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In Linux systems, you can create new directories either from the command line or with the help of your desktop’s file manager. The command that allows you to create directories (also known as folders) is mkdir
.
This tutorial covers the basics of using the mkdir
command, including everyday examples.
The syntax for the mkdir
command is as follows:
mkdir [OPTION] [DIRECTORY]
The command takes one or more directory names as its arguments.
To create a directory in Linux pass the name of the directory as the argument to the mkdir
command. For example, to create a new directory newdir
you would run the following command:
mkdir newdir
You can verify that the directory was created by listing the contents using the [ls](https://linuxize.com/post/how-to-list-files-in-linux-using-the-ls-command/)
command :
ls -l
drwxrwxr-x 2 username username 4096 Jan 20 03:39 newdir
When providing only the directory name, without the full path, it is created in the current working directory.
The current working directory is the directory from which you are running the commands. To change the current working directory, use the [cd](https://linuxize.com/post/linux-cd-command/)
command.
To create a directory in another location you’ll need to provide the absolute or relative file path to the parent directory. For example, to create a new directory in the /tmp
directory you would type:
mkdir /tmp/newdir
If you try to create a directory in a parent directory where the user does not have sufficient permissions you will receive Permission denied
error:
mkdir /root/newdir
mkdir: cannot create directory '/root/newdir': Permission denied
The -v
(--verbose
) option tells mkdir
to print a message for each created directory.
A parent directory is a directory that is above another directory in the directory tree. To create parent directories, use the -p
option.
Let’s say you want to create a directory /home/linuxize/Music/Rock/Gothic
:
mkdir /home/linuxize/Music/Rock/Gothic
If any of the parent directories don’t exist you will get an error as shown below:
mkdir: cannot create directory '/home/linuxize/Music/Rock/Gothic': No such file or directory
Instead of creating the missing parent directories one by one, invoke the mkdir
command with the -p
option:
mkdir -p /home/linuxize/Music/Rock/Gothic
When the -p
option is used, the command creates the directory only if it doesn’t exist.
If you try to create a directory that already exists and the -p
option is not provided, mkdir
will print File exists
error:
mkdir newdir
mkdir: cannot create directory 'newdir': File exists
#linux
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Install via pip:
$ pip install pytumblr
Install from source:
$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install
A pytumblr.TumblrRestClient
is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:
client = pytumblr.TumblrRestClient(
'<consumer_key>',
'<consumer_secret>',
'<oauth_token>',
'<oauth_secret>',
)
client.info() # Grabs the current user information
Two easy ways to get your credentials to are:
interactive_console.py
tool (if you already have a consumer key & secret)client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user
client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog
client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post
client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog
Creating posts
PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.
The default supported types are described below.
We'll show examples throughout of these default examples while showcasing all the specific post types.
Creating a photo post
Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload
#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")
#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
tweet="Woah this is an incredible sweet post [URL]",
data="/Users/johnb/path/to/my/image.jpg")
#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
caption="## Mega sweet kittens")
Creating a text post
Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html
#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")
Creating a quote post
Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported
#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")
Creating a link post
#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
description="Search is pretty cool when a duck does it.")
Creating a chat post
Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)
#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])
Creating an audio post
Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr
#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")
#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")
Creating a video post
Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload
#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
embed="http://www.youtube.com/watch?v=40pUYLacrj4")
#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")
Editing a post
Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.
client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")
Reblogging a Post
Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.
client.reblog(blogName, id=125356, reblog_key="reblog_key")
Deleting a post
Deleting just requires that you own the post and have the post id
client.delete_post(blogName, 123456) # Deletes your post :(
A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):
client.create_text(blogName, tags=['hello', 'world'], ...)
Getting notes for a post
In order to get the notes for a post, you need to have the post id and the blog that it is on.
data = client.notes(blogName, id='123456')
The results include a timestamp you can use to make future calls.
data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])
# get posts with a given tag
client.tagged(tag, **params)
This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).
You'll need pyyaml
installed to run it, but then it's just:
$ python interactive-console.py
and away you go! Tokens are stored in ~/.tumblr
and are also shared by other Tumblr API clients like the Ruby client.
The tests (and coverage reports) are run with nose, like this:
python setup.py test
Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license
1620616862
In this remove or delete directories and files linux tutorial guide, you will learn how to remove empty directory and non empty directory linux using command line. And as well as how to remove/file files linux using command line.
So, this tutorial guide will show you you how to use the rm
, unlink
, and rmdir
commands to remove or delete files and directories in Linux with and without confirmation.
https://www.tutsmake.com/how-to-remove-directories-and-files-using-linux-command-line/
#how to delete directory in linux #how to remove non empty directory in linux #remove all files in a directory linux #linux delete all files in current directory #linux delete all files in a directory recursively #delete all files in a directory linux
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How to Make a New Directory In Linux
To create a directory using the **_mkdir _**command in linux with terminal.
Note : To create a hidden directory, follow our guide on how to show and create hidden files in Linux.
How to Create Multiple Directories with mkdir
If you want to create multiple directory at once command. So, you can use a single mkdir command to create multiple directories at once.
Note that, Do not add any spaces in the curly brackets for the directory names.
How to Make Parent Directories
Note that, you can use ls -R to display the recursive directory tree in linux. And Without the -p option, the terminal returns an error if one of the directories in the string does not exist.
#linux #directories #command #mkdir command
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In this Python article, let's learn about Mutable and Immutable in Python.
Mutable is a fancy way of saying that the internal state of the object is changed/mutated. So, the simplest definition is: An object whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created.
Both of these states are integral to Python data structure. If you want to become more knowledgeable in the entire Python Data Structure, take this free course which covers multiple data structures in Python including tuple data structure which is immutable. You will also receive a certificate on completion which is sure to add value to your portfolio.
Mutable is when something is changeable or has the ability to change. In Python, ‘mutable’ is the ability of objects to change their values. These are often the objects that store a collection of data.
Immutable is the when no change is possible over time. In Python, if the value of an object cannot be changed over time, then it is known as immutable. Once created, the value of these objects is permanent.
Objects of built-in type that are mutable are:
Objects of built-in type that are immutable are:
Object mutability is one of the characteristics that makes Python a dynamically typed language. Though Mutable and Immutable in Python is a very basic concept, it can at times be a little confusing due to the intransitive nature of immutability.
In Python, everything is treated as an object. Every object has these three attributes:
While ID and Type cannot be changed once it’s created, values can be changed for Mutable objects.
Check out this free python certificate course to get started with Python.
I believe, rather than diving deep into the theory aspects of mutable and immutable in Python, a simple code would be the best way to depict what it means in Python. Hence, let us discuss the below code step-by-step:
#Creating a list which contains name of Indian cities
cities = [‘Delhi’, ‘Mumbai’, ‘Kolkata’]
# Printing the elements from the list cities, separated by a comma & space
for city in cities:
print(city, end=’, ’)
Output [1]: Delhi, Mumbai, Kolkata
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(cities)))
Output [2]: 0x1691d7de8c8
#Adding a new city to the list cities
cities.append(‘Chennai’)
#Printing the elements from the list cities, separated by a comma & space
for city in cities:
print(city, end=’, ’)
Output [3]: Delhi, Mumbai, Kolkata, Chennai
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(cities)))
Output [4]: 0x1691d7de8c8
The above example shows us that we were able to change the internal state of the object ‘cities’ by adding one more city ‘Chennai’ to it, yet, the memory address of the object did not change. This confirms that we did not create a new object, rather, the same object was changed or mutated. Hence, we can say that the object which is a type of list with reference variable name ‘cities’ is a MUTABLE OBJECT.
Let us now discuss the term IMMUTABLE. Considering that we understood what mutable stands for, it is obvious that the definition of immutable will have ‘NOT’ included in it. Here is the simplest definition of immutable– An object whose internal state can NOT be changed is IMMUTABLE.
Again, if you try and concentrate on different error messages, you have encountered, thrown by the respective IDE; you use you would be able to identify the immutable objects in Python. For instance, consider the below code & associated error message with it, while trying to change the value of a Tuple at index 0.
#Creating a Tuple with variable name ‘foo’
foo = (1, 2)
#Changing the index[0] value from 1 to 3
foo[0] = 3
TypeError: 'tuple' object does not support item assignment
Once again, a simple code would be the best way to depict what immutable stands for. Hence, let us discuss the below code step-by-step:
#Creating a Tuple which contains English name of weekdays
weekdays = ‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’
# Printing the elements of tuple weekdays
print(weekdays)
Output [1]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(weekdays)))
Output [2]: 0x1691cc35090
#tuples are immutable, so you cannot add new elements, hence, using merge of tuples with the # + operator to add a new imaginary day in the tuple ‘weekdays’
weekdays += ‘Pythonday’,
#Printing the elements of tuple weekdays
print(weekdays)
Output [3]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Pythonday’)
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(weekdays)))
Output [4]: 0x1691cc8ad68
This above example shows that we were able to use the same variable name that is referencing an object which is a type of tuple with seven elements in it. However, the ID or the memory location of the old & new tuple is not the same. We were not able to change the internal state of the object ‘weekdays’. The Python program manager created a new object in the memory address and the variable name ‘weekdays’ started referencing the new object with eight elements in it. Hence, we can say that the object which is a type of tuple with reference variable name ‘weekdays’ is an IMMUTABLE OBJECT.
Also Read: Understanding the Exploratory Data Analysis (EDA) in Python
Where can you use mutable and immutable objects:
Mutable objects can be used where you want to allow for any updates. For example, you have a list of employee names in your organizations, and that needs to be updated every time a new member is hired. You can create a mutable list, and it can be updated easily.
Immutability offers a lot of useful applications to different sensitive tasks we do in a network centred environment where we allow for parallel processing. By creating immutable objects, you seal the values and ensure that no threads can invoke overwrite/update to your data. This is also useful in situations where you would like to write a piece of code that cannot be modified. For example, a debug code that attempts to find the value of an immutable object.
Watch outs: Non transitive nature of Immutability:
OK! Now we do understand what mutable & immutable objects in Python are. Let’s go ahead and discuss the combination of these two and explore the possibilities. Let’s discuss, as to how will it behave if you have an immutable object which contains the mutable object(s)? Or vice versa? Let us again use a code to understand this behaviour–
#creating a tuple (immutable object) which contains 2 lists(mutable) as it’s elements
#The elements (lists) contains the name, age & gender
person = (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])
#printing the tuple
print(person)
Output [1]: (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])
#printing the location of the object created in the memory address in hexadecimal format
print(hex(id(person)))
Output [2]: 0x1691ef47f88
#Changing the age for the 1st element. Selecting 1st element of tuple by using indexing [0] then 2nd element of the list by using indexing [1] and assigning a new value for age as 4
person[0][1] = 4
#printing the updated tuple
print(person)
Output [3]: (['Ayaan', 4, 'Male'], ['Aaradhya', 8, 'Female'])
#printing the location of the object created in the memory address in hexadecimal format
print(hex(id(person)))
Output [4]: 0x1691ef47f88
In the above code, you can see that the object ‘person’ is immutable since it is a type of tuple. However, it has two lists as it’s elements, and we can change the state of lists (lists being mutable). So, here we did not change the object reference inside the Tuple, but the referenced object was mutated.
Also Read: Real-Time Object Detection Using TensorFlow
Same way, let’s explore how it will behave if you have a mutable object which contains an immutable object? Let us again use a code to understand the behaviour–
#creating a list (mutable object) which contains tuples(immutable) as it’s elements
list1 = [(1, 2, 3), (4, 5, 6)]
#printing the list
print(list1)
Output [1]: [(1, 2, 3), (4, 5, 6)]
#printing the location of the object created in the memory address in hexadecimal format
print(hex(id(list1)))
Output [2]: 0x1691d5b13c8
#changing object reference at index 0
list1[0] = (7, 8, 9)
#printing the list
Output [3]: [(7, 8, 9), (4, 5, 6)]
#printing the location of the object created in the memory address in hexadecimal format
print(hex(id(list1)))
Output [4]: 0x1691d5b13c8
As an individual, it completely depends upon you and your requirements as to what kind of data structure you would like to create with a combination of mutable & immutable objects. I hope that this information will help you while deciding the type of object you would like to select going forward.
Before I end our discussion on IMMUTABILITY, allow me to use the word ‘CAVITE’ when we discuss the String and Integers. There is an exception, and you may see some surprising results while checking the truthiness for immutability. For instance:
#creating an object of integer type with value 10 and reference variable name ‘x’
x = 10
#printing the value of ‘x’
print(x)
Output [1]: 10
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(x)))
Output [2]: 0x538fb560
#creating an object of integer type with value 10 and reference variable name ‘y’
y = 10
#printing the value of ‘y’
print(y)
Output [3]: 10
#Printing the location of the object created in the memory address in hexadecimal format
print(hex(id(y)))
Output [4]: 0x538fb560
As per our discussion and understanding, so far, the memory address for x & y should have been different, since, 10 is an instance of Integer class which is immutable. However, as shown in the above code, it has the same memory address. This is not something that we expected. It seems that what we have understood and discussed, has an exception as well.
Quick check – Python Data Structures
Tuples are immutable and hence cannot have any changes in them once they are created in Python. This is because they support the same sequence operations as strings. We all know that strings are immutable. The index operator will select an element from a tuple just like in a string. Hence, they are immutable.
Like all, there are exceptions in the immutability in python too. Not all immutable objects are really mutable. This will lead to a lot of doubts in your mind. Let us just take an example to understand this.
Consider a tuple ‘tup’.
Now, if we consider tuple tup = (‘GreatLearning’,[4,3,1,2]) ;
We see that the tuple has elements of different data types. The first element here is a string which as we all know is immutable in nature. The second element is a list which we all know is mutable. Now, we all know that the tuple itself is an immutable data type. It cannot change its contents. But, the list inside it can change its contents. So, the value of the Immutable objects cannot be changed but its constituent objects can. change its value.
Mutable Object | Immutable Object |
State of the object can be modified after it is created. | State of the object can’t be modified once it is created. |
They are not thread safe. | They are thread safe |
Mutable classes are not final. | It is important to make the class final before creating an immutable object. |
list, dictionary, set, user-defined classes.
int, float, decimal, bool, string, tuple, range.
Lists in Python are mutable data types as the elements of the list can be modified, individual elements can be replaced, and the order of elements can be changed even after the list has been created.
(Examples related to lists have been discussed earlier in this blog.)
Tuple and list data structures are very similar, but one big difference between the data types is that lists are mutable, whereas tuples are immutable. The reason for the tuple’s immutability is that once the elements are added to the tuple and the tuple has been created; it remains unchanged.
A programmer would always prefer building a code that can be reused instead of making the whole data object again. Still, even though tuples are immutable, like lists, they can contain any Python object, including mutable objects.
A set is an iterable unordered collection of data type which can be used to perform mathematical operations (like union, intersection, difference etc.). Every element in a set is unique and immutable, i.e. no duplicate values should be there, and the values can’t be changed. However, we can add or remove items from the set as the set itself is mutable.
Strings are not mutable in Python. Strings are a immutable data types which means that its value cannot be updated.
Join Great Learning Academy’s free online courses and upgrade your skills today.
Original article source at: https://www.mygreatlearning.com
1625631509
Dig Command Line Options and Examples
Here is the frequently used command line options and example’s of dig command.
1. Basic Dig Command
A basic dig command accept domain name as command line parameter and prints Address record.
2. Query With Specific DNS Server
The default dig command queries to dns server configured on your system. For example, the Linux systems keep default DNS entry in /etc/resolv.conf.
3. Print Short Answer
Use +short command line option to print result in short form. This is basically useful with the shell scripting and other automation tasks.
4. Print Detailed but Specific Result
Use +noall with +answer to print detailed information but specific. This will print only answer section including few more details as a result.
#linux commands #command #dig #dig command #useful examples #linux