podb
(p)ython (o)bject (d)ata(b)ase
thread safe, file based, redis style database for python objects
it really just is shelve with a hat on
reasons not to use this
- you want a database cluster
- you have multiple billions of database entries and limited storage space
- you need relationships
reasons to use this
- pure python
- cross-platform (Tested: Windows & Linux)
- fast
- inserting 200 objects takes
- ~0.0003 seconds (i7-4702MQ)
- ~0.0001 seconds (Ryzen 9 3900xt)
- 8-8.3k inserts per second (Ryzen 7 2700X)
- 19k inserts per second (Ryzen 9 3900xt)
- inserting 200 objects takes
- thread safe
- stores python objects
- filters, see below
- ~180 loc
functions
- find
- find_one
- find_after
- find_before
- find_by_uuid
- find_contains
- find_startswith
- find_endswith
- insert
- insert_many
- update
- update_many
- upsert
- upsert_many
- size
- contains
- columns
- drop
- delete
- delete_by_uuid
- delete_before
- get_all
- get_random
- get_random_list
example
from podb import DB, DBEntry
class Company(DBEntry):
def __init__(self, name: str):
DBEntry.__init__(self)
self.name = name
class Customer(DBEntry):
def __init__(self, first_name: str, last_name: str, age: int,
height: float, companies: list[DBEntry]):
DBEntry.__init__(self)
self.first_name = first_name
self.last_name = last_name
self.age = age
self.height = height
self.companies = companies
db = DB("customers")
c0 = Customer("Jeff", "Bezoz", 42, 1.69,
[Company("Whole Foods"), Company("Zappos"),
Company("Ring"), Company("twitch")])
db.insert(c0)
c0 = db.find_one({
"first_name": "Jeff",
"last_name": "Bezoz"
})
c0.companies.append(Company("Audible"))
db.update(c0)
installation
pip3 install podb
1 maintainer
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