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I need to visualize a graph. I don't know how to name it (by the way, if you know - I'll appreciate if you tell me). It would be ideal for graph elements to be clickable (so that when user clicks on a block, I can handle an event with the element id specified) but I can survive even without any interactivity. I may like to be able to focus on a particular node and layout all others to view from its perspective. Are there any components available good for this task? If no, what should I look for to help me to develop an algorithm for drawing such a graph with visually-comfortable layout?
Practical nature of this graph is pretty common: each block represents a derivation from 2 operands. Orange circles are references to 2 operands, green circles are connection points to consumers. It can be significant to distinguish an operand position (left or right), for example if a derivation represents a mathematical operation of difference or division (in this particular case a block can be triangular, but in other cases an operand itself can make use of being aware of for what blocks is it a left operand and for what blocks is it a right). Another common application is intersecting sets with complex relations.
You could take a look at Graph#, but I'm not sure how well it'll handle composite nodes like that. It could be a good starting point though.
I also would like to point you to graphviz. It is not a .NET solution but you can feed it files that are easy enough to write in order to create graphs. I don't think layouting is a very simple thing to do, especially with increasing node count, so it should be a good thing to find some tool for that.
As It seems Microsoft itself has done a really good job on graph visualization called automatic-graph-layout.
Here's the link https://github.com/microsoft/automatic-graph-layout.
Well, you first need to represent it somehow in memory, there are many ways, like adjacency list. Then you need to draw it. While generally drawing a graph is simple, it's not that simple if you need to layout it. Looks like in your case, that's exactly what you need to do to come to that nice representation. It ain't going to be easy.
EDIT: Interesting, there seems to be a library made by Microsoft Research.
I don't know how useful it will be in this particular scenario, but you might want to take a look at http://quickgraph.codeplex.com/
Graphviz4Net provides WPF component for graphs visualization. It depends on GraphViz (open source command line graph visualization tool).
I can not find this component and i decided writen my own control, line and head, and use them to visualization my graph's
If the needed your i can give it's component and program to demonstrate him/
I writen component and program's in visual studio 2008 language C#
This is a fairly new and maintained .NET wrapper for Graphviz: https://github.com/Rubjerg/Graphviz.NetWrapper
(Disclaimer: I'm the author)
This wrapper works differently from other wrappers, since it makes direct function calls to the native Graphviz code. This means you can not only programatically construct your graph in C# code, but also read the layout attributes back out in C# code and render it any way you want. The latter sounds specifically like something you would be interested in.
A quite good looking one is the Diagram tool from Nevron. But it's not for free!
I'm currently using the charts and user interfaces from them and they work quite good.
Have used this commercial product with success: GoDiagram
It support the multiple ports on the nodes like you have shown.
i feel like i'm going back to the stone age.
how do i relearn to develop without intellisense (pydev intellisense doesn't count).. in general, how does one successfully leave the comfort of visual studio ?
I recently learned python with a strong C# background.
My advise: Just do it. Sorry, couldn't resist but I'm also serious. Install python and read: Python.org documentation (v2.6). A book might help too -- I like the Python PhraseBook. From there, I started using python to implement solutions for various things. Most notably, ProjectEuler.net questions.
It forced me to consider the languages and built in data structures.
Python is truly easy to use and intuitive. To learn the basics, took me about an hour. To get pretty good with it, took around 5 hours. Of course, there is always more to learn.
Also, I want to note that I would discourage using IronPython or Jython because I feel learning core, regular python is the first step.
Python has rich "introspection" features. In particular, you can find out a lot about built-in features using a command called help() from the Python command line.
Suppose you want to use regular expressions, and want to find out how to use them.
>>> import re
>>> help(re)
You get a nice display of information, automatically shown to you a page at a time (hit the space bar to see the next page).
If you already know you want to use the sub() function from the re module, you can get help on just that:
>>> help(re.sub)
And this help() feature will even work on your own code, as long as you define Python docstrings for your modules, classes, and functions.
You can enable features in the vim editor (or gvim, or vim for Windows) that enable an "IntelliSense"-like autocompletion feature, and you can use Exuberant Ctags to generate hyperlink "tags" to let you navigate quickly through your code. These turn vim into something that is roughly as powerful as an IDE, with the full power of vim for editing. (There isn't an explicit refactoring tool built in to vim, but there are options available.
And as others have noted, you can get IDEs for Python too. I've used the Wingware IDE, and I recommend it. I try to do most of my work with free, open-source software, but that is one piece of proprietary software I would be willing to buy. I have also used Eclipse with the Pydev plugin (I used its refactoring tool and it worked fine).
P.S. Python has a richer feature set than C#, albeit at the cost that your code won't run as fast. Once you get used to Python, you won't feel like you are in the stone age anymore.
One step at a time?
Start off with simple programs (things you can write with your eyes closed in C#), and keep going... You will end up knowing the API by heart.
<rant>
This is sort of the reason that I think being a good visual studio user makes you a bad developer. Instead of learning an API, you look in the object browser until you find something that sounds more or less like what you are looking for, instantiate it, then hit . and start looking for what sounds like the right thing to use. While this is very quick, it also means it takes forever to learn an API in any depth, which often means you end up either re-inventing the wheel (because the wheel is buried under a mountain worth of household appliances and you had no idea it was there), or just doing things in a sub-optimal way. Just because you can find A solution quickly, doesn't mean it is THE BEST solution.
</rant>
In the case of .NET, which ships with about a billion APIs for everything under the sun, this is actually preferred. You need to sift through a lot of noise to find what you are aiming for.
Pythonic code favors one, obvious way to do any given thing. This tends to make the APIs very straight forward and readable. The trick is to learn the language and learn the APIs. It is not terribly hard to do, especially in the case of python, and while not being able to rely on intellisense may be jarring at first, it shouldn't take more then a week or two before you get used to it not being there.
Learn the language and the basic standard libraries with a good book. When it comes to a new library API, I find the REPL and some exploratory coding can get me to a pretty good understanding of what is going on fairly quickly.
You could always start with IronPython and continue to develop in Visual Studio.
The python ide from wingware is pretty nice. Thats what I ended up using going from visual studio C++/.net to doing python.
Don't worry about intellisense. Python is really simple and there really isn't that much to know, so after a few projects you'll be conceiving of python code while driving, eating, etc., without really even trying. Plus, python's built in text editor (IDLE) has a wimpy version of intellisense that has always been more than sufficient for my purposes. If you ever go blank and want to know what methods/properties and object has, just type this in an interactive session:
dir(myobject)
Same way you do anything else that doesn't have IntelliStuff.
I'm betting you wrote that question without the aid of an IntelliEnglish computer program that showed you a list of verbs you could use and automatically added punctuation at the end of your sentences, for example. :-)
I use Eclipse and PyDev, most of the time, and the limited auto-completion help that it provides is pretty useful.
It's not ever going to come up to the level of VS's IntelliSense, and it can't, because of the dynamic nature of Python. But there are compensations, big ones.
The biggest is the breaking of the code-compile-test cycle. It's so easy to write and test prototype code in IDLE that very often it's where I go first: I'll sketch out and test a couple of methods that have to interoperate, figure out that there's something I don't know, learn it, fix my test, and then port the whole thing over to PyDev and watch it work the first time.
Another is that it's a lot simpler. It's really important to know what the standard modules are, and what they do, but for the most part that can be picked up with a little reading. I only use a small handful of modules in my everyday programming - itertools, os, csv (yeah, well), datetime, StringIO - and everything else is there if I need it, but usually I don't.
The stuff that it's really important to know is stuff that IntelliSense couldn't help you with anyway. Auto-completion isn't going to make
self.__dict__.update(kwargs)
make a damn bit of sense; you have to learn what an amazing line of code that is, and why you'd write it, by yourself.
Then you'll think, "how would I even begin to implement something like that in C#?" and realize that the tools these stone-age people are using are a little more sophisticated than you think.
A mistake people coming from C# or Java make a lot is recreate a large class hierarchy like is common in those languages. With Python this is almost never useful. Instead, learn about duck typing. And don't worry too much about the lack of static typing: in practice, it's almost never an issue.
I'm not too familiar with Python so I'll give some general advice. Make sure to print out some reference pages of common functions. Keep them by you(or pinned to a wall or desk) at all times when your programming.. I'm traditionally a "stone age" developer and after developing in VS for a few months I'm finding my hobby programming is difficult without intellisense.. but keep at it to memorize the most common functions and eventually it'll just be natural
You'll also have to get use to a bit more "difficult" of debugging(not sure how that works with python)
While your learning though, you should enjoy the goodness(at least compared to C#) of Python even if you don't have intellisense.. hopefully this will motivate you!
I've only ever used IDLE for python development and it is not fun in the least. I would recommend getting your favorite text editor, mine is notepad++, and praying for a decent plugin for it. I only ever had to go from Eclipse to Visual Studio so my opinions are generally invalid in these contexts.
Pyscripter does a reasonable job at auto-completion/intellisense. I've been using it recently as I started to learn Python/Django, where I've been mainly a C# developer for the last few years.
I suggest going cold turkey - languages like Python shine with great text editors. Choose one you want to become amazing at (vim, emacs, etc.) and never look back.
I use Komodo Edit and it does reasonably good guessing at the autocompletion.
Others have suggested several editors that have intellisense-like capabilities. Try them out.
Also install ipython and use that to learn the language interactively. It is like a souped up version of the regular python interactive shell with lots and lots of added capabilities, and one of the most useful it its extensive context sensitive tab-completion and help.
For example if you type
import r<tab>
it will show all the modules you can import starting with r
import re
re.<tab>
will show all the objects in the re module
re.compile?
will show the docstring and other information about the re.compile function, automatically piping it through a pager if it is longer than a screenful.
re.compile??
will show the source code as well, if available.
Using this I find it is much faster to switch to ipython and query objects directly than it is to look up anything in the docs. You have access to the usual python help() system as well.
ipython has lots and lots of other features - far too many to cover in a short post.
If it is possible to auto-format code before and after a source control commit, checkout, diff, etc. does a company really need a standard code style?
It feels like standard coding style debates that have been raging since programming began like "put the bracket on the following line" or "properly indent your (" are no longer essential.
I realize in languages where white space matters the diff will have to consider it but for languages where the style is a personal preference is there really a need to worry about it anymore?
Auto-format can really only address whitespace.
It wont address developers giving variables bizarre nonsensical names.
It won't address some developers having functions return null on an error vs throwing an exception.
I'm sure others can think of more examples.
This is what we do at my work:
We all use Eclipse. We don't have a policy for using Eclipse but somehow none of us is an IDEA/IntelliJ guy. We also think our code should be written with legacy in mind. This means our code has to be readable in a certain way even years after (#1) no matter who wrote it and if that person even is in the company anymore.
Eclipse has couple handy features, automatic format on save and a specific Formatter tool. As you can see from the linked screenshot, it can be configured with XML. Thus there's a bunch of premade XML:s available for every worker in our company so that when a new guy comes in, we walk him through of the whole process and configure their Eclipse for them (yes, it's slightly evil thing to do) so that it actually uses those formatting XML:s we have provided. We do not enforce automatic format on save, we don't want to be completely intrusive, we just want to push all our developers into the right directions. For even increased compatability, we mostly use rules defined in JCC.
Next comes the important part, the actual builds. We are those who embrace automatic builds and for that we use Hudson Continuous Integration Server. There's two important parts in our configurations beyond this:
We use CVS loginfo to trigger builds whenever something is committed.
We utilize several plugins available for Hudson, including Continuous Integration Game in conjuction with the most important one, Checkstyle.
The Checkstyle Plugin is the magician in our code style enforcement guide line:
After commiting code to CVS, Hudson build is triggered
After build has been completed succesfully (all unit tests pass etc.), Checkstyle inspects the actual source files
Checkstyle ranks the code based rules we have defined for it
Continuous Integration Game sees the result of Checkstyle and awards/takes away points for the person who has the ownership for the relevant part of the code
Leaderboard shows total points for every commiter in system
Basically this means that when anyone commits ugly code into our CVS, our build server automatically reduces that person's points.
This means that eventually any one of us can be ranked on the Leaderboard based on the general code quality in both look and OO principles such as Law of Demeter, Cyclomatic complexity etc. etc. Naturally this isn't a completely serious statistic, but it's a good indication you're doing something wrong when causing a build to be initiated in our CI won't reduce your points - most of our commits are worth between 1 and 5 points.
And is it working? Sort of, I don't think anyone of us at my work writes ugly or unmaintainable code and personally I love to hunt all kinds of scores so it's definitely motivating me to make code that looks nice and follows all the OO paradigms I know of.
And do we as a company really need it? I think we do as you should see from reading this entire answer, it can be considered a good practice for the advancements it brings.
#1: in a related note, I refactored legacy code from 2002 today which used those standards, didn't look "bad" at all even in its original form and certainly not worse in its new form
No, not really.
If you can actually get it to work consistently and not make it flag code has changed due to a different style of laying the code out.
However, this is just a small part of coding standards. It won't cover multiple return statements, the use or not of ternary operators, etc.
It is always nice if the coding style that the shop uses is the same one that is also followed by the development tools.
Otherwise, if there is a large body of code that already follows a shop standard which is NOT the same as that of the tools you have two choices:
Modify all of the code to follow the tool standard, or
Maintain the existing shop standard.
Many shops do the latter. Regardless, there does need to be some kind of standard, and it does need to be followed.
Some development tools allow you to tweak their standard. In some cases you may be able to bring the tools in alignment with the shop standard.
It probably doesn't matter that much anymore if you can ensure that everybody in the team sees the source code "correctly" formatted, whatever they think it is. However I've not seen a system that can do that - you can do parts of it (say, reformat before and after checkin/checkout) but these days you also have to consider web interfaces into the version control, external code review systems that interact directly with the version control system etc.
The main purpose of a standard code style is (IMHO) to ensure that you can read other team members' code easily without having to start reverse engineering it because all the code is written using the same sort of guiding principles. Indenting and parentheses placement seem to be a major hangup on this but they are only a very small and in my opinion, somewhat overblown and not very important part of the need to make code consistent.
Unfortunately I'm not aware of any tools that can automatically apply consistent coding principles to source code...
Yes, coding styles are needed if there is a desire to have a homogeneous code base. Such a code base can be useful in preventing individual ownership of parts of the code base, which can cause problems when people leave the team. If you can't imagine having wildly different styles and problems understanding all of it, just look at all the different ways English text can be organized in various communications, all written but quite different such as tweets, e-mail, text messages, IM, message board posts, etc. and changes in fonts, capitalization, decorations, etc.
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For someone who’s been happily programming in C# for quite some time now and planning to learn a new language I find the Python community more closely knit than many others.
Personally dynamic typing puts me off, but I am fascinated by the way the Python community rallies around it. There are a lot of other things I expect I would miss in Python (LINQ, expression trees, etc.)
What are the good things about Python that developers love? Stuff that’ll excite me more than C#.
For me its the flexibility and elegance, but there are a handful of things I wish could be pulled in from other languages though (better threading, more robust expressions).
In typical I can write a little bit of code in python and do a lot more than the same amount of lines in many other languages. Also, in python code form is of utmost importance and the syntax lends its self to highly readable, clean looking code. That of course helps out with maintenance.
I love having a command line interpreter that I can quickly prototype an algorithm in rather than having to start up a new project, code, compile, test, repeat. Not to mention the fact I can use it to help me automate my server maintenance as well (I double as a SA for my company).
The last thing that comes to mind immediately is the vast amounts of libraries. There are a lot of things already solved out there, the built-in library has a lot to offer, and the third party ones are many times very good (not always though).
Being able to type in some code and get the result back immediately.
(Disclaimer: I use both C# and Python regularly, and I think both have their good and bad points.)
I'm primarily .NET developer and using Python for me personal projects.
What are the good things about python that developers love?
I can say for myself - Python is like a breath of fresh air.
1) It's simple to learn, took about a week for me in the evenings. I'm saying about Python + Django. Python syntax is quite simple.
2) It's simple to use. No troubles installing Python + Django on Windows at all.
3) It can be run on Windows and UNIX.
4) I need it for web, so I get cheaper hosting than ASP.NET.
5) All the advantages of Python language over C#. Like tuples - so useful!
The only thing I don't like is that my favorite IDE Visual Studio doesn't support it (I know about IronPython, don't you worry).
I'm a very heavy user of both C# and Python; I've built very complicated applications in both languages, and I've also embedded Python scripting in my major C# application. I'm not using either to do much in the way of web work right now, but other than that I feel like I'm pretty qualified to answer the question.
The things about Python that excite me, in particular:
The deep integration of generators into the language. This was the first thing that made me realize that I needed to take a long, serious look at Python. My appreciation for this has deepened considerably since I've become conversant with the itertools module, which looks like a nifty set of tools but is in fact a new way of life.
The coupling of dynamic typing and the fact that everything's an object makes pretty sophisticated techniques extremely simple to implement. It's so easy to replace logic with tables in Python (e.g. o = class_map[k]() instead of if k='foo': o = Foo()) that it becomes a basic technique. It's so normal in Python to write methods that take methods as parameters that you don't raise an eyebrow when you see d = defaultdict(list).
zip, and the methods that are designed with it in mind. It takes a while before you can intuitively grasp what dict(zip(k, v)) and d.update(zip(k, v)) are doing, but it's a paradigm-shifting moment when you get there. An entire universe of uninteresting and potentially error-laden code eliminated, just by using one function. Then you start designing functions and classes with the expectation that they'll be used in conjunction with zip, and suddenly your code gets simpler and easier. (Protip: Or itertools.izip. Or itertools.izip_longest.)
Speaking of dictionaries, the way that they're deeply integrated into the language. Understanding what a line of code like self.__dict__.update(**kwargs) does is another one of those paradigm-shifting moments.
List comprehensions and generator expressions, of course.
Inexpensive exceptions.
An interactive intepreter.
Function decorators.
IronPython, which is so much simpler to use than we have any right to expect.
And that's without even getting into the remarkable array of functionality in the standard modules, or the ridiculous bounty of third-party tools like BeautifulSoup or SQL Alchemy or Pylons.
One of the most direct benefits that I've gotten from getting deeply into Python is that it has greatly improved my C# code. I could generally understand code that had a variable of type Dictionary<string, Action<Foo>> in it, but it didn't seem natural to write it. (I use static dictionaries to replace hard-coded logic far more frequently today than I did a year ago.) I have no difficulty understanding what LINQ is doing now, or how IEnumerable<T> and return yield work.
So what don't I like about Python?
Dynamic typing really limits what you can do with static code analysis. Not only isn't there a tool like Resharper for Python, in a language where it's possible to write getattr(x, y)() there really can't be.
It has a bunch of inelegant conventions. How I would love to be able to go back in time and try to talk GVR out of the idea that lambda expressions should be introduced with the word lambda - it's pretty damning that something as fundamental as lambda expressions should be more concise in C# than they are in Python. The leading and trailing double-underscore convention is horrible, and the fact that people mutely acquiesce to it is testimony to Dostoevsky's observation that man is the animal who can get used to anything. And don't get me started on the fact that a module with the name of StringIO was allowed to get out the door.
Some of the features that make Python work on multiple platforms also make it kind of baffling. It's easy to use import, but it's really not easy to understand what the hell it's actually doing. (Where is it looking? What does __init__.py do? Etc.)
The amazingly rich library of standard modules is so amazingly rich that it's hard to know what's in it. It's often easier to write a function than it is to find out whether or not there's something in the standard library that does the same thing - I'm looking at you, itertools.chain.
Your question is kind of like a plumber asking why carpenters are always going on and on about hammers. After all the plumber doesn't have a hammer and has never missed it. Python (even IronPython) and C# target different types of developers and different types of programs. I am very comfortable in Python and enjoy the freedom to focus on the business rules without being distracted by the syntax requirements of the language. On the other hand I have written some fairly substantial code in C# and would be very concerned about the lack of type safety had I taken on the same task in Python. This is not to say that Python is a "toy" language. You can (and people have) write a complete medium or large application in Python. You have the freedom of dynamic typing, but you also have the responsibility to keep it all straight (frameworks help here). Similarly you can write a small application in C#, but you will bring along some overhead you do not likely need.
So if the problem is a nail use a hammer, if the problem is a screw use a screw driver. In other words spend some time to learn Python, get to know it's streangths (text processing, quick coding cycles, simple clean code, etc) and then when you are looking at tackling a new problem ask whether you would be better off in Python or C#. One thing is certain. So long as C# is the only programming language you know, it is the only one you will ever use.
Pat O
My language of choice is C#, and I didn't quite see the point for me to learn Python so far. This talk from PDC09 really piqued my interest: the guy demonstrates how you can use IronPython (or IronRuby) to make a C# app scriptable (in his demo, drop a Python script in a text box, and it works with/extends your C# code). I found this really fascinating: I don't even know where I would start to do something similar in C#, and this made me at least appreciate that it brings something different to the table, which could really enrich what I can develop!
I'm an asymmetrical user of both languages, in a sense that I use C# mostly professionally and Python for all my "fun" projects (not that work is never fun, but... you know...)
This difference of context may skew my perspective, including my opinion that they are two distinct types (pun intended) of languages for, generally, distinct purposes.
This said, it may not be a coincidence that Python is, at this point in time, [one of?] the languages of choice for all kinds of cutting edge, somewhat scholarly, technology/science oriented projects. (And BTW, this "scholarly" keyword here doesNOT imply, that Python is a university toy, plenty of "serious" applications in plenty of domains/industry are proof to the contrary). This may be due to several factors:
(I don't develop most points, readily well expressed in other responses)
the openness and quasi universal availability of Python (unlike C# !)
the lightweight / ease of use / low learning curve
the extensive, high quality, "standard" library and the extensiver (and occasionally bum quality, but on the whole available, open-sourced, etc.) additional library.
the wide array of open source projects in Python language
the relative ease to bind with C/C++ for reusing legacy code, but also for placing performance-critical portions of a project
the generally higher level of abstraction of may constructs of the language
the multi-paradigms (imperative, object oriented and functional)
the availability of practitioners in so many domain of science and technology
and, yes, the
"herd mentality effect" mentioned in a remark, possibly in a [self?] deriding way. The fact that a language attracts a broad, "closely knit" community, makes it attractive too, beyond the superficial ("look cool" and such) traits of herd mentality. Put in broader context, sometimes the best technology/language to use is not measured on the its intrinsic merits but on the overall "picture", including the user community.
I like all stuff with [] and {}. Selectors like this [-1:1]. Possibility to write less code, but more something meaningfull, that gives to write Models and other declarative things very DRY.
Like any programming language, it is just a tool in the box or a brush by which you may paint your creation. Any creative endeavour requires that the artist loves the tools he uses; otherwise, the outcome suffers. Some people like Python for the same reason others love Perl. Incidentally, I have found that most Python lovers loathe Perl's flexible and expressive syntax. As a Perl lover, I don't hate Python, but consider it to be overly structured and restrictive.
If you ask me, all of these throngs of people who seem to love Python were silently suffering under the tool choices before Python came into being. Some suffered under Perl, others under something else. In other words, I believe that when Python came along, it found a large group of silent sufferers longing for a tool like Python.
I can't program in Python because I can't "think" in Python. I can "think" in Perl, therefore, it is the tool I prefer. The silently suffering mass of, now, Python users seem to have found some long lost salvation. Now if they could only keep their evangelism to themselves :).
If you are familiar with the .NET CLR and prefer a statically-typed language, but you like Python's lightweight syntax, then perhaps Boo is the language for you.
Don't get me wrong, I am and will always be a devoted fan of C#.
But sometimes there are things I can't do in C#. lthough C# keeps reducing those gaps, Python is still the language I go to to fill them.
It's dynamic, flexible, powerful, and clean. Lovely language. Whenever I need to script or build dynamic or functional (as in functional programming) software, I go Python.
For me Python is the most elegant language I've used. The syntax is minimalist (significantly less punctuation than most) and intentionally modeled after the psuedo-code conventions which are ubiquitously used by programmer to outline their intentions.
Python's if __name__ == '__main__': suite encourages re-use and test driven development.
For example, the night before last I hacked together to run thousands of ssh jobs (with about 100 concurrently) and gather up all the results (output, error messages, exit values) ... and record the time take on each. It also handles timeouts (An ssh command can stall indefinitely on connection to a thrashing system --- it's connection timeouts and retry options don't apply after the socket connection is made, not matter if the authentication stalls). This only takes a few dozen lines of Python and it's really is easiest to create it as a class (defined above the __main__ suite) and do my command line parsing in a simple wrapper down inside __main__. That's sufficient to do the job at hand (I ran the script on 25,000 hosts the next day, in about two hours). It I can now use this code in other scripts as easily as:
from sshwrap import SSHJobMan
cmd = '/etc/init.d/foo restart'
targets = queryDB(some_criteria)
job = SSHJobMan(cmd, targets)
job.start()
while not job.done():
completed = job.poll()
# ...
# Deal with incremental disposition of of completed jobs
for each in sorted(job.results):
# ...
# Summarize results
... and so on.
So my script can be used for simple jobs ... and it can be imported as a module for more specialized work that couldn't be described on my wrapper's command line. (For example I could start up "consumer" subprocesses for handling other work on each host where the job was successful while spitting out service tickets or automated reboot requests for all hosts reporting timeouts or failures, etc).
For modules which have no standalone usage I can use the __main__ suite to contain unit-tests. Thus every module can contain its own tests ... which, in fact, can be integrated into the "doc strings" using the doctest module from the standard libraries. (Which, incidentally, means that properly formatted examples in the documentary comments can be kept in sync with the implementation ... since they are parts of the unit-test suite).
The main thing I like about Python is its very concise, readable syntax. Though using indentation as a block delimiter can seem strange at first, once you begin to code a lot in the language I find it begins to make sense. Though the core language is quite simple, its more advanced features, e.g. list comprehension, decorators and generators, are rather useful too.
In addition, the Python standard library is just fantastic; its documentation is very well written, and it contains a lot of very useful packages. I also find that there are plenty of good bindings for C libraries, such as PyGTK, Webkit and Qt, to name but a few.
One caveat is that Python, like most dynamic languages, is quite slow in comparison with compiled, statically-typed languages. However, you can easily extend it with C, allowing you to write code requiring better performance in C and the rest in Python.
It's a great language overall, and (for me at least) makes coding more productive and enjoyable.
Since yesterday, I am analyzing one of our project with Ndepend (free for most of its features) and more I am using it, and more I have doubt about the real value of this type of software (code-analysis software).
Let me explain, The system build a report about the health of the system and class by Rank every metric. I thought it would be a good starting point to do modifications but most of the top result are here because they have over 100 lines inside the class (we have big headers and we do use VS comments styles) so it's not a big deal... than the number of Afferent Coupling level (CA) is always too high and this is almost very true for Interface that we used a lot... so at this moment I do not see something wrong but NDepend seem to do not like it (if you have suggestion to improve that tell me because I do not see the need for). It's the samething for the metric called "NOC" for Number of children that most of my Interface are too high...
For the moment, the only very useful metric is the Cyclomatic Complexity...
My question is : Do you find is worth it to analyse code with Automatic Code Analyser like NDepend? If yes, how do you filter all information that I have mentionned that doesn't really show the real health of the system?
Actually metrics are just one feature of NDepend, did you try to use VisualNDepend that lets you analyze your project much more in depth than the report? By reading your comment, I am almost sure you didn't play with NDepend UI (standalone or integrated in Visual Studio) which is the best way to filter data about your code base.
I am one of the developers of NDepend and we use it a lot to analyze our own code. Basically we write our own quality rules with Code Rules over LINQ Queries (CQLinq). These rules automatically make sure that we don't have regression on our design. Here you'll find the list of around 200 default code rules.
Here are some unique features of NDepend and not related to code metrics:
Write CQLinq rules to make sure we don't have architectural flaws, such as dependency cycles between our components, UI using directly the DB or DB entangled with the business objects.
Make sure we don't have problem with code coverage by tests (like we make sure with a CQLinq rule that if a class is supposed to be 100% covered, it will remain 100% covered in the future)
Enforce side-effects-free code (immutable class/pure methods)
Use the ability to compare 2 analysis to code review changes since the last release, before doing a new release. More specifically, I enjoy using NDepend to know which method has been added and refactored since the last release, and is not 100% covered by tests.
Having an optimal encapsulation for all our members and types (like knowing which internal methods can be declared as private). This is also related to dead-code detection that NDepend also supports.
For a complete list of features if NDepend, see here.
I don't necessarily see NDepend results as "good" or "bad" in software engineering, there's always a good reason why an application is designed the way it is. I see it as a report that can probably help me point out issues with my design, but I have the final word when it comes to deciding if a method needs to be refactored or if it's good the way I designed it. In general, don't get too caught up trying to answer if it's worth it or not. It definitely is, instead I would suggest you carefully review the results. This will help you view your design from another perspective and there may be occasions where you decide the way you designed it is the best to achieve your applications goals.