#100DaysOfCode in Python Transcripts
Chapter: Days 82-84: Data visualization with Plotly
Lecture: Installing feedparser and plotly
0:00 As usual, I have a Jupyter notebook
0:03 prepared for this lesson and first,
0:05 let's actually head over to the terminal
0:08 to install the external modules we're going to use.
0:13 I'm going to create a directory.
0:16 cd into it. I was explaining before I use
0:20 a virtual venv with my Python path
0:23 set to my Anaconda installation.
0:25 I'm using Anaconda because it comes
0:27 with all the data science libraries
0:28 and Jupyter notebook and all that.
0:30 If you're not using Anaconda, you can make
0:33 a virtual environment just by using the standard
0:36 module in Python, like this but I'm using this
0:40 to make it all work with my environment.
0:45 Right. Then I need to enable it.
0:47 I have an as for that as well
0:48 because I'm using virtual environments for anything
0:51 because I always want to isolate my dependencies.
0:54 So, now I'm in the virtual environment
0:57 and you see a nice indication in my prompt.
1:02 As expected there's nothing installed
1:04 and it's exactly what we want because we want
1:05 to have all of our stuff in this namespace.
1:09 I'm going to pip install feedparser
1:12 serve to parse our blog feed
1:14 and plotly to do the graphical work.
1:21 That's all now in our virtual environment,
1:23 so, we can get started.
1:26 So, I'm heading back to my notebook
1:27 and let's import the modules we're going to use.
1:34 Right, by the way, one thing I have
1:36 the virtual environment here enabled
1:38 that's probably not what happens by default for you.
1:42 So, what I did to get the virtual environment
1:46 inside my notebook, was to pip install ipykernel
1:48 so then you run this self install script
1:53 and the name should be your virtual environment.
1:55 So, in my case, that's venv and after we started
1:59 the notebook then I have an option here
2:01 to select my virtual environment.
2:03 So, I put the link here in notebook
2:05 if you want to work from a similar set up
2:07 as I have, you should go through this link.
2:10 That's it for set up, in the next video,
2:12 we're going to use feeds bars
2:14 to pull data from our PyBites blog.