How to fix TypeError: a bytes-like object is required not ‘str’ in Python

A TypeError exception is raised when a function is called on an inappropriate type of object. In this particular error, the function expected a byte-like object, but instead, a string object was provided to it. To understand how to solve this error, we have to first understand the difference between a byte string and a string. Python supports bytes and str objects. Byte objects are a sequence of binary characters. For example, ‘\xce\xb1\xce\xac’. These are not human-readable. However, these can be stored directly in the memory. However, string objects(eg- ‘αά’) are human-readable but cannot be stored directly in the memory. We can convert an … Read more

How to check if a file exists in Python without exceptions?

File operations are frequently used in the programs. If we try to open a file whose path doesn’t exist, an error is thrown and the program halts. To avoid this, we can first check if the file exists in the given path and then open the file. In today’s article, let’s discuss different ways to check if a file exists in Python without using the try-except/finally blocks.  We will be using methods from the pathlib module and os modules. Method 1: Using pathlib.Path object Python has an in-built module named pathlib that can be used to check for any file … Read more

How to print the full NumPy array without any truncation in the output?

NumPy module in Python is extensively used while working with arrays. When you are working on large arrays, if you try to print the elements of the array, you see that the output is being truncated. For example, consider the following code snippet: import numpy as np arr=np.arange(1001) print(arr)   Output : [ 0 1 2 … 998 999 1000]   As you can see from the output, the elements after the 3rd element are being truncated and the last few elements are being shown. This happens when the elements in the array exceed 1000 elements. While this might not … Read more

[SOLVED] pip install fails with connection error: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:598)

Python is a programming language known for its ease. It has a large collection of libraries. The users can make use of these libraries to perform the task instead of developing things from the scratch. Python has some standard libraries which are installed by default when you install Python on your system. If you need to use some other libraries that are developed by the Python community, they are available in the PyPI repo. Installing from PyPI is like downloading software from an unofficial source. There is a risk involved.  Thus many companies do not allow their employees to access … Read more

How to Fix ImportError: No module named requests

Python comes with a standard set of modules that can be used by the users directly by importing them into the program. If you want to use the external modules, they are available in the PyPI repository. To use an external module from the PyPI repository, we have to first install that moudle on our system. To install the module on your system, we can make use of the package managing tools like pip, easy-install, etc. The Import Error: No module named requests signifies that Python is not able to find the module named requests. This can happen in the … Read more

4 Different ways to loop over Python Dictionaries

Python Dictionaries are used extensively in real-time. If you’re using dictionaries in your program, you should definitely know how to iterate over the dictionary. Although this is simple, there is a lot of confusion in the community. This is because many dictionary functions have changed from Python 2 to Python 3.     In this article, let’s check the different methods used to loop over a dictionary in Python. Note: All the methods described below work for Python versions 3+.   Method 1: Using the dictionary directly Python Dictionaries can be iterated directly. However, it is important to note that, … Read more

How to read inputs as numbers in Python?

In Python, one can use the input() method to receive the user input. For example, if you want the user to enter two values x, y, and then find the sum of those values, you can do it as follows : x=input(“Enter the value of x: “) y=input(“Enter the value of y: “) print(“x+y is: “,x+y) Output : Enter the value of x: 5 Enter the value of y: 6 x+y is 56 The sum of two numbers 5 and 6 should be 11. However, the output is 56. If you’re wondering why? Then it is because the input() function … Read more

How to fix TypeError: list indices must be integers or slices, not tuple?

You see TypeError: list indices must be integers or slices, not tuple when you try to index the list with a tuple. Generally, the list indices are expected to be integers or slices(specified with the colon operator). This error shows up if: You’re using a comma instead of a colon for slicing. You miss a comma while defining a list. You index a nested list with a comma. Let’s discuss the causes and fixes for this error in detail with examples. Also, check TypeError: only integer scalar arrays can be converted to a scalar index Fixes for TypeError: list indices … Read more

[FIX] TypeError: only integer scalar arrays can be converted to a scalar index

You see the TypeError: only integer scalar arrays can be converted to a scalar index in Python when you’re working with numpy for one of the following reasons. If you’re trying to index a list with a numpy array instead of a numpy array element.  When a numpy method is expecting dimension, and you provide the array instead. While using numpy.concatenate(), you pass arrays instead of tuples or lists. Now, let’s try to understand the causes with detailed examples. Also check, How to fix IndexError: arrays used as indices must be of integer (or boolean) type.   What causes the … Read more

How to create a pandas series from multiple numpy arrays?

Let’s say you have two numpy arrays as shown below: a=np.array([1,2,3,4,5]) b=np.array([6,7,8,9,10]) Problem : You want a create a pandas series from multiple numpy arrays as shown below. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10   Solution: Join the contents of the array and then add it as a Series 1. First, let’s join the arrays using any of these methods- np.concatenate(), np.join() ,np.hstack, np.append()   2. Once that is done, simply convert this array to pandas Series. import numpy as np import pandas as pd … Read more