Malvina  O'Hara

Malvina O'Hara


A Python Module and Command Line Tool for Working with Fortran Namelists

f90nml - A Fortran namelist parser, generator, and editor

A Python module and command line tool for parsing Fortran namelist files


The complete documentation for f90nml is available from Read The Docs.

About f90nml

f90nml is a Python module and command line tool that provides a simple interface for the reading, writing, and modifying Fortran namelist files.

A namelist file is parsed and converted into an Namelist object, which behaves like a standard Python dict. Values are converted from Fortran data types to equivalent primitive Python types.

The command line tool f90nml can be used to modify individual values inside of a shell environment. It can also be used to convert the data between namelists and other configuration formats. JSON and YAML formats are currently supported.

Quick usage guide

To read a namelist file sample.nml which contains the following namelists:

   input = ''
   steps = 864
   layout = 8, 16
   visc = 1.0e-4
   use_biharmonic = .false.

we would use the following script:

import f90nml
nml ='sample.nml')

which would would point nml to the following dict:

nml = {
    'config_nml': {
        'input': '',
        'steps': 864,
        'layout': [8, 16],
        'visc': 0.0001,
        'use_biharmonic': False

File objects can also be used as inputs:

with open('sample.nml') as nml_file:
    nml =

To modify one of the values, say steps, and save the output, just manipulate the nml contents and write to disk using the write function:

nml['config_nml']['steps'] = 432

Namelists can also be saved to file objects:

with open('target.nml') as nml_file:

To modify a namelist but preserve its comments and formatting, create a namelist patch and apply it to a target file using the patch function:

patch_nml = {'config_nml': {'visc': 1e-6}}
f90nml.patch('sample.nml', patch_nml, 'new_sample.nml')

Command line interface

A command line tool is provided to manipulate namelist files within the shell:

$ f90nml config.nml -g config_nml -v steps=432
   input = ''
   steps = 432
   layout = 8, 16
   visc = 1.0e-4
   use_biharmonic = .false.

See the documentation for details.


f90nml is available on PyPI and can be installed via pip:

$ pip install f90nml

The latest version of f90nml can be installed from source:

$ git clone
$ cd f90nml
$ pip install .

Package distribution

f90nml is not distributed through any official packaging tools, but it is available on Arch Linux via the AUR:

$ git clone
$ cd python-f90nml
$ makepkg -sri

Volunteers are welcome to submit and maintain f90nml on other distributions.

Local install

Users without install privileges can append the --user flag to pip from the top f90nml directory:

$ pip install --user .

If pip is not available, then can still be used:

$ python install --user

When using locally, some users have reported that --prefix= may need to be appended to the command:

$ python install --user --prefix=

YAML support

The command line tool offers support for conversion between namelists and YAML formatted output. If PyYAML is already installed, then no other steps are required. To require YAML support, install the yaml extras package:

$ pip install f90nml[yaml]

To install as a user:

$ pip install --user .[yaml]

Contributing to f90nml

Users are welcome to submit bug reports, feature requests, and code contributions to this project through GitHub. More information is available in the Contributing guidelines.

Download Details:

Author: marshallward
Download Link: Download The Source Code
Official Website:
License: Apache-2.0


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A Python Module and Command Line Tool for Working with Fortran Namelists
Ray  Patel

Ray Patel


Top 20 Most Useful Python Modules or Packages

 March 25, 2021  Deepak@321  0 Comments

Welcome to my blog, In this article, we will learn the top 20 most useful python modules or packages and these modules every Python developer should know.

Hello everybody and welcome back so in this article I’m going to be sharing with you 20 Python modules you need to know. Now I’ve split these python modules into four different categories to make little bit easier for us and the categories are:

  1. Web Development
  2. Data Science
  3. Machine Learning
  4. AI and graphical user interfaces.

Near the end of the article, I also share my personal favorite Python module so make sure you stay tuned to see what that is also make sure to share with me in the comments down below your favorite Python module.

#python #packages or libraries #python 20 modules #python 20 most usefull modules #python intersting modules #top 20 python libraries #top 20 python modules #top 20 python packages

Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Lenora  Hauck

Lenora Hauck


4 Command-line tools for more Python productivity

4 Command-line tools for more Python productivity

June 20, 2015

Hi there folks. In this post I would be sharing a couple of command-line tools which can help to increase your python productivity. These tools have helped me a lot and might help you as well! This post is inspired by another post.

  1. IPython

IPython is the Python REPL on steroids. It has some really nice editions on top of the standard REPL. I am sure that if you use it once you will fall in love with it. The easiest way to install IPython is using pip:

$ pip install ipython

Now you can use it by typing this in your terminal:

$ ipython

You can read more about the nice features and tricks of IPython over here.

You can also automatically import modules when you enter the Python or IPython interpreter. Here is the Stackoverflow link which shows you how to do it.

more information.

  1. Autoenv

This is a simple tool built by Kenneth Reitz. It allows you to automatically activate your projects virtual environment.

You can install it using pip:

$ pip install autoenv

You can also use git:

$ git clone git:// ~/.autoenv
$ echo 'source ~/.autoenv/' >> ~/.bashrc

And if you are on Mac OSX then Homebrew is also an option:

$ brew install autoenv
$ echo 'source /usr/local/opt/autoenv/' >> ~/.bash_profile

What you have to do is make a file with the name of .env in your projects directory. The contents of that file will be somewhat like this:

#4 command #python #python productivity #4 command-line tools

Ray  Patel

Ray Patel


Difference Between Python Module and Python Package?

Difference between python module and python package?

What’s the difference between a Python module and a Python package?

Module:  It is a simple Python file that contains collections of functions and global variables and has a “.py”  extension file. It’s an executable file and we have something called a “Package” in Python to organize all these modules.

Package:  It is a simple directory which has collections of modules, i.e., a package is a directory of Python modules containing an additional  file. It is the  which maintains the distinction between a package and a directory that contains a bunch of Python scripts. A Package simply is a namespace. A package can also contain sub-packages.

When we import a module or a package, Python creates a corresponding object which is always of type module . This means that the dissimilarity is just at the file system level between module and package.

#technology #python #what's the difference between a python module and a python package? #python package #python module