rÒ r )rÝ rÆ r Úsqlalchemy_inspectÚinspÚ table_namesrÌ s r9 Úcheck_case_sensitivez SQLDatabase.check_case_sensitive s ð ||~ d§l¡l¤nõ Aá% d§h¡hÓ/DØ ×.Ñ.°fÒ6PÀÇ Á ×@PÑ@PÐ.ÓQKØ;Ñ&à/°¨vð 6(ð (ð ô ØÜ Ü /Ó 1öð 'ð '5~r; c ó¼ t |
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|
Write records stored in a DataFrame to a SQL database.
|
|
Parameters
|
----------
|
frame : DataFrame
|
name : string
|
Name of SQL table.
|
if_exists : {'fail', 'replace', 'append'}, default 'fail'
|
- fail: If table exists, do nothing.
|
- replace: If table exists, drop it, recreate it, and insert data.
|
- append: If table exists, insert data. Create if does not exist.
|
index : boolean, default True
|
Write DataFrame index as a column.
|
index_label : string or sequence, default None
|
Column label for index column(s). If None is given (default) and
|
`index` is True, then the index names are used.
|
A sequence should be given if the DataFrame uses MultiIndex.
|
schema : string, default None
|
Name of SQL schema in database to write to (if database flavor
|
supports this). If specified, this overwrites the default
|
schema of the SQLDatabase object.
|
chunksize : int, default None
|
If not None, then rows will be written in batches of this size at a
|
time. If None, all rows will be written at once.
|
dtype : single type or dict of column name to SQL type, default None
|
Optional specifying the datatype for columns. The SQL type should
|
be a SQLAlchemy type. If all columns are of the same type, one
|
single value can be used.
|
method : {None', 'multi', callable}, default None
|
Controls the SQL insertion clause used:
|
|
* None : Uses standard SQL ``INSERT`` clause (one per row).
|
* 'multi': Pass multiple values in a single ``INSERT`` clause.
|
* callable with signature ``(pd_table, conn, keys, data_iter)``.
|
|
Details and a sample callable implementation can be found in the
|
section :ref:`insert method <io.sql.method>`.
|
engine : {'auto', 'sqlalchemy'}, default 'auto'
|
SQL engine library to use. If 'auto', then the option
|
``io.sql.engine`` is used. The default ``io.sql.engine``
|
behavior is 'sqlalchemy'
|
|
.. versionadded:: 1.3.0
|
|
**engine_kwargs
|
Any additional kwargs are passed to the engine.
|
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This class enables conversion between DataFrame and SQL databases
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using ADBC to handle DataBase abstraction.
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Parameters
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----------
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con : adbc_driver_manager.dbapi.Connection
|
c ó || _ y r ©r ©rÝ r s r9 rß zADBCDatabase.__init__? ó Ør; c # óø K | j j « 5 } | | j j « d d d « y # t $ r | j j « w xY w# 1 sw Y y xY wwr )r Úcursorr¸ ÚrollbackÚcommit©rÝ Úcurs r9 rí z ADBCDatabase.run_transactionB sm è ø à XX__Ó ð #ð Ø ð HHOOÔ ÷ ð øô ò Ø×!Ñ!Ô#Øð ú÷ ð üs1 A:A.A£A.½ A:Á%A+Á+A.Á.A7Á3A:Nc ót t |t « s t d« |g n|g}| j j « } |j
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|
Read SQL database table into a DataFrame.
|
|
Parameters
|
----------
|
table_name : str
|
Name of SQL table in database.
|
coerce_float : bool, default True
|
Raises NotImplementedError
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg}``, where the arg corresponds
|
to the keyword arguments of :func:`pandas.to_datetime`.
|
Especially useful with databases without native Datetime support,
|
such as SQLite.
|
columns : list, default: None
|
List of column names to select from SQL table.
|
schema : string, default None
|
Name of SQL schema in database to query (if database flavor
|
supports this). If specified, this overwrites the default
|
schema of the SQL database object.
|
chunksize : int, default None
|
Raises NotImplementedError
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
Returns
|
-------
|
DataFrame
|
|
See Also
|
--------
|
pandas.read_sql_table
|
SQLDatabase.read_query
|
|
Tú2'coerce_float' is not implemented for ADBC driversú/'chunksize' is not implemented for ADBC driversú, c 3 ó( K | ]
|
}d | d yw)ú"Nr )r' Úxs r9 r* z*ADBCDatabase.read_table.<locals>.<genexpr>§ s è ø Ò#@° a¨ s¨!¤HÑ#@ùs Ú*zSELECT z FROM ú.©ri N)r r8 ) rÄ r& Újoinr r r Úfetch_arrow_tabler) r )rÝ r r rh r8 rm r r ri Ú index_selectÚ to_selectÚ select_listrþ r Úpa_tabler} s r9 r© zADBCDatabase.read_table` sú ðt tÑ #Ü%ØDóð ñ Ü%Ð&WÓXÐ Xá ÙÜ .¨yÓ 9 à ! Ø$ wÑ.IØ ))Ñ#@°iÔ#@Ó@Kà KÙ Ø [M¨°¨x°q¸¸ ÐEDà [M¨°
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!Ø Ø Ø#ô
|
ð
|
÷ Nð Nús Á?/CÃC c ó, |dur t d« |r t d« |r t d« | j j « 5 } | j |« | j « }
|
t |
|
|¬« } ddd« t |||¬« S # 1 sw Y xY w)aÜ
|
Read SQL query into a DataFrame.
|
|
Parameters
|
----------
|
sql : str
|
SQL query to be executed.
|
index_col : string, optional, default: None
|
Column name to use as index for the returned DataFrame object.
|
coerce_float : bool, default True
|
Raises NotImplementedError
|
params : list, tuple or dict, optional, default: None
|
Raises NotImplementedError
|
parse_dates : list or dict, default: None
|
- List of column names to parse as dates.
|
- Dict of ``{column_name: format string}`` where format string is
|
strftime compatible in case of parsing string times, or is one of
|
(D, s, ns, ms, us) in case of parsing integer timestamps.
|
- Dict of ``{column_name: arg dict}``, where the arg dict
|
corresponds to the keyword arguments of
|
:func:`pandas.to_datetime` Especially useful with databases
|
without native Datetime support, such as SQLite.
|
chunksize : int, default None
|
Raises NotImplementedError
|
dtype : Type name or dict of columns
|
Data type for data or columns. E.g. np.float64 or
|
{'a': np.float64, 'b': np.int32, 'c': 'Int64'}
|
|
.. versionadded:: 1.3.0
|
|
Returns
|
-------
|
DataFrame
|
|
See Also
|
--------
|
read_sql_table : Read SQL database table into a DataFrame.
|
read_sql
|
|
Tr( z,'params' is not implemented for ADBC driversr) r0 N)r r8 rR )rÄ r r r r2 r) r ) rÝ r r rh r8 r r rR ri r r6 r} s r9 r° zADBCDatabase.read_queryº s§ ðf tÑ #Ü%ØDóð ñ Ü%Ð&TÓUÐ UÙ Ü%Ð&WÓXÐ Xà XX__Ó ð N #Ø KKÔ Ø×,Ñ,Ó.HÜ& x¸}ÔMB÷ Nô
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|
Write records stored in a DataFrame to a SQL database.
|
|
Parameters
|
----------
|
frame : DataFrame
|
name : string
|
Name of SQL table.
|
if_exists : {'fail', 'replace', 'append'}, default 'fail'
|
- fail: If table exists, do nothing.
|
- replace: If table exists, drop it, recreate it, and insert data.
|
- append: If table exists, insert data. Create if does not exist.
|
index : boolean, default True
|
Write DataFrame index as a column.
|
index_label : string or sequence, default None
|
Raises NotImplementedError
|
schema : string, default None
|
Name of SQL schema in database to write to (if database flavor
|
supports this). If specified, this overwrites the default
|
schema of the SQLDatabase object.
|
chunksize : int, default None
|
Raises NotImplementedError
|
dtype : single type or dict of column name to SQL type, default None
|
Raises NotImplementedError
|
method : {None', 'multi', callable}, default None
|
Raises NotImplementedError
|
engine : {'auto', 'sqlalchemy'}, default 'auto'
|
Raises NotImplementedError if not set to 'auto'
|
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Return a list of SQL statements that creates a table reflecting the
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|
statement while the rest will be CREATE INDEX statements.
|
ru r* z CONSTRAINT z_pk PRIMARY KEY (r r/ rÏ z CREATE TABLE z (
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Version of SQLDatabase to support SQLite connections (fallback without
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Parameters
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con : sqlite connection object
|
|
c ó || _ y r r r s r9 rß zSQLiteDatabase.__init__S
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Write records stored in a DataFrame to a SQL database.
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|
Parameters
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frame: DataFrame
|
name: string
|
Name of SQL table.
|
if_exists: {'fail', 'replace', 'append'}, default 'fail'
|
fail: If table exists, do nothing.
|
replace: If table exists, drop it, recreate it, and insert data.
|
append: If table exists, insert data. Create if it does not exist.
|
index : bool, default True
|
Write DataFrame index as a column
|
index_label : string or sequence, default None
|
Column label for index column(s). If None is given (default) and
|
`index` is True, then the index names are used.
|
A sequence should be given if the DataFrame uses MultiIndex.
|
schema : string, default None
|
Ignored parameter included for compatibility with SQLAlchemy
|
version of ``to_sql``.
|
chunksize : int, default None
|
If not None, then rows will be written in batches of this
|
size at a time. If None, all rows will be written at once.
|
dtype : single type or dict of column name to SQL type, default None
|
Optional specifying the datatype for columns. The SQL type should
|
be a string. If all columns are of the same type, one single value
|
can be used.
|
method : {None, 'multi', callable}, default None
|
Controls the SQL insertion clause used:
|
|
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|
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|
* callable with signature ``(pd_table, conn, keys, data_iter)``.
|
|
Details and a sample callable implementation can be found in the
|
section :ref:`insert method <io.sql.method>`.
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Get the SQL db table schema for the given frame.
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Parameters
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----------
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frame : DataFrame
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name : str
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name of SQL table
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keys : string or sequence, default: None
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columns to use a primary key
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con: ADBC Connection, SQLAlchemy connectable, sqlite3 connection, default: None
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ADBC provides high performance I/O with native type support, where available.
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Using SQLAlchemy makes it possible to use any DB supported by that
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library
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If a DBAPI2 object, only sqlite3 is supported.
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dtype : dict of column name to SQL type, default None
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Optional specifying the datatype for columns. The SQL type should
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be a SQLAlchemy type, or a string for sqlite3 fallback connection.
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schema: str, default: None
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Optional specifying the schema to be used in creating the table.
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