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Showing posts with label Python Developers. Show all posts
Showing posts with label Python Developers. Show all posts

Which language is better: Python or PHP?

Python Developers
Python Developers
With regard to better language between Python and PHP, Python is considered more easy and effective language. Generally the suitability depends on the nature and scale of assignments. Reading difficulty arises in case of large projects. Lots of more activities are going on with Python in the cloud. Google AppEngine would be more likely perfect example. When it comes to construct a scalable application platform, PHP is given less advantage as compared to Python. Yet it still takes over Python when it comes to database operations, IMHO.

There lies a number of distinction between the two language, but the most important part of discussion should be- which is more comfortable with the viewpoint of readability. Neither can be given less importance as you can also prefer PHP because it’s hard to find experienced Python developers. You can move along with any of the one according to your preference, knowing what people around you are of the view. If you are viewing it as a learning part, both the options are valid. But if you want to deal with it, you should go with the one which you find more reliable, whose performance is good and in which you are good at. You may get to know better difference after working on your preferred option. One thing that should be taken due care is that the one you opted should not create hindrance for you and ruin your everyday work.

Let’s make some comparisons between Python and PHP. Python could be considered a good option as it has a philosophy that helps to write better for understanding code. Though Python developers are not easily found, it has more compact and clean syntax that helps developers. Here you can do the same thing in the same way. What iterate things you are using among list, tuple, string or something else, is of no serious issue. You can always access by index, get a slice, iterate over it or can get the length in the same way.

Python is characterized with more extended and powerful standard library, much better than PHP. Most probably it coincide with exceptions with the object to improve working with exceptions in the future versions. It provides you with better namespaces and importing. All the things included in it are objects types, functions, objects, modules which can be introspected including ABC collections and other good batteries. Apart from these features, it also provides you with better support of functional programming style and also gives a better Unicode support (much better in Py3k). It is implemented with improved interactive interpreter mode. However, PHP is being subject to some negative feedback because the auto typing in PHP is broken which will cast the char ‘0’ into false. Casting of empty string into false might be useful, but not in the cases of zero digit strings. Thus it is bound by some of these limitations.

Neither of the languages are better than another, nor are they similar. Indeed PHP comes with some common demerits, but with its assistance you can accomplish anything you are reasoning to do with it, within the limits of normal web application. You can get served in various more ways than in PHP. On the other hand, for developing a web page, PHP seems to be more suitable. Not denying with the fact that most PHP codes out there is horrible, but at the same time it leads from the people writing it are untrained hobbyists. The only factor of differentiation here is the skill off the developer. Just because of inexperienced developers who have only passed through a couple of tutorials with limited assignments, this language is termed to be bad.

However, what ever language you are looking forward to get your web application developed, Laitkor development team is the right solution, may it be PHP application development or Python Application Development.

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5 Best Productivity Tools For Python Developers!

Python Development
Python Development
Python developers generally use tools for most of the serious Python development that shows a worthy trust. The private micro-projects could be easily done by simpler editors. But to a higher lever and to think even beyond that, one must not simply use a notepad to save a few Dollars. For Just-a-beginner, Integrated scm-tools (for git and others) and better Django Integration are very good to deal.

Some of the best productivity tools for python developers are as listed:

1.    PyCharm

PyCharm is an Integrated Development Environment(IDE), developed by a Czech Company JetBrains, and is used for programming in python. PyCharm has a vast plug-in-library to care for many of the needs. The main features of this tool are, it provides:

•    Code analysis
•    A graphical debugger
•    An integrated unit tester
•    Integration with version control system (VCSes)
•    Support wib development with Django.

2.    Spyder

Spyder (formally named as pydee ) is an open source  IDE for scientific programming in Python language. It was developed by Spyder developer community. Spyder is an efficient tool that integrates SciPy, NumPy, Ipython, Matplotlib and other software. It acts as a support to interactive tool for data inspection and other services. Spyder is an available cross platform through Anaconda and operates in different mode in different environment. It may be available:

•    On Mac Operating system (Mac OS) through MacPort,
•    On Windows with WinPython and Python(x,y),
•    On major linux distribution such as Fedora, Open  Suse, Debian Ubuntu and Gentoo .

3.    pip

pip is a package management system, written in Python and is used to install and manage software packages. One of the major advantage of pip rely on the fact that it provides a command line interface which allows the installation of Python software as easy as providing one command.  Python 2.7.9 (and the later on Python2 series) and Python 3.4 (and later) includes pip by default.

4.    Virtualenv

Virtualenv is a productivity tool and a Virtual Environment Software for Python. It may be a software, a program or a system that manages, implement and control multiple virtual environmental instance. Virtual environment can be extended to use in any field from Military Alliance to virtual classrooms.

5.    Ipython

Ipython is a cross platform operating system that has a command shell for interactive computing in multiple programming languages, which was originally designed for Python programming language, that offers introspection, shell syntax, rich media, tab completion and history.

We at Laitkor can always assist you in providing the necessary information regarding the best productivity tools for python developers.

Source Link: Python Developers
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Is web2py a good Python framework for web?

Python Development Services - Laitkor
Python Development Services - Laitkor
Web2py is one of the best Frameworks with the main goal to ease the use from setup to learning and extending towards distribution, coding and deployment. It is already able to manage things very well towards the verge of achieving goal and thus providing base to one of the successful python development Services.

Web2py: a good python web framework

1.    It offers a very wide variety of features set and allows a lot of flexibility. Day-by-day it is constantly improving with new releases every couple of weeks, and has attracted a very friendly, active and helpful community that is quickly growing.

2.    The documentations of web2py is excellent and is capable of getting support through extremely active mailing list. You are more expected to get a reply from a core developer within an hour or less.

3.    It is seen that many of the web2py modules can be used standalone or in conjunction with other frameworks. In fact a number of people are still using the DAL along with other frameworks, and even with non-web applications. Now Web2py offers gluino, which is a port of a number of the web2py modules for integration with the Flask, Bottle, Torando and Pyramid frameworks as well as wsgiref.

4.    It is totally up to you to decide if python is providing you your needs and web2py sticks to your requirement as a web framework. Web2py is easier to start for fresher candidate or beginners. The document may not be as good as Django but the user group is very helpful.

5.    After knowing web2py, you would find it easier to handle other web frameworks as well. It does not consume lots of time but would surely preach you lot of things.

6.    However, there are a few hindrances in the way of web2py. It is rare to find sites that combine web2py with other tools from the Python ecosystem. It is quite common to see non-web2py sites combine for nearly all sorts of things from the python world.

7.    If you are learning web2py, you must also learn another Python web tool as well. Flask would also be a good choice as it is small, lightweight and can probably be picked up in an evening.

If web2py is fulfilling all your needs, then it is the best choice for you. The python community and ecosystem is fantastic to go. If you only live in web2py, it may land you to a risk of wearing blinders to the bigger and better world. Web2py is excellent in terms of compatibility, gae compatibility, documentation and a lot more.
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Python development Services: How do you debug Python code?

Python Development Services - Laitkor
Python Development Services - Laitkor
Debugging process varies from one service to another. Python can fairly assist to debug complex code when using loops, and dealing with some data. You must go with test driven development methods and version control technique as the best way to ‘debug’ your code. This can be applied with appropriate discipline and precision that your bugs are instantly obvious and triflingly isolated.

Debug Python Code

1.    Pycharm is one of the best python IDE which has almost all the features that a programmer need. You can download the community version of pycharm for free. It could provide you happy coding or happy indenting.

2.    Python has a debugging module, but it is console based and not visual. It is effective and light weight once you get used to it. There are free IDE’s available for python, notably IDLE and PyDev.there are also commercial IDE’s, notably Komodo from ActiveState.

3.    If you have Visual Studio, there may be plug ins for python. PyDev in eclipse is much easier of syntax-highlighting editor like Notepad++ and python’s native debugger, etc.

4.    Pdb is a good choice for python programs. There is also pydb available which is an enhanced version of pdb which can also be used.

5.
   A debugger is simply one tool for actually debugging apps. Error handling, logging and simple print statements can be faster than debuggers. Visual Studio and C# are just one methodlogy of programming. You can certainly continue using best practices from that mindset, but you may find that just like python has different data structures and operations, it also has different ways of handling debugging than C#, of which a debugger app is just one.

6.    Pycharm from JetBrains is a really nice Python IDE. There are a lot more IDE present. You can move to TDD if you want. It makes a big difference for such a dynamic language, and people often end up using the debugger less. The convenience in trying thing interactively is another reason you see less use of debuggers among Python users.

7.    Python has a debugger built into the standard library: the Python Debugger. It is powerful, but the interface is a little arcane as is the documentation. Eclipse works for Python as well as for other languages, so it can also be a better option to use.

You can use Pycharm professional, but if you find comfortable with VS you should be aware that there is a very decent package called Python Tools for Visual Studio. It makes debugging Python fairly easy compared to some other tools. Give a try to few services and select those that fit your work best.

Do contact us in case of any queries related to Python development Services.
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Best template engines for Node.js and why?

Before we talk about Python and Python application development services,  it is necessary to understand the Core Python. The task could be performed very quickly by Django but it fails to answer the user about the feedback which lack understanding of the Core Python.

The application of Python is vast in field. From the development of web applications (like django, pylons and tornado) to scientific and numerical computations (like numpy, scipy or interface to R), networking or management automation and system administration, the scope of python is appreciable. Along with the application, the toolkit and the standard python library has a wide range of usage.
Python Application Development Services - Laitkor
Python Application Development Services
1.    Virtualenv
It is a python tool to create python environment. It is a virtual environment software to run Python/django and other apps and allow creation of new environment to install all package dependency into the Virtualenv, thus preventing the system’s site-packages. The package can be upgrated too. One can create a new Virtualenv, copy/install apps into it, run a test and delete it after the task.

2.    Pip
Pip is a package management system, written in Python and is used to install and manage software packages. It provides a command line Interface and a software can be installed in one command. Python developers keep this tool to reduce the time and increase the security. Python 2.7 and Python 3.4 include pip by default.

3.    Fabric
It is a command line tool and python (2.5 to 2.7) library as a platform to the use of SSH for apps deployment or system administration tasks. This helps to write deployment script and to create a basic suite operation for compiling local/remote shell command and uploading/downloading files and auxiliary functionality. The components of fabric may be imported to other Python code and provide high level Pythonic interface to SSH protocol suite.

For a Python tool developer or a software engineer working mainly on distributed systems and web application, it is mandatory to have one among django/ tornado/ pyramid/ bottle/ web.py or turbogears.

We at Laitkor can always assist you in providing the necessary information regarding the best tools that a modern python developers must have.


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Ready To Hire Python Developers For Your Enterprise?

Python has been used widely as a programming language by most of the developers. It is a general purpose high level language that has design philosophy highlights code readability and its syntax allows programmer to direct concepts in a few lines of code than that could be possible by using C++ or Java language.

Python Application Development - Laitkor
Python Application Development - Laitkor

Are you ready to hire?
There are few questions that a company generally wants the clear answer before hiring any Python developer. Here are few of them:
  1. Define Python
This is a very simple question that almost every candidate concocts themselves to answer such as a question. You, as a company recruiter must find one who clarifies the terms very well and specifically. It is a significant programming language that contains modules, exceptions, threads, objects and automatic memory management.
  1. Is there any benefit of using Python?
This is also a legal question that must be necessarily answered before moving ahead. Yes, there are a number of assistances of using Python as a programming language. The list of features generally include: simplicity, user-friendly, portability, extensibility and availability of default data structure.
  1. What is PEP 8?
It is a coding convention. PEP 8 is a collection of recommendations that make Python code more readable for programmers.
  1. Can you define Pickling and Unpickling?
Pickle is a module that can be used to convert Python into a string representation and dumps it into file with the help of “dumb” function. This complete process is known as Pickling. Talking about unpickling, it is a process in which developer retrieves original Python objects from the stored string representation.

  1. Can anyone manage memory in Python? Is there any special method?
Python memory can be managed by its Private Heap Space. All the objects and data structures of Python are located in a private Heap. There is also a nonpayment garbage collector that recycles the used memory, cleans it up and makes it available to that Heap Space.
  1. Is there any tool that helps in determining bugs in Python?
Yes, Lambda in Python is a single expression unidentified function that is often used as an inline function.
  1. What is Docstring?
When talking in terms of programming, a docstring is a string literal quantified in source code that can be used as like a comment, to document a specific segment of code.
  1. Explain the generators in Python?
A generator ‘generates’ value. Creating generators was made as straightforward as conceivable through the notion of generator functions, introduced concurrently.
  1. How to copy an object in Python?
Shallow copy conceptsa new compound objects and then inserts orientations into it to the objects found in the original. A deep copy ideas a new compound object and then, recursively, inserts copies into it of the objects found in the original.
There are many similar questions that can be asked from candidates who would like to get hired by your company. To hire Python developers having great development skills, you can ask them such discussed questions and judge them on the basis of quality answers and understanding.
With so many applications, it is hard to find a good Python developer for your Python application development, even though it is one of the most popular languages out there. By tapping into developer communities, you will be able to speak to developers who take their own resourcefulness to improve their technical skills. In order to interview successfully, it is significantly important to have a well-defined and well-planned hiring process that is tailored to the nuances of Python.

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Can A Company Intend A High-Performing EDA Tool in Python?

Most EDA tools accessible for programmers are compute intensive and retention intensive. Python Development Company treasures the idea great to use Python as a vanilla language to develop EDA tools. Chips have become more complex and transistor counts have increased exponentially with every cohort. This exponential evolution in intricacy and size has led to a conforming growth in EDA tool data-base sizes as well as computes power compulsory to processes these data-bases.


Python Development - Laitkor
Python Development - Laitkor

High-Performing EDA Tools in Python

 1. Most of the EDA tools are compute intensive as well as memory intensive; challenging high performance from a compute as well as competence standpoint. EDA Tools has to handle input data sets that contained signal level commotion over 100’s of millions of clock cycles and convey results in seconds. It has to scrutinize this signal level activity and recognize outlines and classify them. This practice is quite compute intensive and has to be achieved over large input data sets.

 2. Python is a high-productivity language. By some approximations, writing the same logic takes 1/6th the number of lines when equated to C. This is great for tool development as it permits developers to add functionality at a break-neck pace. It also allows developers to try different slants and select the one that works best.

3. On the other hand, Python does not have a status for high-performance is the forfeit developers have to recompense for the productivity gains a high-level language like Python offers. Untimely optimization is the root of all sinful, and so initially the tool developers focused more on functional accuracy and not so much on enactment. As the tool encountered real life data sets, performance bottlenecks became observable. Numerous iterations of presentation optimizations followed.

4. Initial performance optimizations were done with feedback from a performance profiler. The profiler recognized where the program was spending a lot of execution time. This helped to identify performance issues such as:
    • Sub optimally written code
    • Bad data-structures choice
    • Better algorithm choices
    • Memory VS Compute tradeoffs

    • 5. With the above optimizations identified and done in the Python Code, you can be able to get recital improvements of 50-70%.

    • During the process, some very grave routines may not be improved any further. By writing small parts of the program in C, you can profit from both, the high performance of C and the high-productivity of Python.

    • 6. For the next level of programming again, you have to look at parallelizing the tool’s core engine. This is where Python really shined. To parallelize the tool, you have to make some serious architectural changes. Using Python’s multi-processing library you could parallelize with ease. What would have taken 6 to 8 months in C may take less than 2 months and give another 20 to 50 % performance upgrading that depends on data input set.

    • 7. The PDA tool decodes high-level protocol packets and dealings from signal level information. It allows users to visualize system and unit activities in terms of lists of packets or state machines. The tool also checks for protocol mistakes and helps by providing several repair analysis and mechanization features.

    • Python’s rich high-level programming features and its C extensions competences allow you to achieve the performance objectives by using practices such as: Code or memory profiling, implementing small, performance critical kernel in C and parallelizing the core engine. Yes, it is possible to develop high-performance tools in Python.
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Before we talk about Python and Python application development services,  it is necessary to understand the Core Python. The task could be performed very quickly by Django but it fails to answer the user about the feedback which lack understanding of the Core Python.
The application of Python is vast in field. From the development of web applications (like django, pylons and tornado) to scientific and numerical computations (like numpy, scipy or interface to R), networking or management automation and system administration, the scope of python is appreciable. Along with the application, the toolkit and the standard python library has a wide range of usage.

Python application development services - Laitkor
Python application development services - Laitkor

A python developer’s basic and important tools:
1.    Virtualenv
It is a python tool to create python environment. It is a virtual environment software to run Python/django and other apps and allow creation of new environment to install all package dependency into the Virtualenv, thus preventing the system’s site-packages. The package can be upgrated too. One can create a new Virtualenv, copy/install apps into it, run a test and delete it after the task.

2.    Pip

Pip is a package management system, written in Python and is used to install and manage software packages. It provides a command line Interface and a software can be installed in one command. Python developers keep this tool to reduce the time and increase the security. Python 2.7 and Python 3.4 include pip by default.

3.    Fabric

It is a command line tool and python (2.5 to 2.7) library as a platform to the use of SSH for apps deployment or system administration tasks. This helps to write deployment script and to create a basic suite operation for compiling local/remote shell command and uploading/downloading files and auxiliary functionality. The components of fabric may be imported to other Python code and provide high level Pythonic interface to SSH protocol suite.
For a Python tool developer or a software engineer working mainly on distributed systems and web application, it is mandatory to have one among django/ tornado/ pyramid/ bottle/ web.py or turbogears.

We at Laitkor can always assist you in providing the necessary information regarding the best tools that a modern python developers must have.
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