As an Anaconda user for a long time
I started practising data science more than 2.5 years and was using Anaconda since then. Whoever is doing data science must be well aware of Anaconda. Anaconda is not just about one software, it is a package of many data with related software in it. Hence it is more in use with many built-in modules and packages.
How much was it useful?
How well did it work?
Anaconda installation was simple for individuals and there is also miniconda which is a lighter version of the Anaconda. Coming to the installation of Anaconda go to anaconda.org/download anaconda for Windows/Linus/Mac. Don’t forget to add PATH to system variables. After installation, you will be able to open the Anaconda navigator from Windows. Install jupyter notebook or jupyter lab or any other required software like R studio, Spyder..etc. Now you will be able to open jupyter notebook from windows, there will be already available packages and default base kernel in it. If you want to add some more packages it can be added otherwise you can even create new conda environments. To list down available conda environments use the command: conda info — envs or conda env list.
Pros :
- It was easy working with many installed data science python packages present in it.
- There is no other user-friendly software containing all the relevant packages.
- Constant development in the UI
- All the data scientists are aware of this popular software.
Cons:
- After some days you see the trouble while working with high-level coding.
- There are many times when the DLL errors occur saying it is not compatible with your anaconda, python, or other packages you previously installed.
- When multiple versions of python are present you might face challenges then delete them and even reinstall Anaconda. Repeat the process many times.
- The Enterprise version is not free
- Dependent modules may not work as the required version is not installed.
What's happening?
There are many bugs from time to time. It is becoming difficult to continue working with Anaconda. Even simple codes or packages which worked well were not working. So it's a clear sign that I need to look for alternate software or a place I can easily work for my data science projects. So my main requirements were python and a jupyter notebook. So, I have tried installing only them instead of anything else. Guess what, Splendid!! It did work.
Installation of python, jupyter notebook and working with it:
- Install any python version from the python website
- You are halfway done. Just you need to install jupyter from the command line to make python work from the jupyter notebook
- Now open the command line
- Type “python” or “python -V” to know if python is installed properly on your device and can know the version that is installed.
- Activate the base environment. (same as mentioned below)
- Just install jupyter from the same path you want to open the python notebook ‘pip install jupyter’
- Next, just type ‘jupyter notebook’ and if doesn’t open the notebook. Try with ‘python -m notebook’. For me, the second one works.
- If you want to create a virtual environment and work on it. Follow the below steps.
- To create a virtual environment on a specific path ‘python -m .venv <%PATH%>’
- Now change to that directory(‘cd .venv’) and you will find the files which are required to activate the environment. They are bin, include, lib, pyvenv.cfg
- To know the available files in that folder just type ‘dir’ in the command line or ‘ls’ in powershell.
- To activate the virtual environment, type -> ‘.\Scripts\activate’.
- Now pip install jupyter
- Open jupyter notebook and before that, you can do ‘python -m pip freeze’ to import the libraries to the virtual environment which are present in the pip list.
- If you want to create a new kernel from this environment. Just ‘pip install ipykernel’ and ‘python -m ipykernel install — user — name myenv — display-name “Python (myenv)”’.
- You can create as many environments and kernels as you want using the same commands just by changing the names of it. Amazing!!!
Great things have a small start
Go do some amazing things and reinvent life
If you have learnt an amazing way of working with jupyter without an enormous task just let me know by showing some support and sharing it with someone useful. If you have any queries or anything do let me know in the comment box and do follow for some of the amazing stories. Bring some light to the world. Have a nice day. 🥰🕊🤍