Introduction
Python, considerably comparable ot Node, makes use of a system of put in modules/packages. However as you proceed to put in increasingly modules, it’d get a bit difficult to maintain monitor of all of them. On this Byte, we’ll discover learn how to get a listing of all regionally put in Python modules, which may be very useful in managing your Python setting.
Python Modules
A Python module is mainly only a file (or listing of information) containing Python definitions and statements. These modules can outline capabilities, lessons, and variables that may be utilized in different Python code. It is like a toolkit full of varied instruments, every designed for a selected activity. Python comes with a typical library of modules, however the fantastic thing about Python really lies within the huge array of third occasion modules which can be accessible. These may be put in regionally and used as wanted.
As an illustration, in case you’re engaged on an internet scraping mission, you would possibly set up the BeautifulSoup module. Or, in case you’re coping with information evaluation, the pandas module is well-liked for a lot of data-related duties.
How you can Record Put in Python Modules
Python supplies a number of other ways to record all of the modules put in in your native setting. The commonest methodology is utilizing the pip command, which is the usual bundle supervisor for Python.
Utilizing pip record
The pip record command is a fast method to see all of the Python modules put in in your present setting. Open up your terminal or command line interface and kind within the following command:
$ pip record
This may offer you a listing of all put in packages, together with their respective variations.
Package deal Model
--------------- -------
beautifulsoup4 4.9.3
numpy 1.19.5
pandas 1.1.5
pip 21.0.1
setuptools 54.1.2
Notice: Keep in mind that the record of modules you see can be particular to your present Python setting. For those who’re utilizing a digital setting, solely the modules put in in that setting can be proven.
That is it for the pip record command. It is a fairly easy method to get a fast overview of your put in Python modules. Within the subsequent part of this Byte, we’ll see one other helpful command, pip freeze, and see the way it differs from pip record.
Utilizing pip freeze
pip freeze is one other command that you should utilize to record all put in Python modules. However not like pip record, pip freeze returns the record of modules in a format that pip can eat. This implies every line of the output is a legitimate argument for pip set up.
Let’s run pip freeze within the command line and see what it provides us:
$ pip freeze
This may return one thing like:
asn1crypto==0.24.0
certifi==2018.1.18
cffi==1.11.5
chardet==3.0.4
cryptography==2.1.4
idna==2.6
pycparser==2.18
PySocks==1.6.8
requests==2.18.4
six==1.11.0
urllib3==1.22
Every line within the output is a module together with its put in model. That is tremendous useful when it’s worthwhile to replicate your setting elsewhere or create your necessities.txt file.
Variations Between pip record and pip freeze
Now that you have seen each pip record and pip freeze in motion, you is likely to be questioning what the distinction is, aside from some easy formatting.
And the principle distinction between the 2 instructions actually is simply the formatting of their output. pip record outputs a barely extra human-readable format of put in packages, which is nice whenever you’re shortly checking what’s put in. However, pip freeze outputs a listing of packages in a format that pip can use in different instructions. That is significantly helpful whenever you wish to replicate your setting, as you possibly can merely redirect the output of pip freeze to a necessities file, then use pip set up -r necessities.txt on one other machine to put in the identical packages.
Notice: Each pip record and pip freeze will record all put in packages, no matter the place they had been put in from. This contains packages put in by way of pip, setup.py, and different bundle managers.
Itemizing Modules in a Digital Surroundings
Working in a digital setting might help you handle dependencies for various Python initiatives and maintain them separate. Whenever you activate a digital setting, pip record and pip freeze will solely present the packages put in in that setting.
For example, let’s create a brand new digital setting and set up a bundle:
$ python3 -m venv myenv
$ supply myenv/bin/activate
(myenv) $ pip set up requests
Now, if we run pip record or pip freeze, solely the requests bundle and its dependencies can be listed:
(myenv) $ pip record
Package deal Model
---------- -------
certifi 2021.5.30
chardet 4.0.0
idna 2.10
requests 2.25.1
urllib3 1.26.6
Conclusion
To sum up, Python supplies a number of methods to record all put in modules, whether or not you are working in a world or digital setting. pip record and pip freeze are two instructions that not solely record the put in packages but additionally present more information, particularly the model of the packages. Keep in mind that the record of put in packages can range relying in your energetic setting, so all the time double-check which setting you are in earlier than putting in or itemizing packages.
