Migrate an Existing Project to AndroidX

AndroidX is an open-source project by Google that provides a major improvement to the original Android Support Library. AndroidX is replaced the Support Library. Like support library, Google keeps AndroidX is independently from the Android OS and provides backward-compatibility across Android releases. AndroidX package structure is to encourage smaller and more focused libraries.

AndroidX replaces the original support library APIs with packages in the androidx namespace. Only the package and import names changed. Class, method, and field names did not change in migration.

Example:-

android.support.v7.widget.RecyclerView is changed to androidx.recyclerview.widget.RecyclerView

android.support.v7 is replced by androidx.

Migrating existing project:-

Before start migration, we need to make sure to follow the below things:-

1.  Android studio version should be higher than 3.2, You can check your android studio version from About Android Studio section. also use the latest Gradle version. Check project level Build.Gradle file to change the version.

2. Target SDK version and Compile SDK version should be 28 or greater. Check your app level Build.Gradle file to change target and compile SDK version.

3. Take a backup of your project. 

4. Add below properties to gradle.properties file. You can find this file on Project Level.

A.) android.useAndroidX: set to true, the Android plugin uses the AndroidX library instead of a Support Library. The value is false by default.

B.) android.enableJetifier: set to true, the Android plugin automatically migrates existing third-party libraries to use AndroidX. The value is false by default.

Let’s start migration:-

1.  Click Refactor from the menu in Android studio.

2. Then Click on Migrate to AndroidX from Refactor dropdown.

3. After that, It will ask you to take a backup of the whole project. If you have already taken the backup then ignore this step.

4. After the backup process clicks on Migrate, It will show list all support library where we are using in this project. Just click on Do Refactor and wait for some time.

5. After some time, you can see the project all support library replaced by the AndroidX library. Most of the support library will merge automatically and few we need to replaced manually. If you found any error,  Fix it manually. and test your app carefully. The application could crash due to incorrect auto-correction during migration.

That’s it. Enjoy Coding using AndroidX. 🙂

Reference:-

https://developer.android.com/jetpack/androidx/migrate

Shell script wrapper function for sending messages through Pushover

Pushover makes it easy to get real-time notifications on your Android, iPhone, iPad, and Desktop (Android Wear and Apple Watch, too!)

You can use this shell function anywhere in your script.

Example:

Note: you need to update API tokens and title above

Fetch Contacts From Native Phonebook

Import Contacts In iOS

Contacts are We are going to use built in Contacts.framework to import all contacts in our app. To display a list of contacts, you must have access to the user’s address book. Apple does a great job of protecting the user’s privacy, so you can’t read any of their contacts’ data without asking the user for permission. Similar restrictions apply to access the user’s camera, location, photos, and more.

Whenever we need access to privacy-sensitive information, you are required to specify this in your app’s Info.plist file. This file keeps track of many of your app’s properties, such as its display name, supported interface orientations, and, in the case of accessing a user’s contacts, Info.plist also contains information about why you need access to the user’s contacts.

Let’s go step by step:-

  • Add usage description in Info.plist file for contacts.

Open Plist file and click on plus button to add new row for contact usage description.

Add Privacy – Contacts Usage Description in key

Select Type as String

Write the usage purpose of contacts in your app.

  • Import Contacts Framework in your class.

 

  •  Request for Contact permission

 

Above two function will check Contact authorisation status. If not determined it will show alert for contact permission. Keep in mind you can ask Contact permission only once. Once user denied you can just open Setting screen for enable Contact permission.

  • Fetch Contact Using CNContactStore:-

 

We create a CNContactStore instance and this object is used to communicate directly with the Contacts system on iOS. In this method, we wrap our code in a do-catch statement because two of the methods we use are throwing methods.We can retrieve different values using different Keys like first name, last name, contact image, mobile number, address, emails etc. We then create an array that contains a number of constant keys. These keys directly relate to the information your app has access too.

There is different container Group in Native phonebook. We can retrieve Contacts from different Container according our need. Here we are retrieving contacts of all Groups using store.containers(matching: nil) and iterate it one by one to fetch contacts.

store.unifiedContacts will return array of CNContact which you can store in Your app data or in your app’s database and display contacts In your own tableview Format.

Important:-

In iOS 13, apple have added a new entitlement that is needed if you wish to access the notes for contacts. The entitlement is com.apple.developer.contacts.notes. You can request permission to use this entitlement for an app being put in the App Store.

The reason it was added is primarily for privacy reasons — the notes field can contain any information you might have on the contact; and a lot of times this information is significantly more sensitive than just the contact information.

 

Happy Coding.

Still Confused With SMTP, IMAP, POP Ports?

Configuring SMTP, IMAP and POP ports can be confusing. Users and sometimes even system administrators aren’t sure when to use port 25, 587, or 465.

This article will clarify all ports related to the mail server.

SMTP 25
SMTP-SSL/TLS 587,465
IMAP 143
IMAP-SSL/TLS 993
POP3 110
POP3-SSL/TLS 995

IMAP uses port 143, but SSL/TLS encrypted IMAP uses port 993.

POP uses port 110, but SSL/TLS encrypted POP uses port 995.

SMTP uses port 25, but SSL/TLS encrypted SMTP uses port 465.

587 vs. 465
These port assignments are specified by the Internet Assigned Numbers Authority (IANA):

Port 587: [SMTP] Message submission (SMTP-MSA), a service that accepts submission of email from email clients (MUAs). Described in RFC 6409.
Port 465: URL Rendezvous Directory for SSM (entirely unrelated to email)
Historically, port 465 was initially planned for the SMTPS encryption and authentication “wrapper” over SMTP, but it was quickly deprecated (within months, and over 15 years ago) in favor of STARTTLS over SMTP (RFC 3207). Despite that fact, there are probably many servers that support the deprecated protocol wrapper, primarily to support older clients that implemented SMTPS. Unless you need to support such older clients, SMTPS and its use on port 465 should remain nothing more than a historical footnote.

Howto list all instances in all regions from mutliple accounts using awscli – AWS

AWS Cloud spans 69 Availability Zones within 22 geographic regions around the world, with announced plans for 9 more Availability Zones and three more Regions in Cape Town, Jakarta, and Milan.

If you are using more than one region it takes much time to browse through all regions in a browser and check which instances are running.

To save time, we are using awscli command in a shell script which will list all instances from all regions. You can use multiple profile names.

scrot

 

You can specify multiple profile names as follows:

This will run jobs in parallel and exit when all jobs are completed.

Locking your bash script against parallel execution

Sometimes there’s a need to ensure only one copy of a script runs, i.e prevent two or more copies running simultaneously. Imagine an important cronjob doing something very important, which will fail or corrupt data if two copies of the called program were to run at the same time. To prevent this, a form of MUTEX (mutual exclusion) lock is needed.

The basic procedure is simple: The script checks if a specific condition (locking) is present at startup, if yes, it’s locked – the script doesn’t start.

This article describes locking with common UNIX® tools.

Method 1

setting the noclobber shell option (set -C). This will cause redirection to fail, if the file the redirection points to already exists (using diverse open() methods). Need to write a code example here.

 

Method 2

A simple way to get that is to create a lock directory – with the mkdir command. It will:

create a given directory only if it does not exist, and set a successful exit code
it will set an unsuccessful exit code if an error occurs – for example, if the directory specified already exists
With mkdir it seems, we have our two steps in one simple operation. A (very!) simple locking code might look like this:

In case mkdir reports an error, the script will exit at this point – the MUTEX did its job!

Howto reverse proxy in nginx

Proxying is typically used to distribute the load among several servers, seamlessly show content from different websites, or pass requests for processing to application servers over protocols other than HTTP.

When NGINX proxies a request, it sends the request to a specified proxied server, fetches the response, and sends it back to the client. It is possible to proxy requests to an HTTP server (another NGINX server or any other server) or a non-HTTP server (which can run an application developed with a specific framework, such as PHP or Python) using a specified protocol.

1. To pass a request to an HTTP proxied server, the proxy_pass directive is specified inside a location. For example:

 2. This address can be specified as a domain name or an IP address. The address may also include a port:

3. To pass a request to a non-HTTP proxied server, the appropriate **_pass directive should be used:

  • fastcgi_pass passes a request to a FastCGI server
  • uwsgi_pass passes a request to a uwsgi server
  • scgi_pass passes a request to an SCGI server
  • memcached_pass passes a request to a memcached server

4. Passing Request Headers

 

5. To disable buffering in a specific location, place the proxy_buffering directive in the location with the off parameter, as follows:

 

 

Openvas installation in CentOS 7

What is Openvas?

OpenVAS (Open Vulnerability Assessment System, originally known as GNessUs) is a software framework of several services and tools offering vulnerability scanning and vulnerability management.

All OpenVAS products are free software, and most components are licensed under the GNU General Public License (GPL). Plugins for OpenVAS are written in the Nessus Attack Scripting Language, NASL.

The primary reason to use this scan type is to perform comprehensive security testing of an IP address. It will initially perform a port scan of an IP address to find open services. Once listening services are discovered they are then tested for known vulnerabilities and misconfiguration using a large database (more than 53000 NVT checks). The results are then compiled into a report with detailed information regarding each vulnerability and notable issues discovered.

Once you receive the results of the tests, you will need to check each finding for relevance and possibly false positives. Any confirmed vulnerabilities should be re-mediated to ensure your systems are not at risk.

Vulnerability scans performed from externally hosted servers give you the same perspective as an attacker. This has the advantage of understanding exactly what is exposed on external-facing services.

Step 1: Disable SELinux

sed -i 's/=enforcing/=disabled/' /etc/selinux/config

and reboot the machine.

Step 2:  Install dependencies

yum -y install wget rsync curl net-tools

Step 3: Install OpenVAS repository

install the official repository so that OpenVAS works appropriately in the analysis of vulnerabilities.

wget -q -O - http://www.atomicorp.com/installers/atomic |sh

Step 4: Install OpenVAS

yum -y install openvas

Step 5: Run OpenVAS

Once OpenVAS is installed, we continue to start it by executing the following command:

openvas-setup

Once downloaded it will be necessary to configure the GSAD IP address, Greenbone Security Assistant, which is a web interface to manage system scans.

Step 6: Configure OpenVAS Connectivity

We go to our browser and enter the IP address of the CentOS 7 server where we have installed OpenVAS, and we will see that the following message is displayed:

Openvas dashboard

 

Automatic NVT Updates With Cron

35 1 * * * /usr/sbin/greenbone-nvt-sync > /dev/null
5 0 * * * /usr/sbin/greenbone-scapdata-sync > /dev/null
5 1 * * * /usr/sbin/greenbone-certdata-sync > /dev/null

 

Python Matplotlib Library with Examples

What Is Python Matplotlib?

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.

Pyplot is a Matplotlib module which provides a MATLAB-like interface. Matplotlib is designed to be as usable as MATLAB, with the ability to use Python and the advantage of being free and open-source. matplotlib.pyplot is a plotting library used for 2D graphics in the python programming language. It can be used in python scripts, shell, web application servers, and other graphical user interface toolkits.

There are several toolkits that are available that extend python Matplotlib functionality.

  • Basemap: It is a map plotting toolkit with various map projections, coastlines, and political boundaries.
  • Cartopy: It is a mapping library featuring object-oriented map projection definitions, and arbitrary point, line, polygon and image transformation capabilities.
  • Excel tools: Matplotlib provides utilities for exchanging data with Microsoft Excel.
    Mplot3d: It is used for 3-D plots.
  • Natgrid: It is an interface to the “natgrid” library for irregular gridding of the spaced data.
  • GTK tools: mpl_toolkits.gtktools provides some utilities for working with GTK. This toolkit ships with matplotlib, but requires pygtk.
  • Qt interface
  • Mplot3d: The mplot3d toolkit adds simple 3D plotting capabilities to matplotlib by supplying an axes object that can create a 2D projection of a 3D scene.
  • matplotlib2tikz: export to Pgfplots for smooth integration into LaTeX documents.

Types of Plots
There are various plots which can be created using python Matplotlib. Some of them are listed below:

  • Bar Graph
  • Histogram
  • Scatter Plot
  • Line Plot
  • 3D plot
  • Area Plot
  • Pie Plot
  • Image Plot

We will demonstrate some of them in detail.

But before that, let me show you elementary codes in python matplotlib in order to generate a simple graph.

So, with three lines of code, you can generate a basic graph using python matplotlib.

Let us see how can we add title, labels to our graph created by python matplotlib library to bring in more meaning to it. Consider the below example:

You can even try many styling techniques to create a better graph by changing the width or color of a particular line or what if you want to have some grid lines, there you need styling!

The style package adds support for easy-to-switch plotting “styles” with the same parameters as a matplotlibrc file.

There are a number of pre-defined styles provided by matplotlib. For example, there’s a pre-defined style called “ggplot”, which emulates the aesthetics of ggplot (a popular plotting package for R). To use this style, just add:

To list all available styles, use:

So, let me show you how to add style to a graph using python matplotlib. First, you need to import the style package from python matplotlib library and then use styling functions as shown in below code:

Now, we will understand the different kinds of plots. Let’s start with the bar graph!

Matplotlib: Bar Graph
A bar graph uses bars to compare data among different categories. It is well suited when you want to measure the changes over a period of time. It can be plotted vertically or horizontally. Also, the vital thing to keep in mind is that longer the bar, the greater is the value. Now, let us practically implement it using python matplotlib.

When I run this code, it generates a figure like below:


In the above plot, I have displayed a comparison between the distance covered by two cars BMW and Audi over a period of 5 days. Next, let us move on to another kind of plot using python matplotlib – Histogram

Matplotlib – Histogram
Let me first tell you the difference between a bar graph and a histogram. Histograms are used to show a graphical representation of the distribution of numerical data whereas a bar chart is used to compare different entities.

It is an estimate of the probability distribution of a continuous variable (quantitative variable) and was first introduced by Karl Pearson. It is a kind of bar graph.

To construct a histogram, the first step is to “bin” the range of values — that is, divide the entire range of values into a series of intervals — and then count how many values fall into each interval. The bins are usually specified as consecutive, non-overlapping intervals of a variable. The bins (intervals) must be adjacent and are often (but are not required to be) of equal size.

Basically, histograms are used to represent data given in the form of some groups or we can say when you have arrays or a very long list. X-axis is about bin ranges where Y-axis talks about frequency. So, if you want to represent the age-wise population in form of the graph then histogram suits well as it tells you how many exist in certain group range or bin if you talk in the context of histograms.

In the below code, I have created the bins in the interval of 10 which means the first bin contains elements from 0 to 9, then 10 to 19 and so on.

When I run this code, it generates a figure like below:

As you can see in the above plot, Y-axis tells about the age groups that appear with respect to the bins. Our biggest age group is between 40 and 50.

Matplotlib: Scatter Plot
A scatter plot is a type of plot that shows the data as a collection of points. The position of a point depends on its two-dimensional value, where each value is a position on either the horizontal or vertical dimension. Usually, we need scatter plots in order to compare variables, for example, how much one variable is affected by another variable to build a relation out of it.
Consider the below example:

As you can see in the above graph, I have plotted two scatter plots based on the inputs specified in the above code. The data is displayed as a collection of points having ‘high-income low salary’ and ‘low-income high salary.’

Scatter plot with groups
Data can be classified into several groups. The code below demonstrates:

The purpose of using “plt.figure()” is to create a figure object. It’s a Top-level container for all plot elements.

The whole figure is regarded as the figure object. It is necessary to explicitly use “plt.figure()”when we want to tweak the size of the figure and when we want to add multiple Axes objects in a single figure.

fig.add_subplot() is used to control the default spacing of the subplots.
For example, “111” means “1×1 grid, first subplot” and “234” means “2×3 grid, 4th subplot”.

You can easily understand by the following picture:

Next, let us understand the area plot or you can also say Stack plot using python matplotlib.

Matplotlib: Area Plot
Area plots are pretty much similar to the line plot. They are also known as stack plots. These plots can be used to display the evolution of the value of several groups on the same graphic. The values of each group are displayed on top of each other. It allows checking on the same figure the evolution of both the total of a numeric variable and the importance of each group.

A line chart forms the basis of an area plot, where the region between the axis and the line is represented by colors.

The above-represented graph shows how an area plot can be plotted for the present scenario. Each shaded area in the graph shows a particular bike with the frequency variations denoting the distance covered by the bike on different days. Next, let us move to our last yet most frequently used plot – Pie chart.

Matplotlib: Pie Chart
In a pie plot, statistical data can be represented in a circular graph where the circle is divided into portions i.e. slices of pie that denote a particular data, that is, each portion is proportional to different values in the data. This sort of plot can be mainly used in mass media and business.

In the above-represented pie plot, the bikes scenario is illustrated, and I have divided the circle into 4 sectors, each slice represents a particular bike and the percentage of distance traveled by it. Now, if you have noticed these slices adds up to 24 hrs, but the calculation of pie slices is done automatically for you. In this way, the pie charts are really useful as you don’t have to be the one who calculates the percentage of the slice of the pie.

Matplotlib: 3D Plot
Plotting of data along x, y, and z axes to enhance the display of data represents the 3-dimensional plotting. 3D plotting is an advanced plotting technique that gives us a better view of the data representation along the three axes of the graph.

Line Plot 3D

In the above-represented 3D graph, a line graph is illustrated in a 3-dimensional manner. We make use of a special library to plot 3D graphs which are given in the following syntax.
Syntax for plotting 3D graphs:

The import Axes3D is mainly used to create an axis by making use of the projection=3d keyword. This enables a 3-dimensional view of any data that can be written along with the above-mentioned code.

Surface Plot 3D

By default, it will be colored in shades of a solid color, but it also supports color mapping by supplying the cmap argument.

The rstride and cstride kwargs set the stride used to sample the input data to generate the graph. If 1k by 1k arrays are passed in, the default values for the strides will result in a 100×100 grid being plotted. Defaults to 10. Raises a ValueError if both stride and count kwargs (see next section) are provided.

Matplotlib: Image Plot

Matplotlib: Working With Multiple Plots
I have discussed multiple types of plots in python matplotlib such as bar plot, scatter plot, pie plot, area plot, etc. Now, let me show you how to handle multiple plots.

How to create letsencrypt wildcard certificates

What’s Certbot?

Certbot is a free, open-source software tool for automatically using Let’s Encrypt certificates on manually-administrated websites to enable HTTPS.

Wildcard certificates

Let’s Encrypt supports wildcard certificate via ACMEv2 using the DNS-01 challenge.

It is necessary to add a TXT record specified by Certbot to the DNS server.

Caution: As it is necessary to update Let’s Encrypt’s certificate every 90 days, a new TXT record is required at every renewal.

 

Step 1: Run command

 

Step 2: Update DNS TXT record

 

After a successful verification