Replace sqlite3 with sqlean

[kracekumar]

Description

1. Sqlean is drop in replacement for sqlite3 with extra extensions.
2. It's built 12 extra extensions. From the website

Think of them as the extended standard library for SQLite:

    [crypto](https://antonz.org/sqlean-crypto/): Hashing, encoding and decoding data.
    [define](https://antonz.org/sqlean-define/): User-defined functions and dynamic SQL.
    [fileio](https://antonz.org/sqlean-fileio/): Reading and writing files and catalogs.
    [fuzzy](https://github.com/nalgeon/sqlean/blob/main/docs/fuzzy.md): Fuzzy string matching and phonetics.
    [ipaddr](https://github.com/nalgeon/sqlean/blob/main/docs/ipaddr.md): IP address manipulation.
    [math](https://github.com/nalgeon/sqlean/blob/main/docs/math.md): Math functions.
    [regexp](https://antonz.org/sqlean-regexp/): Pattern matching using regular expressions.
    [stats](https://github.com/nalgeon/sqlean/blob/main/docs/stats.md): Math statistics — median, percentiles, etc.
    [text](https://antonz.org/sqlean-text/): Powerful Unicode-aware string functions.
    [time](https://antonz.org/sqlean-time/): High-precision date/time.
    [uuid](https://github.com/nalgeon/sqlean/blob/main/docs/uuid.md): Universally Unique IDentifiers.
    [vsv](https://github.com/nalgeon/sqlean/blob/main/docs/vsv.md): CSV files as virtual tables.

3. This provides some extra extensions inside sqlite which can be handy as reported in writefile function with fileio #119
4. It's worth experimenting to see how it goes especially in terms of regression.
5. Note: I ran ruff formatter and it fixed a bunch of style issues.

Notes:

• I haven't used sqlean in production or in any other project not sure of any issues
• This may sound risky to replace sqlite3, though it's a drop-in replacement.

Checklist

• I've added this contribution to the CHANGELOG.md file.

[kracekumar]

All the formatting done by ruff.

[kracekumar]

Adding extra table and columns from sqlean define

[kracekumar]

Here is a simple benchmark

# -*- coding: utf-8 -*-

from litecli.main import LiteCli
import timeit


def perf():
    dbname=":memory:"
    cli = LiteCli()
    cli.connect(dbname)
    # Create a table
    cli.run_query("create table test (a text)")
    # Insert 10000 rows
    for i in range(10000):
        cli.run_query(f'insert into test values("{i}")')
    # Delete the table
    cli.run_query("drop table test")


def main():
    # timeit is not needed when using hyperfine
    print(timeit.timeit("perf()", globals=globals(), number=10))


if __name__ == "__main__":
    main()

Default Sqlite3

hyperfine --shell /opt/homebrew/bin/fish  --runs 5 --show-output  'uv run python litecli/performance.py'
Benchmark 1: uv run python litecli/performance.py
3.7350782089924905
3.7475891669892007
3.77843445900362
3.740818833000958
3.749061916998471
  Time (mean ± σ):      3.966 s ±  0.027 s    [User: 3.899 s, System: 0.050 s]
  Range (min … max):    3.944 s …  4.008 s    5 runs

Sqlean

 hyperfine --shell /opt/homebrew/bin/fish  --runs 5 --show-output  'uv run python litecli/performance.py'
Benchmark 1: uv run python litecli/performance.py
3.648521625000285
3.724126499990234
3.765500624998822
3.648744167003315
3.666765707996092
  Time (mean ± σ):      3.921 s ±  0.083 s    [User: 3.824 s, System: 0.066 s]
  Range (min … max):    3.854 s …  4.027 s    5 runs

I don't see much deviation in performance and I think it should be okay.

Let me know what you think.