SimpleSQLite 0.12.0

SimpleSQLite is a Python library to simplify SQLite database operations: table creation, data insertion and get data as other data formats.

Home-page: https://github.com/thombashi/SimpleSQLite
Author: Tsuyoshi Hombashi
Author-email: [e-mail]
License: MIT License
Description: SimpleSQLite
============

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Summary
-------

SimpleSQLite is a Python library to simplify SQLite database operations: table creation, data insertion and get data as other data formats.

Features
--------

- Automated SQLite table creation from data
- Support various data types of record(s) insertion into a table:
- ``dict``
- ``namedtuple``
- ``list``
- ``tuple``
- Create table(s) from:
- CSV file/text
- JSON file/text
- `pandas.DataFrame <http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html>`__ instance
- `pytablereader.TableData <http://pytablereader.rtfd.io/en/latest/pages/reference/data.html#tabledata>`__ instance loaded by `pytablereader <https://github.com/thombashi/pytablereader>`__
- Get data from a table as:
- `pandas.DataFrame <http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html>`__ instance
- `pytablereader.TableData <http://pytablereader.rtfd.io/en/latest/pages/reference/data.html#tabledata>`__ instance



Examples
========

Create a table
--------------

Create a table from data matrix
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

:Sample Code:
.. code:: python

import json
from simplesqlite import SimpleSQLite

table_name = "sample_table"
con = SimpleSQLite("sample.sqlite", "w")

# create table -----
data_matrix = [
[1, 1.1, "aaa", 1, 1],
[2, 2.2, "bbb", 2.2, 2.2],
[3, 3.3, "ccc", 3, "ccc"],
]
con.create_table_from_data_matrix(
table_name,
attr_name_list=["attr_a", "attr_b", "attr_c", "attr_d", "attr_e"],
data_matrix=data_matrix)

# display values in the table -----
print(con.get_attr_name_list(table_name))
result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record)

# display data type for each column in the table -----
print(json.dumps(con.get_attr_type(table_name), indent=4))

:Output:
.. code::

['attr_a', 'attr_b', 'attr_c', 'attr_d', 'attr_e']
(1, 1.1, u'aaa', 1.0, u'1')
(2, 2.2, u'bbb', 2.2, u'2.2')
(3, 3.3, u'ccc', 3.0, u'ccc')
{
"attr_b": " REAL",
"attr_c": " TEXT",
"attr_a": " INTEGER",
"attr_d": " REAL",
"attr_e": " TEXT"
}

Create a table from CSV
~~~~~~~~~~~~~~~~~~~~~~~

:Sample Code:
.. code:: python

from simplesqlite import SimpleSQLite

with open("sample_data.csv", "w") as f:
f.write("\n".join([
'"attr_a","attr_b","attr_c"',
'1,4,"a"',
'2,2.1,"bb"',
'3,120.9,"ccc"',
]))

# create table ---
con = SimpleSQLite("sample.sqlite", "w")
con.create_table_from_csv("sample_data.csv")

# output ---
table_name = "sample_data"
print(con.get_attr_name_list(table_name))
result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record)

:Output:
.. code::

['attr_a', 'attr_b', 'attr_c']
(1, 4.0, u'a')
(2, 2.1, u'bb')
(3, 120.9, u'ccc')

Create a table from pandas.DataFrame
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

:Sample Code:
.. code:: python

from simplesqlite import SimpleSQLite
import pandas

con = SimpleSQLite("pandas_df.sqlite")

con.create_table_from_dataframe(pandas.DataFrame(
[
[0, 0.1, "a"],
[1, 1.1, "bb"],
[2, 2.2, "ccc"],
],
columns=['id', 'value', 'name']
), table_name="pandas_df")

:Output:
.. code::

$ sqlite3 pandas_df.sqlite
sqlite> .schema
CREATE TABLE 'pandas_df' (id INTEGER, value REAL, name TEXT);

Insert records into a table
---------------------------

Insert dictionary
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

:Sample Code:
.. code:: python

from simplesqlite import SimpleSQLite


table_name = "sample_table"
con = SimpleSQLite("sample.sqlite", "w")
con.create_table_from_data_matrix(
table_name,
attr_name_list=["attr_a", "attr_b", "attr_c", "attr_d", "attr_e"],
data_matrix=[[1, 1.1, "aaa", 1, 1]])

con.insert(
table_name,
insert_record={
"attr_a": 4,
"attr_b": 4.4,
"attr_c": "ddd",
"attr_d": 4.44,
"attr_e": "hoge",
}
)
con.insert_many(
table_name,
insert_record_list=[
{
"attr_a": 5,
"attr_b": 5.5,
"attr_c": "eee",
"attr_d": 5.55,
"attr_e": "foo",
},
{
"attr_a": 6,
"attr_c": "fff",
},
]
)

result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record)

:Output:
.. code::

(1, 1.1, 'aaa', 1, 1)
(4, 4.4, 'ddd', 4.44, 'hoge')
(5, 5.5, 'eee', 5.55, 'foo')
(6, None, 'fff', None, None)


Insert list/tuple/namedtuple
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

:Sample Code:
.. code:: python

from collections import namedtuple
from simplesqlite import SimpleSQLite


table_name = "sample_table"
con = SimpleSQLite("sample.sqlite", "w")
con.create_table_from_data_matrix(
table_name,
attr_name_list=["attr_a", "attr_b", "attr_c", "attr_d", "attr_e"],
data_matrix=[[1, 1.1, "aaa", 1, 1]])

SampleTuple = namedtuple(
"SampleTuple", "attr_a attr_b attr_c attr_d attr_e")

con.insert(table_name, insert_record=[7, 7.7, "fff", 7.77, "bar"])
con.insert_many(
table_name,
insert_record_list=[
(8, 8.8, "ggg", 8.88, "foobar"),
SampleTuple(9, 9.9, "ggg", 9.99, "hogehoge"),
]
)

result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record)

:Output:
.. code::

(1, 1.1, u'aaa', 1, 1)
(7, 7.7, u'fff', 7.77, u'bar')
(8, 8.8, u'ggg', 8.88, u'foobar')
(9, 9.9, u'ggg', 9.99, u'hogehoge')

Get Data from a table as pandas DataFrame
-----------------------------------------

:Sample Code:
.. code:: python

from simplesqlite import SimpleSQLite

con = SimpleSQLite("sample.sqlite", "w", profile=True)

con.create_table_from_data_matrix(
table_name="sample_table",
attr_name_list=["a", "b", "c", "d", "e"],
data_matrix=[
[1, 1.1, "aaa", 1, 1],
[2, 2.2, "bbb", 2.2, 2.2],
[3, 3.3, "ccc", 3, "ccc"],
])

print(con.select_as_dataframe(table_name="sample_table"))

:Output:
.. code::

$ sample/select_as_dataframe.py
a b c d e
0 1 1.1 aaa 1.0 1
1 2 2.2 bbb 2.2 2.2
2 3 3.3 ccc 3.0 ccc

For more information
--------------------

More examples are available at
http://simplesqlite.rtfd.io/en/latest/pages/examples/index.html

Installation
============

::

pip install SimpleSQLite


Dependencies
============

Python 2.7+ or 3.3+

Mandatory
-----------------
- `DataPropery <https://github.com/thombashi/DataProperty>`__ (Used to extract data types)
- `logbook <http://logbook.readthedocs.io/en/stable/>`__
- `mbstrdecoder <https://github.com/thombashi/mbstrdecoder>`__
- `pathvalidate <https://github.com/thombashi/pathvalidate>`__
- `pytablereader <https://github.com/thombashi/pytablereader>`__
- `six <https://pypi.python.org/pypi/six/>`__
- `typepy <https://github.com/thombashi/typepy>`__


Test dependencies
-----------------
- `pytest <http://pytest.org/latest/>`__
- `pytest-runner <https://pypi.python.org/pypi/pytest-runner>`__
- `tox <https://testrun.org/tox/latest/>`__

Documentation
=============

http://simplesqlite.rtfd.io/

Related project
===============

- `sqlitebiter <https://github.com/thombashi/sqlitebiter>`__: CLI tool to convert CSV/Excel/HTML/JSON/LTSV/Markdown/TSV/Google-Sheets SQLite database by using SimpleSQLite


Keywords: SQLite,CSV,Google Sheets,JSON
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Database
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules