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Python dict based database with persistence and search capabilities
For those times when you need something simple and sql is overkill
pip install json_database
This project includes a native hivemind-plugin-manager integration, providing seamless interoperability with the HiveMind ecosystem.
hivemind-json-db-plugin
allowing to use JSON-based storage for client credentials and permissionsSometimes you need persistent dicts that you can save and load from file
from json_database import JsonStorage
from os.path import exists
save_path = "my_dict.conf"
my_config = JsonStorage(save_path)
my_config["lang"] = "pt"
my_config["secondary_lang"] = "en"
my_config["email"] = "jarbasai@mailfence.com"
# my_config is a python dict
assert isinstance(my_config, dict)
# save to file
my_config.store()
my_config["lang"] = "pt-pt"
# revert to previous saved file
my_config.reload()
assert my_config["lang"] == "pt"
# clear all fields
my_config.clear()
assert my_config == {}
# load from a specific path
my_config.load_local(save_path)
assert my_config == JsonStorage(save_path)
# delete stored file
my_config.remove()
assert not exists(save_path)
# keep working with dict in memory
print(my_config)
Ever wanted to search a dict?
Let's create a dummy database with users
from json_database import JsonDatabase
db_path = "users.db"
with JsonDatabase("users", db_path) as db:
# add some users to the database
for user in [
{"name": "bob", "age": 12},
{"name": "bobby"},
{"name": ["joe", "jony"]},
{"name": "john"},
{"name": "jones", "age": 35},
{"name": "joey", "birthday": "may 12"}]:
db.add_item(user)
# pretty print database contents
db.print()
# auto saved when used with context manager
# db.commit()
search entries by key
from json_database import JsonDatabase
db_path = "users.db"
db = JsonDatabase("users", db_path) # load db created in previous example
# search by exact key match
users_with_defined_age = db.search_by_key("age")
for user in users_with_defined_age:
print(user["name"], user["age"])
# fuzzy search
users = db.search_by_key("birth", fuzzy=True)
for user, conf in users:
print("matched with confidence", conf)
print(user["name"], user["birthday"])
search by key value pair
# search by key/value pair
users_12years_old = db.search_by_value("age", 12)
for user in users_12years_old:
assert user["age"] == 12
# fuzzy search
jon_users = db.search_by_value("name", "jon", fuzzy=True)
for user, conf in jon_users:
print(user["name"])
print("matched with confidence", conf)
# NOTE that one of the users has a list instead of a string in the name, it also matches
updating an existing entry
# get database item
item = {"name": "bobby"}
item_id = db.get_item_id(item)
if item_id >= 0:
new_item = {"name": "don't call me bobby"}
db.update_item(item_id, new_item)
else:
print("item not found in database")
# clear changes since last commit
db.reset()
You can save arbitrary objects to the database
from json_database import JsonDatabase
db = JsonDatabase("users", "~/databases/users.json")
class User:
def __init__(self, email, key=None, data=None):
self.email = email
self.secret_key = key
self.data = data
user1 = User("first@mail.net", data={"name": "jonas", "birthday": "12 May"})
user2 = User("second@mail.net", "secret", data={"name": ["joe", "jony"], "age": 12})
# objects will be "jsonified" here, they will no longer be User objects
# if you need them to be a specific class use some ORM lib instead (SQLAlchemy is great)
db.add_item(user1)
db.add_item(user2)
# search entries with non empty key
print(db.search_by_key("secret_key"))
# search in user provided data
print(db.search_by_key("birth", fuzzy=True))
# search entries with a certain value
print(db.search_by_value("age", 12))
print(db.search_by_value("name", "jon", fuzzy=True))
FAQs
searchable json database with persistence
We found that json-database demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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