In this video, learn how to download and install Anaconda, as well as any extra packages you may need.
- For this course, we need an updated installation of Python, and a few third party packages, including ipython, the jupyter notebook, and a few more. If you already use Python, and you know how to install extra packages, you are free to do so. Otherwise, I suggest you follow me and install the free Anaconda Python distribution. This distribution includes everything that we need. So we go to the continuum.io website, we found the download, scroll down to a platform of choice, select the graphical installer, for the Python 3 version of Anaconda.
Throughout this course, we're going to be using Python version 3. In this case, 3.5. Although Python 2 is still a useful tool, and is still supported by the Python Software Foundation, there is no reason not to use the newer version now, which fixes several problems with the older Pythons, and introduces several new useful features. We don't need to register. We continue in .io. Once the download has completed, we go find a file, double click on it to install, and go through a standard installation.
This will require several clicks. We can install only for our user, or for everybody. The installation will take a few minutes. All done. When the installation is finished, we can open a terminal, type Python. This will start the Anaconda version of Python 3. We're in the standup Python shell, where we can write and execute code interactively. It's traditional to say hello. The packages that we need for this course are numpy, matplotlib, ipython, jupyter notebook, requests, beautiful soup, shortened to bs4, pillow, flask, basemap, geopy, line_profiler, and memory_profiler.
Of these, only the last four are not already included in the Anaconda distribution. So we're going to install them manually, from the shell. We do this using the conda installation tool for basemap, with y to proceed. You see that conda installs the package that we requested, and also a few dependencies. And we're going to use a slightly different tool, pip, to install line profiler, memory profiler, an geopy. Ready to go. In the Python shell, we can check that these packages are imported correctly.
For instance, geopy. No news is good news here. We are now ready to start experimenting with Python.
- Designing efficient loops
- Exploiting Python collections
- Writing Pythonic code
- Choosing the best libraries for your tasks
- Downloading webpages with requests
- Parsing HTML with Beautiful Soup
- Manipulating images with Pillow
- Making videos and drawing on maps with matplotlib
- Serving webpages with Jinja2 and Flask
- Working with Python classes
- Taking advantage of functional techniques
- Profiling CPU and memory use
- Exploiting parallelism