I have a file transfer app that I've been writing and part of it involves a PySide GUI that'll show progress of file transfers. I have dictionary data being passed around while the transferring goes and I'm struggling with which variety of TableView/Widget and AbstractItemView/Model/etc.
In short, I'd like to be able to use the dictionary of data to populate the table and then have the table reflect changing values in the dictionary (like progress %, filesize, etc). Unfortunately ModelViews still elude me and at least a step in the right kind of direction would be most appreciated. Thanks in advance, SO!
Related
This may be a question for Survey Monkey, but I felt that someone here may have encountered something like this in past experiences. Is there a way to work with the API of Survey Monkey (SM), to add the information from the survey straight into a database of my own? I realize that I can generate the information into output files, but I was wondering if there was a way to directly access the information from the SM database. I feel like this might cause some privacy concerns for SM. Has anyone attempted this, or would the best option of mine be to create my own surveys without a third party website?
I had a similar issue and here's my solution.
I was doing health related surveys which contain HIPPA protected Personal Health Info. Zapier is NOT HIPAA safe, so the "zap the results over to Google Drive" solution didn't work.
So I wanted a quick n dirty way to grab SM survey data and begin to design a data structure to analyse and store this data. I figured that I would start with <1000 results, sort it out, then build out a bigger/fancier structure as needed.
I just downloaded CSV's of the SM individual responses, munged the downloaded CSV files to make a Python CSV reader happy, then wrote a Python 3.5 script to grab the survey data and spit it out into a couple of output CSV files designed for different analytic purposes.
It was really quick and easy to alter the Python script to deliver different subsets of data to different output files, and really quick and easy to see if these output (CSV or XLS) files really told me what I wanted to know.
This is a really quick and easy way to start analysing right away without spending too much time on procedural overhead. You can alter CSV (or XLS ) tables really quickly and easily, so you can mix and match data / derivative data as much as you want. A wise person once told me "don't think, do." So the more you analyse on small runs of data, the better your final Big Buildout In The Sky will look.
Yah, you can spend a lot of time writing and API and setting up a dbase, but if you are not completely happy with what you want out of the SM data, start small. Hope this helps.
Similar to this question by #Gabriel Gonzalez: How to do fast data deserialization in Haskell
I have a big Map full of Integers and Text that I serialized using Cerial. The file is about 10M.
Every time I run my program I deserialize the whole thing just so I can lookup an handful of the items. Deserialization takes about 500ms which isn't a big deal but I alway seem to like profiling on Friday.
It seems wasteful to always deserialize 100k to 1M items when I only ever need a few of them.
I tried decodeLazy and also changing the map to a Data.Map.Lazy (not really understanding how a Map can be Lazy, but ok, it's there) and this has no effect on the time except maybe it's a little slower.
I'm wondering if there's something that can be a bit smarter, only loading and decoding what's necessary. Of course a database like sqlite can be very large but it only loads what it needs to complete a query. I'd like to find something like that but without having to create a database schema.
Update
You know what would be great? Some fusion of Mongo with Sqlite. Like you could have a JSON document database using flat-file storage ... and of course someone has done it https://github.com/hamiltop/MongoLiteDB ... in Ruby :(
Thought mmap might help. Tried mmap library and segfaulted GHCI for the first time ever. No idea how can even report that bug.
Tried bytestring-mmap library and that works but no performance improvement. Just replacing this:
ser <- BL.readFile cacheFile
With this:
ser <- unsafeMMapFile cacheFile
Update 2
keyvaluehash may be just the ticket. Performance seems really good. But the API is strange and documentation is missing so it will take some experimenting.
Update 3: I'm an idiot
Clearly what I want here is not lazier deserialization of a Map. I want a key-value database and there's several options available like dvm, tokyo-cabinet and this levelDB thing I've never seen before.
Keyvaluehash looks to be a native-Haskell key-value database which I like but I still don't know about the quality. For example, you can't ask the database for a list of all keys or all values (the only real operations are readKey, writeKey and deleteKey) so if you need that then have to store it somewhere else. Another drawback is that you have to tell it a size when you create the database. I used a size of 20M so I'd have plenty of room but the actual database it created occupies 266M. No idea why since there isn't a line of documentation.
One way I've done this in the past is to just make a directory where each file is named by a serialized key. One can use unsafeinterleaveIO to "thunk" the deserialized contents of each read file, so that values are only forced on read...
I have a web app that uses Guids as the PK in the DB for an Employee object and an Association object.
One page in my app returns a large amount of data showing all Associations all Employees may be a part of.
So right now, I am sending to the client essentially a bunch of objects that look like:
{assocation_id: guid, employees: [guid1, guid2, ..., guidN]}
It turns out that many employees belong to many associations, so I am sending down the same Guids for those employees over and over again in these different objects. For example, it is possible that I am sending down 30,000 total guids across all associations in some cases, of which there are only 500 unique employees.
I am wondering if it is worth me building some kind of lookup index that I also send to the client like
{ 1: Guid1, 2: Guid2 ... }
and replacing all of the Guids in the objects I send down with those ints,
or if simply gzipping the response will compress it enough that this extra effort is not worth it?
Note: please don't get caught up in the details of if I should be sending down 30,000 pieces of data or not -- this is not my choice and there is nothing I can do about it (and I also can't change Guids to ints or longs in the DB).
Your wrote at the end of your question the following
Note: please don't get caught up in the details of if I should be
sending down 30,000 pieces of data or not -- this is not my choice and
there is nothing I can do about it (and I also can't change Guids to
ints or longs in the DB).
I think it's your main problem. If you don't solve the main problem you will be able to reduce the size of transferred data to 10 times for example, but you still don't solve the main problem. Let us we think about the question: Why so many data should be sent to the client (to the web browser)?
The data on the client side are needed to display some information to the user. The monitor is not so large to show 30,000 total on one page. No user are able to grasp so much information. So I am sure that you display only small part of the information. In the case you should send only the small part of information which you display.
You don't describe how the guids will be used on the client side. If you need the information during row editing for example. You can transfer the data only when the user start editing. In the case you need transfer the data only for one association.
If you need display the guids directly, then you can't display all the information at once. So you can send the information for one page only. If the user start to scroll or start "next page" button you can send the next portion of data. In the way you can really dramatically reduce the size of transferred data.
If you do have no possibility to redesign the part of application you can implement your original suggestion: by replacing of GUID "{7EDBB957-5255-4b83-A4C4-0DF664905735}" or "7EDBB95752554b83A4C40DF664905735" to the number like 123 you reduce the size of GUID from 34 characters to 3. If you will send additionally array of "guid mapping" elements like
123:"7EDBB95752554b83A4C40DF664905735",
you can reduce the original size of data 30000*34 = 1020000 (1 MB) to 300*39 + 30000*3 = 11700+90000 = 101700 (100 KB). So you can reduce the size of data in 10 times. The usage of compression of dynamic data on the web server can reduce the size of data additionally.
In any way you should examine why your page is so slowly. If the program works in LAN, then the transferring of even 1MB of data can be quick enough. Probably the page is slowly during placing of the data on the web page. I mean the following. If you modify some element on the page the position of all existing elements have to be recalculated. If you would be work with disconnected DOM objects first and then place the whole portion of data on the page you can improve the performance dramatically. You don't posted in the question which technology you use in you web application so I don't include any examples. If you use jQuery for example I could give some example which clear more what I mean.
The lookup index you propose is nothing else than a "custom" compression scheme. As amdmax stated, this will increase your performance if you have a lot of the same GUIDs, but so will gzip.
IMHO, the extra effort of writing the custom coding will not be worth it.
Oleg states correctly, that it might be worth fetching the data only when the user needs it. But this of course depends on your specific requirements.
if simply gzipping the response will compress it enough that this extra effort is not worth it?
The answer is: Yes, it will.
Compressing the data will remove redundant parts as good as possible (depending on the algorithm) until decompression.
To get sure, just send/generate the data uncompressed and compressed and compare the results. You can count the duplicate GUIDs to calculate how big your data block would be with the dictionary compression method. But I guess gzip will be better because it can also compress the syntactic elements like braces, colons, etc. inside your data object.
So what you are trying to accomplish is Dictionary compression, right?
http://en.wikibooks.org/wiki/Data_Compression/Dictionary_compression
What you will get instead of Guids which are 16 bytes long is int which is 4 bytes long. And you will get a dictionary full of key value pairs that will associate each guid to some int value, right?
It will decrease your transfer time when there're many objects with the same id used. But will spend CPU time before transfer to compress and after transfer to decompress. So what is the amount of data you transfer? Is it mb / gb / tb? And is there any good reason to compress it before sending?
I do not know how dynamic is your data, but I would
on a first call send two directories/dictionaries mapping short ids to long GUIDS, one for your associations and on for your employees e.g. {1: AssoGUID1, 2: AssoGUID2,...} and {1: EmpGUID1, 2:EmpGUID2,...}. These directories may also contain additional information on the Associations and Employees instances; I suspect you do not simply display GUIDs
on subsequent calls just send the index of Employees per Association { 1: [2,4,5], 3:[2,4], ...}, the key being the association short id and the ids in the array value, the short ids of the employees. Given your description building the reverse index: Employee to Associations may give better result size wise (but higher processing)
Then its all down to associative arrays manipulations which is straightforward in JS.
Again, if your data is (very) dynamic server side, the two directories will soon be obsolete and maintaining synchronization may cost you a lot.
I would start by answering the following questions:
What are the performance requirements? Are there size requirements? Speed requirements? What is the minimum performance that is truly needed?
What are the current performance metrics? How far are you from the requirements?
You characterized the data as possibly being mostly repeats. Is that the normal case? If not, what is?
The 2 options you listed above sound reasonable and trivial to implement. Try creating a look-up table and see what performance gains you get on actual queries. Try zipping the results (with look-ups and without), and see what gains you get.
In my experience if you're not TOO far from the goal, performance requirements are often trial and error.
If those options don't get you close to the requirements, I would take a step back and see if the requirements are reasonable in the time you have to solve the problem.
What you do next depends on which performance goals are lacking. If it is size, you're starting to be limited if you're required to send the entire association list ever time. Is that truly a requirement? Can you send the entire list once, and then just updates?
I need some tips and examples for the following task:
I have a image data somewhere on my disk ... this data can be of type .svg/.bmp/.gif/.png ... lets say for the moment that all of them are of type .svg.
My task is to insert several of these image data in soecific places of the WordML that I am generating.
The generation of WordML is working superbly, but as I have NEVER before read or heard about inserting image data in wordML data ... I am kinda lost.
I am going forward with <maml:medialink> and <maml:image>.
Would be really nice of you, if anyone can give me a little introduction and support with this new venture of mine.
Thank you.
Jasmin
ETL is pretty common-place. Data is out there somewhere so you go get it. After you get it, it's probably in a weird format so you transform it into something and then load it somewhere. The only problem I see with this method is you have to write the transform rules. Of course, I can't think of anything better. I supposed you could load whatever you get into a blob (sql) or into a object/document (non-sql) but then I think you're just delaying the parsing. Eventually you'll have to parse it into something structured (assuming you want to). So is there anything better? Does it have a name? Does this problem have a name?
Example
Ok, let me give you an example. I've got a printer, an ATM and a voicemail system. They're all network enabled or I can give you connectivity. How would you collect the state from all these devices? For example, the printer dumps a text file when you type status over port 9000:
> status
===============
has_paper:true
jobs:0
ink:low
The ATM has a CLI after you connect on port whatever and you can type individual commands to get different values:
maint-mode> GET BILLS_1
[$1 bills]: 7
maint-mode> GET BILLS_5
[$5 bills]: 2
etc ...
The voicemail system requires certain key sequences to get any kind of information over a network port:
telnet> 7,9*
0 new messages
telnet> 7,0*
2 total messages
My thoughts
Printer - So this is pretty straight-forward. You can just capture everything after sending "status", split on lines and then split on colons or something. Pretty easy. It's almost like getting a crap-formatted result from a web service or something. I could avoid parsing and just dump the whole conversation from port 9000. But eventually I'll want to get rid of that equal signs line. It doesn't really mean anything.
ATM - So this is a bit more of a pain because it's interactive. Now I'm approaching expect or a protocol territory. It'd be better if they had a service that I could query these values but that's out of scope for this post. So I write a client that gets all the values. But now if I want to collect all the data, I have to define what all the questions are. For example, I know that the ATM has more bills than $1 and $5 so I'd have a complete list like "BILLS_1 BILLS_5 BILLS_10 BILLS_20". If I ask all the questions then I have an inventory of the ATM machine. Of course, I still have to parse out the results and clean up the text if I wanted to figure out how much money is left in the ATM machine. So I could parse the results and figure out the total at data collection time or just store it raw and make sense of it later.
Voicemail - This is similar to the ATM machine where it's interactive. It's just a bit weirder because the key sequences/commands aren't "get key". But essentially it's the same problem and solution.
Future Proof
Now what if I was going to give you an unknown device? Like a refrigerator. Or a toaster. Or anything? You'd have to write "connectors" ahead of time or write a parser afterwards against some raw field you stored earlier. Maybe in the case of these very limited examples there's no alternative. There's no way to future-proof. You just have to understand the new device and parse it at collection or parse it after the fact (your stored blob/object/document).
I was thinking that all these systems are text driven so maybe you could create a line iterator type abstraction layer that simply requires the device to split out lines. Then you could have a text processing piece that parses based on rules. For the ATM device, you'd have to write something that "speaks ATM" and turns it into lines which the iterator would then take care of. At this point, hopefully you'd be able to say "I can handle anything that has lines of text".
But then what will you call these rules for parsing the text? "Printer rules" might as well be called "printer parser" which is the same to me as "printer transform". Is there a better term for all of this?
I apologize for this question being so open ended. :)
When your sources of information are as disparate as what you illustrate then you have no choice but to implement the Transform in order to bring the items into a common data repository. Usually your data sources won't be this extreme, the data will all be related in some way but you may be retrieving it from different sources (some might come from a nicely structured database, some more might come from an Excel or XML or text file, some more might come from a web service call, etc).
When coding up a custom ETL application, a common pattern that is used is the Provider model, this enables you to write a whole bunch of custom providers to load/query and then transform the data. All the providers will implement a common interface with some relatively common function definitions (for example QueryData(), TransformData()), but the implementation of those methods will be wildly different depending on the data source being dealt with - the interface just gives a common way to deal with all the different providers. You can then use an XML configuration file to dictate which providers to run and any other initial settings they may require. Tools like SSIS abstract this stuff away for you by giving you a nice visual designer, but you can still get down and dirty and write your own code which it calls.
Now what if I was going to give you an unknown device? Like a refrigerator. Or a toaster.
No problem, i would just write a new provider, which can sit in its very own assembly (dll), so it can be shipped (or modified, upgraded, etc) in isolation to any other providers i already have. Or if i was using SSIS then i would write a new DTS package.
I was thinking that all these systems are text driven so maybe you could create a line iterator type abstraction layer ... Then you could have a text processing piece that parses based on rules.
Absolutely - you can have a base class containing common functionality which several different providers can implement, and each provider can use its own set of rules which could be coded into it or they can be contained in an external configuration file.
So I could parse the results and figure out the total at data collection time or just store it raw and make sense of it later.
Use whichever approach makes sense for the data you are grabbing. It is also quite common for an ETL process to dump its data into a staging area (like some staging tables in a database) while the data is all being aggregated and accumulated, and then further process it to link related data and perform calculations. In the case of your ATM it may not be necessary to calculate a cash balance at ETL time because you can easily calculate it at any time in the future.