Using Python to Access Web Data

I have one big criticism of this class. The Python keyword "import" is never explained. The concept of "module" is never explained.

We're just told to cant this magic incantation "import re" and suddenly statements that generated traceback errors suddenly don't. Even more intriguingly, python now seems to recognize regular expressions!

Later, we're just told to cant another magic incantation "import xml.etree.ElementTree as ET" and now there are actually new data types!

How this happens is never explained.

To make this class perfect, you just need to add one -- just one -- lecture which explains what modules are and what importing them does. Take if from "just type this magic incantation," to "this is how we can add functions and data types and methods and expand python."

Python itself is a wonderfully-compact little language, just 33 keywords and just eight data types. Python itself can't interpret regular expressions, can't parse XML or JSON, can't convolve matrices of complex number. What makes Python such an amazing language is that one of the keywords is "import." With import, we can expand python to interpret regular expressions, parse XML or JSON, and convolve matrices of complex number too. You can even write a program that can convolve matrices of complex numbers that come from a web-based source in the JSON, all in one program. This is why it's so important to understand modules and libraries of modules and understand what import does. It shouldn't be taught as just some mysterious magical incantation.

Students should be taught that there are standard libraries of python modules available, that there are countless non-standard libraries and modules which are also available to "use at your own risk," that many companies and institutions have in-house libraries, and that they can even learn to create their own libraries if they want to (though the mechanics of this can be left to another class).

I really enjoyed the first two courses of Dr. Chuck's Python for Everybody Specialization -- but not this one. As some other reviewers have already stated I, too, felt increasingly frustrated and somehow left alone during this course. Most of this course's assignments were way too difficult and I had to search the web for hours to find some help to solve them. Or, quite honestly, I had to cheat my way through them, because I just didn't know what to do anymore. There are of course the discussion forums where one can state one's problem - but although the staff and mentors are really quick with replying (thumbs up for that), their tips are often way too general and not helpful at all.

After taking this third course I will definitely not continue with the Specialization, as I originally planned to, simply because in comparison to the first two courses, this third course is way too difficult and frustrating!

Also, in my opinion, Dr Chuck tries to squeeze in far too many different topics and different programming langauges into this course, instead of really just focusing on Python itself.

I completed this course, yes, but it left me with a very frustrated and unsatisfied feeling. I don't think I was really able to learn a lot from it, which is really a pity, since I enjoyed the first two courses so much.

Sorry for the bad feedback, but this is honestly how I felt about the course!

Although my specialty is zoology, I signed up and paid for this course (one in a series offered by them) to learn a little about Python which intrigued me for some reason.

The course gives a somewhat disjointed, quick overview of using Python to access web data, but Professor Severance does try to touch shallowly on a good array of the relevant subject matter.

The real sin, however, (and the entire reason I’m taking the time to post this review) is to be found in the course’s abomination of a forum, where the “teaching assistants” are aggressively unhelpful. A teaching forum is intended to be a resource for students who have hit a wall in an assignment and need a few well-placed words of guidance to get them over a hump, but there is none of that found here.

Right around week 5 of this 6 week course was an assignment that a fair number of students had trouble with (judging by the number of questions in the forum) . I read several student to teaching assistant exchanges on the forum where a student just couldn’t figure out that bit of code with the vague “guidance” they had received, and when they had the temerity to persist with their questions, were cut off at the knees by the teaching assistant, and instructed to stop asking . . Really condescending, uncalled for, and shocking, quite frankly, in an educational setting.

I would highly recommend that if you want to learn to use Python to access web data, or any of the other courses in the Python for Everybody series at the University of Michigan, you seek out some other, more professionally run courses where you can get actual assistance if you have a question. There are certainly plenty to choose from.

As I mentioned in the previous reviews about this Specialisation, all these courses are meant for beginners without previous programming experience and difficulty of courses rises gradually.

Thus, the first course was a real piece of cake, second got a little tougher and this one is the first course that really took me some time to finish it. This time I really had to listen to some lectures twice, to debug my code a hell lot of times and to stick to the sample code a lot.

Students, who have programming experience might still think that this course is too slow and easy, but it is a great way for the beginner to learn python.

The only problem that seems to appear is new coursera policy, that doesn't allow you to submit assignments before you pay for the course, e.g. you can only get access to theory unless you pay. But there is a solution - Dr Chuck has created his own website to complete these courses https://www.py4e.com//

To sum up: great course, uprising difficulties, recommend to enroll after finishing previous courses. 10/10

This third course applies and builds on the basic knowledge from the first two python courses. Especially interesting is the information on regular expressions, which kicks this course off. Following this the course gears up into a higher transmission focusing on using python with web browsers and reading webpages. Beautiful Soup gets covered as well as how to deal with XML data. So far so good.

Unfortunately the course loses itself suddenly in Java Script Object Notation and dealing with Twitter and Google Maps to the point where the amount of knowledge required does not match the content and quality of the classes.

Also ' dr. Chuck' seems more and more concerned with his self-promotion in the bonus video material that is provided each week, rather than focusing only on content. The age of the material (the course was ' shot' in 2015) also starts to show with the assignments that often lack sufficient information for students with English as a second language or jump into a level of complexity that is possible more than the basic student can understand.

With this review, you must understand, a major part of this review is because of my interest/expectations/etc., what I was looking for from the course. If you are interested in “fully engaging” in Python, becoming a computer scientist, etc., this course if fine. Me, I’m an engineer by profession. About every 5 years, I go back and take a class to keep my programming skills up. So, my interests in programming would be about 80% math implementation, 20% string/list/character manipulation. This course was all string/list/character manipulation, I felt. So, I was turned off by the course.

This course definitely isn’t a beginner Python course. You need to have had Python experience before taking this course.

Other things I will describe briefly. They are only examples.

First, I didn’t know we would get into things like XML and JSON has deeply as we did. If I wanted to learn XML or JSON, I would have taken a course on those. I was interested in learning Python, not XML and JSON.

Given that, I couldn’t understand why we were learning things in this course. I could understand much of what the programs were doing. But, “why” learn this information? Like, in one program, I felt I have done the manipulation much, much easier and faster with “copy-n-paste” and MS Excel. So, why make a Python program to do the manipulation? I couldn’t tell why.

Given that, I felt that Dr. Chuck was doing more along the lines of “forcing” this information onto us during this course. Something like, not a quote but what it seemed like, “Python can do this, so just do it. Don’t worry about learning it. Just do it.” But, then, he wants us to demonstrate our ability in the knowledge and programming at the end of the chapter?

In summary, again, if you want to get “fully engaged” in everything Python can do, aka become a computer scientist, this course will probably be good for you. But, for me, sorry, but it lacked what I look for from a programming course.

I just completed the course. It is excellent, but needs a few bug fixes.

The Week 5 Chapter assignment references the wrong exemplar (not wrong, per se, but far more complex than a simpler example covered in the lectures that transfers better to the assignment).

This threw a lot of people and protracted completion of the exercise. A plurality of people who noticed this whined. Apparently, the course shell has not been updated in 2 years.

The code snippets reference the P4E website, which is Dr. Chuck's open source version of the course. The links to the snippets should be given in the course shell, rather than requiring the student to navigate over to the P4E website, dive into the Resources area, then scan to find the snippet.

As one reviewer noticed, there are 2 questions in the Week 6 chapter quiz on REST, but no mention of REST in the lectures, and only a cursory mention of it in Chapter 13 of the text.

I also think that the GeoCoding example covered in the lecture videos needs to be broken down into steps. Perhaps it could be developed incrementally--showing the outputs generated and data structures used at each step. I ended up doing this myself, but I have significant prior knowledge.

There is also little use of functions in the course to-date. It might be good to enforce that as a precept of modular design and to inculcate good habits.

I used https://repl.it throughout the course, despite the recommendation that students invoke Python from the shell and use the platform agnostic Atom editor. Repl is a great learning tool and has a social component these days that has some of the collaboration functionality of forums like Slack. I think the course would run better this way.

Overall, this is one of the better classes on Python out there. I took an introductory Data Science oriented version of a Python course at Harvard and wish Dr. Chuck had been the instructor.

On to Course 4: Using Databases with Python...

jerald_cole @ alumni DOT harvard DOT edu

:-)

The 3 installment of the specialization deals with getting, parsing and reading data from the internet, specifically data in XML and JSON formats.

In comparison with the previous 2 chapters, this one feels quite rushed and overwhelming. Now, I completely understand that it's not possible to explain every single thing in a beginner's course, historically and functionality wise but I couldn't help feeling a bit dumb having to copy-paste some import statements in order to complete the assignments.

There's a lot more to talk about on the topic and I fully agree that the content has to be shrunk to a minimum in order to give a high-level overview of the subject but it could be of great help to the course if there were more assignments, more worked exercises, more lectures that go in further detail.

In the final part of the course, the examples are of reading data from Twitter and Google Maps. In theory, it sounds great and exciting, but in reality, I think it's an overkill for the purpose of the course. There's just too much stuff for a complete noob such as myself. Just a month ago, we were learning what's a dictionary and now we're going through nested dictionaries within lists within dictionaries... quite the jump. Adding to this - explaining what's an API is not done good enough. I only know what APIs do because in work in a SaaS company. If I only had the explanation the course provides, I would be immensely confused.

I'm not trying to say programming is easy, not at all. This particular course though can be done better, so it's easier for students to follow, I'm sure.

As usual, Dr. Chruck is great and it's a pleasure to have him as the tutor here.

I'll continue with the specialization and I hope course 4 will be structured better than this one. :)

Cheers and good luck!

This course, compared to the previous two of Uni of Michigan's Python series, is much more specialized, but it also has more elements thrown at you to overcome a challenge.

I must say, I encountered too many roadblocks that cannot be overcome unless you use different compilers that can solve all your problems. Atom is strictly recommended to run compilers, which was fine at first. But afterwards, when many more complicated modules had to be included, you are compelled to find another approach to run codes, because your compiler in case you know none other than Atom) can unexpectedly not run the imported modules or crash from running it. So I had to resort to Jupyter Notebook as a solution.

Not to mention, a few complicated aspects of a code to parse websites are not thoroughly explained, which leaves an empty feeling. Most importantly, however, is that this course felt like it necessitated "copy and paste from another template project" to pass assignments, which is not only underwhelming in terms of learning about it, but feels dishonest when walking out of this course.

Have I learned anything new that I will do during my work, or even pastime? Both yes and no. Yes because I can now parse a lot of website for a lot of cool coding details I enjoy reading over. And no, because I have not learned how to code any of those codes by myself, because I felt I was spoiled by the template codes presented to us in order to feel at ease with coding certain parts of the programs, for later assignments in particular.

I did not write this to repel the audience thinking of taking this course, because you will learn some nice material regarding cracking website coding details that are fun to do. But if you think you can code new programs entirely from scratch without a reference while taking the course, then the newcomers should look elsewhere for the same material. It does not hurt to learn through this course at all, just less satisfying compared to the first two modules of the series.

Ali Fuat Becan

Anonymous completed this course.

I have one big criticism of this class. The Python keyword "import" is never explained. The concept of "module" is never explained.

We're just told to cant this magic incantation "import re" and suddenly statements that generated traceback errors suddenly don't. Even more intriguingly, python now seems to recognize regular expressions!

Later, we're just told to cant another magic incantation "import xml.etree.ElementTree as ET" and now there are actually new data types!

How this happens is never explained.

To make this class perfect, you just need to add one -- just one -- lecture which explains what modules are and what importing them does. Take if from "just type this magic incantation," to "this is how we can add functions and data types and methods and expand python."

Python itself is a wonderfully-compact little language, just 33 keywords and just eight data types. Python itself can't interpret regular expressions, can't parse XML or JSON, can't convolve matrices of complex number. What makes Python such an amazing language is that one of the keywords is "import." With import, we can expand python to interpret regular expressions, parse XML or JSON, and convolve matrices of complex number too. You can even write a program that can convolve matrices of complex numbers that come from a web-based source in the JSON, all in one program. This is why it's so important to understand modules and libraries of modules and understand what import does. It shouldn't be taught as just some mysterious magical incantation.

Students should be taught that there are standard libraries of python modules available, that there are countless non-standard libraries and modules which are also available to "use at your own risk," that many companies and institutions have in-house libraries, and that they can even learn to create their own libraries if they want to (though the mechanics of this can be left to another class).

I have one big criticism of this class. The Python keyword "import" is never explained. The concept of "module" is never explained.

We're just told to cant this magic incantation "import re" and suddenly statements that generated traceback errors suddenly don't. Even more intriguingly, python now seems to recognize regular expressions!

Later, we're just told to cant another magic incantation "import xml.etree.ElementTree as ET" and now there are actually new data types!

How this happens is never explained.

To make this class perfect, you just need to add one -- just one -- lecture which explains what modules are and what importing them does. Take if from "just type this magic incantation," to "this is how we can add functions and data types and methods and expand python."

Python itself is a wonderfully-compact little language, just 33 keywords and just eight data types. Python itself can't interpret regular expressions, can't parse XML or JSON, can't convolve matrices of complex number. What makes Python such an amazing language is that one of the keywords is "import." With import, we can expand python to interpret regular expressions, parse XML or JSON, and convolve matrices of complex number too. You can even write a program that can convolve matrices of complex numbers that come from a web-based source in the JSON, all in one program. This is why it's so important to understand modules and libraries of modules and understand what import does. It shouldn't be taught as just some mysterious magical incantation.

Students should be taught that there are standard libraries of python modules available, that there are countless non-standard libraries and modules which are also available to "use at your own risk," that many companies and institutions have in-house libraries, and that they can even learn to create their own libraries if they want to (though the mechanics of this can be left to another class).