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How to Install pip on Windows

How to Install pip on Windows
Awais Khan
Technical writer
Python Windows
15.01.2025
Reading time: 6 min

pip is a utility that turns Python package installation and management into a straightforward task. From Python beginners to coding wizards, having this utility on your Windows computer is a true game-changer. It effortlessly facilitates the setup of crucial frameworks and libraries for your development needs. Automating package management with pip frees up your time and reduces the complications linked to manual installations.

Follow this guide to become proficient in configuring pip and overseeing your Python packages seamlessly.

pip Setup Process for Windows

Here are the guidelines to set up pip on a Windows machine.

Step 1: Confirm Installation

Verify Python is operational on your device before starting the pip setup. To carry out this operation, run command prompt and apply:

python --version

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If Python's not present on your system, download it from the official site.

Step 2: Download get-pip.py

Python's standard installation package automatically includes pip. However, in case of accidental removal, grab the get-pip.py script. 

You have a couple of options: either visit the pip.py webpage, or use the curl command for a quick install:

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py

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Note: Installing Python again to get pip is also an option. However, it can sometimes lead to conflicts with other dependencies or settings. Your existing Python setup stays unchanged with this script.

Step 3: Run get-pip.py

Move to the script’s location through the command prompt and apply:

python get-pip.py

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This will smoothly install pip on your device.

Step 4: Confirm pip Installation

Validate the installation by executing:

pip --version

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Applying this command ensures pip is installed on the system.

Step 5: Add pip to System PATH

If the command doesn't execute properly, update your system PATH with these instructions to incorporate pip:

  • Access Properties by right-clicking on My Computer or This PC from the drop-down menu.

  • Opt for Advanced system settings.

  • Select Environment Variables.

  • Head over to System Variables, spot the Path variable, and choose Edit.

  • Insert the Python Scripts directory into your system PATH, for example, C:\Python39\Scripts.

Alternative Ways for pip Installation on Windows

Let's discuss a few other ways to effortlessly get pip running on Windows.

Via Built-in ensurepip Module

From Python 3.4 onward, there's an awesome built-in module named ensurepip. With this tool, pip installation is simplified, eliminating the need for the get-pip.py script.

Step 1: Run ensurepip

Input the command below to set up pip:

python -m ensurepip --default-pip

Step 2: Verify pip Installation

Check pip version through:

pip --version

Python Installer Approach for pip Installation

Ensure the pip checkbox is marked during the Python setup. Here's how:

Step 1: Download Installer

Fire up your favorite browser, go to the official Python website, and acquire the most recent installation file.

Step 2: Launch the Installer

Launch the installer you've downloaded and remember to pick the Add Python to PATH option while setting up.

Step 3: Install pip

While progressing through the setup, don't forget to enable the Install pip option.

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Step 4: Validate pip is Installed

When the setup wraps up, check pip installation via:

pip --version

Adjusting pip Version: Upgrade or Downgrade

pip can be adjusted to suit your requirements by upgrading or downgrading. Here's how:

Upgrading pip

To give pip a fresh upgrade, execute:

python -m pip install --upgrade pip

Downgrading pip

To roll back pip, apply:

python -m pip install pip==<version>

Enter the desired version number to install instead of <version> (e.g., 21.0).

Resolving pip Installation Issues: Essential Commands

Let's discover common pip installation issues and their fixes:

Issue 1: "pip" is not recognized as an internal or external command

Solution: This implies the pip path isn't set in your system PATH. Simply follow the instructions in "Step 5" to fix this.

Issue 2: Permission Denied

Solution: Elevate your command prompt privileges by right-clicking the Command Prompt icon and choosing Run as administrator. Afterward, rerun the commands.

Issue 3: Missing Dependencies

Solution: Sometimes, you'll run into trouble because of missing dependencies. To correct this, manually install the essential dependencies with pip. For example:

pip install package_name

Swap out package_name for the appropriate dependency.

Utilizing Virtual Environments

Employing virtual environments keeps dependencies distinct and avoids any conflicts. Here's how to utilize a virtual environment with pip:

Creating a Virtual Environment

python -m venv env_name

Replace env_name with your desired environment name.

Initiating Your Virtual Environment

env_name\Scripts\activate

Standard pip Commands

To explore pip's usage, check these essential commands:

Installing a Package

pip install package_name

Modify package_name to accurately reflect the package you're aiming to install.

Uninstalling a Package

pip uninstall package_name

Showing Installed Packages

pip list

Showing Package Information

pip show package_name

Optimal Strategies for Package Management

  • Employ virtual environments to handle dependencies efficiently in multiple projects.

  • Regularly inspect and upgrade your packages to keep everything running smoothly.

  • Prepare requirements files to ease the management of dependencies in your projects.

Securing pip Installation

Ensuring the protection of packages handled by pip is critical. Here are some tips to keep your environment secure:

  • Maintain project isolation to avoid conflicts and secure installations.

  • Check the trustworthiness and verification of package sources before installing. Always refer to official repositories and examine reviews if they are available.

  • Consistently update pip and your packages to stay protected with the latest security patches and improvements.

  • Periodically review your dependencies for known vulnerabilities. Tools such as pip-audit can assist in identifying and resolving security concerns.

  • Adhere to secure coding standards and steer clear of deprecated or insecure packages.

Integrating pip with IDEs

pip can be effortlessly embedded into various Integrated Development Environments (IDEs), significantly boosting your development efficiency:

  • VS Code: Utilize the built-in terminal for direct pip command and package management within the editor.

  • PyCharm: Streamline package management by setting up pip configurations via the project interpreter. This simplifies the process of installing and managing packages customized to your project's specific needs.

  • Jupyter Notebook: Employ magic commands in the notebook interface for direct package installation. This provides a smooth and integrated experience for managing dependencies while you work on your interactive notebooks. 

Conclusion

Windows offers several methods to set up pip, catering to different preferences and requirements. No matter if you select the .py script, use Python's built-in ensurepip module, or enable pip during the initial setup, these approaches will make sure pip is properly configured on your system. This all-in-one guide empowers you to handle and install Python packages with ease.

Don't forget, keeping pip updated is essential for ensuring the security and efficiency of your Python setup. Routinely check for updates and keep pip upgraded.

In addition, on our application platform you can find Python apps, such as Celery, Django, FastAPI and Flask.

Python Windows
15.01.2025
Reading time: 6 min

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Python Static Method

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Python Static Method vs Class Method Though they look similar, class and static methods in Python have different uses; so, let's now quickly review their differences. Defined inside a class, a class method is connected to that class rather than an instance. Conventionally called cls, the class itself is the first parameter; so, it can access and change class-level data. Factory patterns, alternate constructors, or any activity applicable to the class as a whole and not individual instances are often implemented via class methods. Conversely, a static method is defined within a class but does not start with either self or cls parameters. It is just a regular function that “lives” inside a class but doesn’t interact with the class or its instances. For utility tasks that are conceptually related to the class but don’t depend on its state, static methods are perfect. Here's a quick breakdown of the Python class/static methods differences: Feature Class Method Static Method Binding Bound to the class Not bound to class or instance First parameter cls (class itself) None (no self or cls) Access to class/instance data Yes No Common use cases Factory methods, class-level behavior Utility/helper functions Decorator @classmethod @staticmethod Python Static Method vs Regular Functions You might ask: why not just define a function outside the class instead of using a static method? The answer is structure. A static method keeps related logic grouped within the class, even if it doesn't interact with the class or its instances. # Regular function def is_even(n): return n % 2 == 0 # Static method inside a class class NumberUtils: @staticmethod def is_even(n): return n % 2 == 0 Both functions do the same thing, but placing is_even inside NumberUtils helps keep utility logic organized and easier to find later. Let’s proceed to the hands-on Python static method examples. Example #1 Imagine that we have a MathUtils class that contains a static method for calculating the factorial: class MathUtils: @staticmethod def factorial(n): if n == 0: return 1 else: return n * MathUtils.factorial(n-1) Next, let's enter: print(MathUtils.factorial(5))120 We get the factorial of 5, which is 120. Here, the factorial static method does not use any attributes of the class instance, only the input argument n. And we called it using the MathUtils.factorial(n) syntax without creating an instance of the MathUtils class. In Python, static methods apply not only in classes but also in modules and packages. The @staticmethod decorator marks a function you define inside a class if it does not interact with instance-specific data. The function exists on its own; it is related to the class logically but is independent of its internal state. 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16 April 2025 · 6 min to read
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Input in Python

Python provides interactive capabilities through various tools, one of which is the input() function. Its primary purpose is to receive user input. This function makes Python programs meaningful because without user interaction, applications would have limited utility. How the Python Input Works This function operates as follows: user_name = input('Enter your name: ') user_age = int(input('How old are you? ')) First, the user is asked to enter their name, then their age. Both inputs are captured using a special operator that stores the entered values in the variables user_name and user_age. These values can then be used in the program. For example, we can create an age-based access condition for a website (by converting the age input to an integer using int()) and display a welcome message using the entered name: if user_age < 18: print('Sorry, access is restricted to adults only') else: print('Welcome to the site,', user_name, '!') So, what happens when int() receives an empty value? 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08 April 2025 · 6 min to read
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Operators in Python

Python operators are tools used to perform various actions with variables, as well as numerical and other values called operands—objects on which operations are performed. There are several types of Python operators: Arithmetic Comparison Assignment Identity Membership Logical Bitwise This article will examine each of them in detail and provide examples. Arithmetic Operators For addition, subtraction, multiplication, and division, we use the Python operators +, -, *, and / respectively: >>> 24 + 28 52 >>> 24 - 28 -4 >>> 24 * 28 672 >>> 24 / 28 0.8571428571428571 For exponentiation, ** is used: >>> 5 ** 2 25 >>> 5 ** 3 125 >>> 5 ** 4 625 For floor division (integer division without remainder), // is used: >>> 61 // 12 5 >>> 52 // 22 2 >>> 75 // 3 25 >>> 77 // 3 25 The % operator returns the remainder (modulo division): >>> 62 % 6 2 >>> 65 % 9 2 >>> 48 % 5 3 >>> 48 % 12 0 Comparison Operators Python has six comparison operators: >, <, >=, <=, ==, !=. Note that equality in Python is written as ==, because a single = is used for assignment. The != operator is used for "not equal to." When comparing values, Python will return True or False depending on whether the expressions are true or false. >>> 26 > 58 False >>> 26 < 58 True >>> 26 >= 26 True >>> 58 <= 57 False >>> 50 == 50 True >>> 50 != 50 False >>> 50 != 51 True Assignment Operators A single = is used for assigning values to variables: >>> b = 5 >>> variants = 20 Python also provides convenient shorthand operators that combine arithmetic operations with assignment: +=, -=, *=, /=, //=, %=. For example: >>> cars = 5 >>> cars += 7 >>> cars 12 This is equivalent to: >>> cars = cars + 7 >>> cars 12 The first version is more compact. Other assignment operators work similarly: >>> train = 11 >>> train -= 2 >>> train 9 >>> moto = 3 >>> moto *= 7 >>> moto 21 >>> plain = 8 >>> plain /= 4 >>> plain 2.0 Notice that in the last case, the result is a floating-point number (float), not an integer (int). Identity Operators Python has two identity operators: is and is not. The results are True or False, similar to comparison operators. >>> 55 is 55 True >>> 55 is 56 False >>> 55 is not 55 False >>> 55 is not 56 True >>> 55 is '55' False >>> '55' is "55" True In the last two examples: 55 is '55' returned False because an integer and a string were compared. '55' is "55" returned True because both operands are strings. Python does not differentiate between single and double quotes, so the identity check was successful. Membership Operators There are only two membership operators in Python: in and not in. They check whether a certain value exists within a sequence. For example: >>> wordlist = ('assistant', 'streetcar', 'fraudster', 'dancer', 'heat', 'blank', 'compass', 'commerce', 'judgment', 'approach') >>> 'house' in wordlist False >>> 'assistant' in wordlist True >>> 'assistant' and 'streetcar' in wordlist True In the last case, a logical operator (and) was used, which leads us to the next topic. Logical Operators Python has three logical operators: and, or, and not. and returns True only if all operands are true. It can process any number of values. Using an example from the previous section: >>> wordlist = ('assistant', 'streetcar', 'fraudster', 'dancer', 'heat', 'blank', 'compass', 'commerce', 'judgment', 'approach') >>> 'assistant' and 'streetcar' in wordlist True >>> 'fraudster' and 'dancer' and 'heat' and 'blank' in wordlist True >>> 'fraudster' and 'dancer' and 'heat' and 'blank' and 'house' in wordlist False Since 'house' is not in the sequence, the result is False. These operations also work with numerical values: >>> numbers = 54 > 55 and 22 > 21 >>> print(numbers) False One of the expressions is false, and and requires all conditions to be true. or works differently: it returns True if at least one operand is true. If we replace and with or in the previous example, we get: >>> numbers = 54 > 55 or 22 > 21 >>> print(numbers) True Here, 22 > 21 is true, so the overall expression evaluates to True, even though 54 > 55 is false. not reverses logical values: >>> first = True >>> second = False >>> print(not first) False >>> print(not second) True As seen in the example, not flips True to False and vice versa. Bitwise Operators Bitwise operators are used in Python to manipulate objects at the bit level. There are five of them (shift operators belong to the same type, as they differ only in shift direction): & (AND) | (OR) ^ (XOR) ~ (NOT) << and >> (shift operators) Bitwise operators are based on Boolean logic principles and work as follows: & (AND) returns 1 if both operands contain 1; otherwise, it returns 0: >>> 1 & 1 1 >>> 1 & 0 0 >>> 0 & 1 0 >>> 0 & 0 0 | (OR) returns 1 if at least one operand contains 1, otherwise 0: >>> 1 | 1 1 >>> 1 | 0 1 >>> 0 | 1 1 >>> 0 | 0 0 ^ (XOR) returns 1 if the operands are different and 0 if they are the same: >>> 1 ^ 1 0 >>> 1 ^ 0 1 >>> 0 ^ 1 1 >>> 0 ^ 0 0 ~ (NOT) inverts bits, turning positive values into negative ones with a shift of one: >>> ~5 -6 >>> ~-5 4 >>> ~7 -8 >>> ~-7 6 >>> ~9 -10 >>> ~-9 8 << and >> shift bits by a specified number of positions: >>> 1 << 1 2 >>> 1 >> 1 0 To understand shifts, let’s break down values into bits: 0 = 00 1 = 01 2 = 10 Shifting 1 left by one bit gives 2, while shifting right results in 0. What happens if we shift by two positions? >>> 1 << 2 4 >>> 1 >> 2 0 1 = 001 2 = 010 4 = 100 Shifting 1 two places to the left results in 4 (100 in binary). Shifting right always results in zero because bits are discarded. For more details, refer to our article on bitwise operators. Difference Between Operators and Functions You may have noticed that we have included no functions in this overview. The confusion between operators and functions arises because both perform similar actions—transforming objects. However: Functions are broader and can operate on strings, entire blocks of code, and more. Operators work only with individual values and variables. In Python, a function can consist of a block of operators, but operators can never contain functions.
08 April 2025 · 6 min to read

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