A very fast in-memory database with export to sqlite written purely in python
Project description
pymemdb
will soon be available with
pip install pymemdb
Description
Very simple RDMBS that is supposed to serve as a drop-in replacement for a conventional DB during build-up. It is very fast, completely written in python und relies heavily on dictionaries. It features a to_sqlite export method - more DBs will follow.
Usage
Insert into a table
from pymemdb import Table
table = Table()
row1 = dict(firstname="John", lastname="Smith")
row2 = dict(firstname="Jane", lastname="Smith")
row3 = dict(firstname="John", lastname="Doe")
for row in [row1, row2, row3]:
table.insert(row)
iterate over the entire table
print(list(table.all()))
[{'id': 0, 'firstname': 'John', 'lastname': 'Smith'},
{'id': 1, 'firstname': 'Jane', 'lastname': 'Smith'},
{'id': 2, 'firstname': 'John', 'lastname': 'Doe'}]
update rows
table.update(where={"firstname": "Jane"}, firstname="Joanne")
print(list(table.all()))
[{'id': 0, 'firstname': 'John', 'lastname': 'Smith'},
{'id': 1, 'firstname': 'Joanne', 'lastname': 'Smith'},
{'id': 2, 'firstname': 'John', 'lastname': 'Doe'}]
search for rows
print(list(table.find(firstname="John")))
[{'id': 0, 'firstname': 'John', 'lastname': 'Smith'},
{'id': 2, 'firstname': 'John', 'lastname': 'Doe'}]
search for values in iterable
print(list(table.find(firstname=["John", "Joanne"])))
[{'id': 0, 'firstname': 'John', 'lastname': 'Smith'},
{'id': 1, 'firstname': 'Joanne', 'lastname': 'Smith'},
{'id': 2, 'firstname': 'John', 'lastname': 'Doe'}]
delete rows
table.delete(firstname="John", lastname="Smith")
print(list(table.all()))
[{'id': 1, 'firstname': 'Joanne', 'lastname': 'Smith'},
{'id': 2, 'firstname': 'John', 'lastname': 'Doe'}]
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pymemdb-1.4.3.tar.gz.
File metadata
- Download URL: pymemdb-1.4.3.tar.gz
- Upload date:
- Size: 11.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.24.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5320351d3a2da16cc7f7b27a0844bdbbbae0ea40f7bbe57a108528ce49d93b80
|
|
| MD5 |
f2a9684a7128805fe8009b6e5d0c85a6
|
|
| BLAKE2b-256 |
253758f2d772c1958eddedca136bd88fa2795bea71eb87ba2f9d741b774de3a1
|
File details
Details for the file pymemdb-1.4.3-py3-none-any.whl.
File metadata
- Download URL: pymemdb-1.4.3-py3-none-any.whl
- Upload date:
- Size: 7.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.24.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
df7e8b17cea4291624109e884f624b04e909f0bd33b9397c2fceac35c89dce53
|
|
| MD5 |
f21cf81f0a27671cfb151ca26d60b366
|
|
| BLAKE2b-256 |
105241a9100f0d55a21eacfcfc10c5d00c29e58e94c4996e41cc43bdd4098fb4
|