SimpleSQLite
SimpleSQLite is a Python library to simplify SQLite database operations: table creation, data insertion and get data as other data formats. Simple ORM functionality for SQLite.
- 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 instance
- tabledata.TableData instance loaded by pytablereader
- Get data from a table as:
- pandas.DataFrame instance
- tabledata.TableData instance
- Simple object-relational mapping (ORM) functionality
Sample Code: | 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_a", "attr_b", "attr_c", "attr_d", "attr_e"],
data_matrix,
)
# display data type for each column in the table -----
print(con.schema_extractor.fetch_table_schema(table_name).dumps())
# display values in the table -----
print("records:")
result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record) |
---|---|
Output: | .. table:: sample_table
+---------+-------+-----------+--------+------+-----+
|Attribute| Type |PRIMARY KEY|NOT NULL|UNIQUE|Index|
+=========+=======+===========+========+======+=====+
|attr_a |INTEGER| | | | |
+---------+-------+-----------+--------+------+-----+
|attr_b |REAL | | | | |
+---------+-------+-----------+--------+------+-----+
|attr_c |TEXT | | | | |
+---------+-------+-----------+--------+------+-----+
|attr_d |REAL | | | | |
+---------+-------+-----------+--------+------+-----+
|attr_e |TEXT | | | | |
+---------+-------+-----------+--------+------+-----+
records:
(1, 1.1, 'aaa', 1.0, '1')
(2, 2.2, 'bbb', 2.2, '2.2')
(3, 3.3, 'ccc', 3.0, 'ccc')
|
Sample Code: | 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.fetch_attr_names(table_name))
result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record) |
---|---|
Output: | ['attr_a', 'attr_b', 'attr_c']
(1, 4.0, 'a')
(2, 2.1, 'bb')
(3, 120.9, 'ccc')
|
Sample Code: | 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: | $ sqlite3 pandas_df.sqlite
sqlite> .schema
CREATE TABLE 'pandas_df' (id INTEGER, value REAL, name TEXT); |
Sample Code: | from simplesqlite import SimpleSQLite
table_name = "sample_table"
con = SimpleSQLite("sample.sqlite", "w")
con.create_table_from_data_matrix(
table_name,
["attr_a", "attr_b", "attr_c", "attr_d", "attr_e"],
[[1, 1.1, "aaa", 1, 1]])
con.insert(
table_name,
record={
"attr_a": 4,
"attr_b": 4.4,
"attr_c": "ddd",
"attr_d": 4.44,
"attr_e": "hoge",
})
con.insert_many(
table_name,
records=[
{
"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: | (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)
|
Sample Code: | 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_a", "attr_b", "attr_c", "attr_d", "attr_e"],
[[1, 1.1, "aaa", 1, 1]],
)
# insert namedtuple
SampleTuple = namedtuple("SampleTuple", "attr_a attr_b attr_c attr_d attr_e")
con.insert(table_name, record=[7, 7.7, "fff", 7.77, "bar"])
con.insert_many(
table_name,
records=[(8, 8.8, "ggg", 8.88, "foobar"), SampleTuple(9, 9.9, "ggg", 9.99, "hogehoge")],
)
# print
result = con.select(select="*", table_name=table_name)
for record in result.fetchall():
print(record) |
---|---|
Output: | (1, 1.1, 'aaa', 1, 1)
(7, 7.7, 'fff', 7.77, 'bar')
(8, 8.8, 'ggg', 8.88, 'foobar')
(9, 9.9, 'ggg', 9.99, 'hogehoge')
|
Sample Code: | from simplesqlite import SimpleSQLite
con = SimpleSQLite("sample.sqlite", "w", profile=True)
con.create_table_from_data_matrix(
"sample_table",
["a", "b", "c", "d", "e"],
[
[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: | $ 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
|
Sample Code: | from simplesqlite import connect_memdb
from simplesqlite.model import Integer, Model, Real, Text
class Sample(Model):
foo_id = Integer(primary_key=True)
name = Text(not_null=True, unique=True)
value = Real(default=0)
def main() -> None:
con = connect_memdb()
Sample.attach(con)
Sample.create()
Sample.insert(Sample(name="abc", value=0.1))
Sample.insert(Sample(name="xyz", value=1.11))
Sample.insert(Sample(name="bar"))
print(Sample.fetch_schema().dumps())
print("records:")
for record in Sample.select():
print(f" {record}")
if __name__ == "__main__":
main() |
---|---|
Output: | .. table:: sample
+--------+---------+----------+-----+---------+-------+-------+
| Field | Type | Nullable | Key | Default | Index | Extra |
+========+=========+==========+=====+=========+=======+=======+
| foo_id | INTEGER | YES | PRI | NULL | X | |
+--------+---------+----------+-----+---------+-------+-------+
| name | TEXT | NO | UNI | | X | |
+--------+---------+----------+-----+---------+-------+-------+
| value | REAL | YES | | 0 | | |
+--------+---------+----------+-----+---------+-------+-------+
records:
Sample (foo_id=1, name=abc, value=0.1)
Sample (foo_id=2, name=xyz, value=1.11)
Sample (foo_id=3, name=bar, value=0.0)
|
More examples are available at https://simplesqlite.rtfd.io/en/latest/pages/examples/index.html
pip install SimpleSQLite
sudo add-apt-repository ppa:thombashi/ppa sudo apt update sudo apt install python3-simplesqlite
- loguru
- Used for logging if the package installed
- pandas
- pytablereader
- sqlitebiter: CLI tool to convert CSV/Excel/HTML/JSON/LTSV/Markdown/TSV/Google-Sheets SQLite database by using SimpleSQLite