which is the best back end for python applications and what is the advantage of using sqlite ,how it can be connected to python applications
What do you mean with back end? Python apps connect to SQLite just like any other database, you just have to import the correct module and check how to use it.
The advantages of using SQLite are:
You don't need to setup a database server, it's just a file
No configurations needed
Cross platform
Mainly, desktops applications are the ones that take real advantage of this. For web apps, SQLite is not recommended, since the file containing the data, is easily readable (lacks any kind of encryption), and when the web server lacks special configuration, the file is downloadable by anyone.
Django, Twisted, and CherryPy are popular Python "Back-Ends" as far as web applications go, with Twisted likely being the most flexible as far as networking is concerned.
SQLite can, as has been previously posted, be directly interfaced with using SQL commands as it has native bindings for Python, or it can be accessed with an Object Relational Manager such as SQLObject (another Python library).
As far as performance is concered, SQLite is fairly scalable and should be able to handle most use cases that don't require a seperate database server (nothing enterprise level). An additional benefit of SQLite is that the database is self-contained in a single file allowing for easy backup while remained a common enough format that multiple applications can access the data. A word of advice on using SQLite with Python, however, is that you may run into issues with threading (in the past most of the bindings for SQLite were not thread-safe, although this may have changed over time).
The language you are using at the application layer has little to do with your database choice underneath. You need to examine the advantages of other DB packages to get an idea of what you want.
Here are some popular database packages for cheap or free:
ms sql server express, pg/sql, mysql
If you mean "what is the best database?" then there's simply no way to answer this question. If you just want a small database that won't be used by more than a handful of people at a time, SQLite is what you're looking for. If you're running a database for a giant corporation serving thousands, you're probably looking for Oracle. In between those, you have MySQL, PostgreSQL, SQL Server, db2, and probably more.
If you're familiar with one of those, that may be the best to go with from a practical standpoint. If you're doing a typical webapp, my advice would be to go with MySQL or PostgreSQL as they're free and well supported by just about any ORM you could think of (my personal preference is towards PostgreSQL, but I'm not experienced enough with either of these to make a good argument one way or another). If you do go with one of those two, my recommendation is to use storm as the ORM.
(And yes, there are free versions of SQL Server and Oracle. You won't have as many choices as far as ORMs go though)
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I am building this ecommerce app with django, and I was thinking if the default database (sqlite) was fine enough? My django app is going to have around 200 different products, and for payments I will use stripe API. I do not expect too much traffic when the app is up, since it's a website only for the country I live in with 6 million inhabitants. So can I settle with the sqlite database?
Although your answer may seem opinion based, the right answer is no anyways. SQLite3 is a lightweight database, which is commonlu used when your project is small and you don't mind to start up a server.
SQLite comes with following advantages and disadvantages (source)
Advantages of SQLite
Small footprint: As its name implies, the SQLite library is very lightweight. Although the space it uses varies depending on the system where it’s installed, it can take up less than 600KiB of space. Additionally, it’s fully self-contained, meaning there aren’t any external dependencies you have to install on your system for SQLite to work.
User-friendly: SQLite is sometimes described as a “zero-configuration” database that’s ready for use out of the box. SQLite doesn’t run as a server process, which means that it never needs to be stopped, started, or restarted and doesn’t come with any configuration files that need to be managed. These features help to streamline the path from installing SQLite to integrating it with an application.
Portable: Unlike other database management systems, which typically store data as a large batch of separate files, an entire SQLite database is stored in a single file. This file can be located anywhere in a directory hierarchy, and can be shared via removable media or file transfer protocol.
Disadvantages of SQLite
Limited concurrency: Although multiple processes can access and query an SQLite database at the same time, only one process can make changes to the database at any given time. This means SQLite supports greater concurrency than most other embedded database management systems, but not as much as client/server RDBMSs like MySQL or PostgreSQL.
No user management: Database systems often come with support for users, or managed connections with predefined access privileges to the database and tables. Because SQLite reads and writes directly to an ordinary disk file, the only applicable access permissions are the typical access permissions of the underlying operating system. This makes SQLite a poor choice for applications that require multiple users with special access permissions.
Security: A database engine that uses a server can, in some instances, provide better protection from bugs in the client application than a serverless database like SQLite. For example, stray pointers in a client cannot corrupt memory on the server. Also, because a server is a single persistent process, a client-server database cancontrol data access with more precision than a serverless database, allowing for more fine-grained locking and better concurrency.
It depends where are you going to host it. Some servers do not accept SQLite3 as database and require something more complicated as PostgreSQL (like Heroku). But if you are hosting by yourself (Rapsberry Pi for instance) then it's going to be fine and simple, if the site is going to have small traffic.
I'm comfortable with sqlite but when I use two different python program to access the same database. It throws an error like table is locked.
What are the different portable database to use with python?
SQLite is great but is designed as a small, fast, single user database. it isn't designed for the use you describe.
You can just pretty much any database with Python. The Python database API provides a straightforward way to interface with most relational databases, including SQLite.
However, to interact with a database in a more natural Python style, I've enjoyed using SQLAlchemy. It took a bit to work through the tutorial but it's great.
My personal preferred database is Postgres, but there are many other choices.
I have been developing a fairly simple desktop application to be used by a group of 100-150 people within my department mainly for reporting. Unfortunately, I have to build it within some pretty strict confines similar to the specs called out in this post. The application will just be a self contained executable with no need to install.
The problem I'm running into is figuring out how to handle the database need. There will probably only be about 1GB of data for the app, but it needs to be available to everyone.
I would embed the database with the application (SQLite), but the data needs to be refreshed every week from a centralized process, so I figure it would be easier to maintain one database, rather than pushing updates down to the apps. Plus users will need to write to the database as well and those updates need to be seen by everyone.
I'm not allowed to set up a server for the database, so that rules out any good options for a true database. I'm restricted to File Shares or SharePoint.
It seems like I'm down to MS Access or SQLite. I'd prefer to stick with SQLite because I'm a fan of python and SQLAlchemy - but based on what I've read SQLite is not a good solution for multiple users accessing it over the network (or even possible).
Is there another option I haven't discovered for this setup or am I stuck working with MS Access? Perhaps I'll need to break down and work with SharePoint lists and apps?
I've been researching this for quite a while now, and I've run out of ideas. Any help is appreciated.
FYI, as I'm sure you can tell, I'm not a professional developer. I have enough experience in web / python / vb development that I can get by - so I was asked to do this as a side project.
SQLite can operate across a network and be shared among different processes. It is not a good solution when the application is write-heavy (because it locks the database file for the duration of a write), but if the application is mostly reporting it may be a perfectly reasonable solution.
As my options are limited, I decided to go with a built in database for each app using SQLite. The db will only need updated every week or two, so I figured a 30 second update by pulling from flat files will be OK. then the user will have all data locally to browse as needed.
I am looking for a small database that can be "embedded" into my Python application without running a separate server, as one can do with SQLite or Metakit. I don't need an SQL database, in fact storing free-form data like Python dictionaries or JSON is preferable.
The other requirement is that to be able to run an instance of the database on a server, and have instances of my application (clients) sync the database with the server (two-way), similar to what CouchDB replication can do.
Is there a database that will do this?
From what you describe, it sounds like you could get by using pickle and FTP.
If you don't need an SQL database, what's wrong with CouchDB? You can spawn a local process to serve the DB, and you could easily write a server wrapper to allow only access from your app. I'm not sure about the access story, but I believe the latest Ubuntu uses CouchDB for synchronizeable user-level data.
Seems like the perfect job for CouchDB: 2 way sync is incredibly easy, schema-less JSON documents are the native format. If you're using python, couchdb-python is a great way to work with CouchDB.
Do you need clients to work offline and then resync when they reconnect to the network? I don't know if MongoDB can handle the offline client scenario, but if the client is online all the time, MongoDB might be a good solution too. It has pretty goode python support. Still a separate process, but perhaps easier to get running on Windows than CouchDB.
BerkeleyDB might be another option to check out, and it's lightweight enough. easy_install bsddb3 if you need a Python interface.
HSQLDB does this, but unfortunately it's Java rather than Python.
Firebird SQL might be closer to what you want, since it does seem to have a Python interface.
I am planning to make some big project (1 000 000 users, approximately 500 request pre second - in hot time).
For performance I'm going to use no relational dbms (each request could cost lot of instructions in relational dbms like mysql) - so i can't use DAL.
My question is:
how web2py is working with a big traffic, is it work concurrently? I'm consider to use web2py or Gork - Zope,
How is working zodb(Z Object Database) with a lot of data? Is there some comparison with object-relational postgresql?
Could you advice me please.
First, don't assume that a data abstraction layer will have unacceptable performance, until you actually see it in practice. It is pretty easy to switch to RAW sql if and when you run into a problem.
Second, most users who worry about there server technology handling a million users never finish their applications. Pick whatever technology you think will enable you to build the best application in the shortest time. Any technology can be scaled, at the very least, through clustering.
I agree with mikerobi - pick what will let you develop fastest. For me that is web2py.
web2py runs on Google App Engine, so if you don't want to use a relational database then you can use Google's datastore.
Zope and the ZODB have been used with big applications, but I'd still consider linking Zope with MySQL or something like that for serious large-scale applications. Even though Zope has had a lot of development cycles, it is usually used with another database engine for good reason. As far as I know, the argument applies doubly for web2py.