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Introduction
Python is the programming language employed to create Web2py. A free, open-source web framework called Web2py allows for the rapid creation of safe, database-driven online applications. Web2py is a full-stack framework that includes all the components needed to build fully functional online applications. In this blog, we will learn about Lazy tables and replicated databases in web2py.
Lazy Tables: a significant performance boost
In Lazy Tables and replicated databases in Web2py, all tables are defined for each request because web2py models are processed before controllers. Some of the effort invested in determining tables is probably wasted because not all tables are required to serve every request. Although conditional models can be helpful, lazy_tables in web2py significantly improve performance. Due to this feature, the table's construction is delayed until it is referenced. Lazy tables are enabled when a database is initialized using the DAL constructor. Setting the parameter for "lazy tables" is necessary.
DAL(..., lazy_tables=True)
It is one of the most extensive response-time performance improvements in Lazy Tables and replicated databases in Web2py.
Model-less Applications
Using web2py's model directory for your application models is reasonably practical and effective. Even for large applications, performance is always adequate when using lazy tables and conditional models. This is used in production environments by many skilled developers.
However, DAL tables can be defined as on-demand inside controller functions or modules. This may make sense when lazy tables and conditional models are burdened by the quantity or complexity of table definitions.
The web2py community refers to this as "model-less" programming. It implies less use of the Python files in the model directory that are automatically executed. It does not mean that models, views, and controllers are no longer relevant in Lazy Tables and replicated databases in Web2py
Execution of code inside the model directory
Maintainability is another thing to keep in mind in Lazy Tables and replicated databases in Web2py. Other web2py developers anticipate finding model definitions in the model directory.
How to use the model-less approach
You are responsible for performing these two housekeeping duties if you employ the "model-less" method. When necessary, you call the table definitions, and the current object gives you access to the global scope.
For instance, a typical model-less application might define the tables on demand for each controller function but leave the definitions of the database connection objects in the model file.
Moving the table definitions to a module file is the usual scenario in Lazy Tables and replicated databases in Web2py(a Python file saved in the modules directory).
Your controller must call the define_mobileData_tables() function before accessing any tables if the function to define a set of tables is called define_mobileData_tables() in a module called "table setup.py".his is mandatory if you wish to employ the tables related to employee records to create an SQLFORM. In order to define tables, the define_mobileData_tables() function requires access to the database connection object. Because of this, you must utilize the current object in the module file that contains define_mobileData_tables()
Replicated Databases
A master-slave database architecture with numerous replicated slaves and possibly a few replicated servers may be used in a high-performance environment. Depending on the request parameters, the DAL can manage this scenario and connect to various services conditionally.
A list of URIs may be the initial input to DAL(...) functions. Web2py attempts to connect to each of them in this instance. The major goal is to manage and distribute workload among many database servers. A common use case is as follows:
db = DAL(['mysql://...1', 'mysql://...2', 'mysql://...3'])
If the initial connection attempt fails, the DAL will try the second and third connections. In a master-slave configuration for a database, this can also be utilized to share the load in Lazy Tables and replicated databases in Web2py
Frequently Asked Questions
What function does Web2py perform?
Web2py enables Python dynamic web content programming for web developers. Web2py is designed to reduce time-consuming web development tasks like creating web forms from scratch; however, a web developer can still do so if necessary.
Are Python web applications suitable?
Python is a popular choice for web development because of its key capabilities. Python is accessible, open-source, and cost-free to start. But perhaps more importantly, it is also very adaptable. Web designers may create websites utilizing a variety of programming paradigms thanks to Python.
Why should you learn Web2py?
Yes, Web2py is an excellent framework. One of the main goals of Web2py is to make usage as simple as possible, from installation to learning to code to distribution to deployment.
Explain DAL Python.
A Database Abstraction Layer (DAL), an API that transforms Python objects into database objects, including queries, tables, and records, is included with web2py.
Is web2py an MVC framework?
The Django and Ruby on Rails frameworks inspired the development of web2py. The model-view-controller (MVC) architectural paradigm is used by web2py, which prioritizes rapid growth and encourages convention over configuration.
Conclusion
This article extensively discussed the Lazy tables and replicated databases in Web2py, how it acts as a performance booster and the applications of the model-less approach in Web2py.
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