NORM
Not an ORM (NORM) was created by me during my third semester of BTech as a side project. A pandas like interface for SQL.
SQLiteHandler
V1.0
- Keeps a buffer to serialize transactions (even if threaded).
With pythonic syntax, store data in an sql file.
Known Issues / Features that can be added later
- Vulnerable to SQLInjection
- Storage of Arrays and Dicts can be done by normalisation
- SQLite3 does not allow the deletion of columns directly. (Unit test added)
- Queries for a column is not working. (Unit test added)
Connecting to a database
from NORM import SQLiteHandler as db
main = db.database("main.db",tables = [db.table("Cars",columns = [db.column("Manufacturer",str),db.column("Model",str),db.column("Year",int)])])This above snippet asks to connect to main.db with considering only one table that is named "Cars" with columns "Manufacturer","Model" and "Year" with the respective data types.
Writing Queries
Fetching data
In order to fetch all the models by Ferrari before 1999,
Connecting to a database
from NORM import SQLiteHandler as db
main = db.database("main.db",tables = [db.table("Cars",columns = [db.column("Manufacturer",str),db.column("Model",str),db.column("Year",int)])])
print(main["Cars"][main["Cars"]["Manufacturer"] == 'Ferrari'])
#This prints only the cars with Manufacturer as Ferrari
print(main["Cars"][main["Cars"]["Year"]<1999])
#This prints only the cars with Year smaller than 1999
print(main["Cars"][(main["Cars"]["Year"]<1999) and (main["Cars"]["Manufacturer"] == 'Ferrari'])])
#This prints all the information about Ferrari's before 1999
print(main["Cars"][(main["Cars"]["Year"]<1999) and (main["Cars"]["Manufacturer"] == 'Ferrari']),'Model'])
#This only prints the Models of Ferrari's before 1999Adding Data
from NORM import SQLiteHandler as db
main = db.database("main.db",tables = [db.table("Cars",columns = [db.column("Manufacturer",str),db.column("Model",str),db.column("Year",int)])])
main["Cars"].append({"Manufacturer":"Ferrari","Model":"Enzo","Year":1999})
#Adding single row of data
main["Cars"].append([{"Manufacturer":"Ferrari","Model":"Enzo","Year":1999},{"Manufacturer":"Audi","Model":"R8",Year:2007}])
#Adding multiple rows of dataModifying Data
In order to increament the years by 10 and then replace all the Volkswagen with Vw,
from NORM import SQLiteHandler as db
main = db.database("main.db",tables = [db.table("Cars",columns = [db.column("Manufacturer",str),db.column("Model",str),db.column("Year",int)])])
main["Cars"]["Year"]+=10
#This increaments all the year by 10
main["Cars"][main["Cars"]["Manufacturer"]=="Volkswagen","Manufacturer"] = "Vw" # WARNING: Test Failing
#This searches for all the Cars with Manufacturers Volkswagen and then store in the Manufacturers column "vw" which satisfies the query.Deleting Data
from NORM import SQLiteHandler as db
main = db.database("main.db",tables = [db.table("Cars",columns = [db.column("Manufacturer",str),db.column("Model",str),db.column("Year",int)])])
del main["Cars"][main["Cars"]["Manufacturer"]=="Ferrari","Year"]
#Removes the Year attribute of all the Cars where Manufacturer is Ferrari
del main["Cars"][main["Cars"]["Manufacturer"]=="Ferrari"]
#Deletes all the rows where Manufacturer is Ferrari
del main["Cars"]["Year"]# WARNING: Test Failing
#Deletes the column year
del main["Cars"]
#Deletes the table cars from database