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• Code completion in NetBeans' python plugin does not work properly

  - by T.K.

  I am asking on StackOverflow because surely I am doing something completely silly and I hope S.O. might provide me with a quick answer. I've installed the latest stable Python-plugin for NetBeans. It works great, and I tested code completion with various packages such as sys, os and so on. It works beautifully. However, it does not seem to pick up the code completion for the code in my own project. I created a package called mypackage (it has _init_.py as well), and in it I have a module called mymodule.py. Inside mymodule I've put a class called MyClass, complete with doc-strings and all. Please refer to this screenshot to describe what happens in code-completion: As you see, it's suggesting irrelevant things, as opposed to just MyClass. (Note that if I execute mymodule.MyClass() it works 100%, it's just that I would really like code completion on my own code) Hope I'm just doing something silly here... Any ideas?

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• Is it possible to do A/B testing by page rather than by individual?

  - by mojones

  Lets say I have a simple ecommerce site that sells 100 different t-shirt designs. I want to do some a/b testing to optimise my sales. Let's say I want to test two different "buy" buttons. Normally, I would use AB testing to randomly assign each visitor to see button A or button B (and try to ensure that that the user experience is consistent by storing that assignment in session, cookies etc). Would it be possible to take a different approach and instead, randomly assign each of my 100 designs to use button A or B, and measure the conversion rate as (number of sales of design n) / (pageviews of design n) This approach would seem to have some advantages; I would not have to worry about keeping the user experience consistent - a given page (e.g. www.example.com/viewdesign?id=6) would always return the same html. If I were to test different prices, it would be far less distressing to the user to see different prices for different designs than different prices for the same design on different computers. I also wonder whether it might be better for SEO - my suspicion is that Google would "prefer" that it always sees the same html when crawling a page. Obviously this approach would only be suitable for a limited number of sites; I was just wondering if anyone has tried it?

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• SQL Table Setup Advice

  - by Ozzy

  Hi all. Basically I have an xml feed from an offsite server. The xml feed has one parameter ?value=n now N can only be between 1 and 30 What ever value i pick, there will always be 4000 rows returned from the XML file. My script will call this xml file 30 times for each value once a day. So thats 120000 rows. I will be doing quite complicated queries on these rows. But the main thing is I will always filter by value first so SELECT * WHERE value = 'N' etc. That will ALWAYS be used. Now is it better to have one table where all 120k rows are stored? or 30 tables were 4k rows are stored? EDIT: the SQL database in question will be MySQL

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• how to profile my code??

  - by kaki

  i want to how to profile my code... i have gone through the docs , but as there were no example codes given i could not get anything from it. i have a large code and it is taking so much time hence want to profile and increase its speed. i havent written my code in method , there are few in between but not completely. i dont have any main in my code..i want to know how to use profiling.. looking for some example or sample code of about how to profile.. i tried psyco i.e just addded two line at the top of my code import psyco psyco.full() is this write,it did not show any improvement. and other way of speeding up ,please suggest. thanks in advance..

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• Optimize date query for large child tables: GiST or GIN?

  - by Dave Jarvis

  Problem 72 child tables, each having a year index and a station index, are defined as follows: CREATE TABLE climate.measurement_12_013 ( -- Inherited from table climate.measurement_12_013: id bigint NOT NULL DEFAULT nextval('climate.measurement_id_seq'::regclass), -- Inherited from table climate.measurement_12_013: station_id integer NOT NULL, -- Inherited from table climate.measurement_12_013: taken date NOT NULL, -- Inherited from table climate.measurement_12_013: amount numeric(8,2) NOT NULL, -- Inherited from table climate.measurement_12_013: category_id smallint NOT NULL, -- Inherited from table climate.measurement_12_013: flag character varying(1) NOT NULL DEFAULT ' '::character varying, CONSTRAINT measurement_12_013_category_id_check CHECK (category_id = 7), CONSTRAINT measurement_12_013_taken_check CHECK (date_part('month'::text, taken)::integer = 12) ) INHERITS (climate.measurement) CREATE INDEX measurement_12_013_s_idx ON climate.measurement_12_013 USING btree (station_id); CREATE INDEX measurement_12_013_y_idx ON climate.measurement_12_013 USING btree (date_part('year'::text, taken)); (Foreign key constraints to be added later.) The following query runs abysmally slow due to a full table scan: SELECT count(1) AS measurements, avg(m.amount) AS amount FROM climate.measurement m WHERE m.station_id IN ( SELECT s.id FROM climate.station s, climate.city c WHERE -- For one city ... -- c.id = 5182 AND -- Where stations are within an elevation range ... -- s.elevation BETWEEN 0 AND 3000 AND 6371.009 * SQRT( POW(RADIANS(c.latitude_decimal - s.latitude_decimal), 2) + (COS(RADIANS(c.latitude_decimal + s.latitude_decimal) / 2) * POW(RADIANS(c.longitude_decimal - s.longitude_decimal), 2)) ) <= 50 ) AND -- -- Begin extracting the data from the database. -- -- The data before 1900 is shaky; insufficient after 2009. -- extract( YEAR FROM m.taken ) BETWEEN 1900 AND 2009 AND -- Whittled down by category ... -- m.category_id = 1 AND m.taken BETWEEN -- Start date. (extract( YEAR FROM m.taken )||'-01-01')::date AND -- End date. Calculated by checking to see if the end date wraps -- into the next year. If it does, then add 1 to the current year. -- (cast(extract( YEAR FROM m.taken ) + greatest( -1 * sign( (extract( YEAR FROM m.taken )||'-12-31')::date - (extract( YEAR FROM m.taken )||'-01-01')::date ), 0 ) AS text)||'-12-31')::date GROUP BY extract( YEAR FROM m.taken ) The sluggishness comes from this part of the query: m.taken BETWEEN /* Start date. */ (extract( YEAR FROM m.taken )||'-01-01')::date AND /* End date. Calculated by checking to see if the end date wraps into the next year. If it does, then add 1 to the current year. */ (cast(extract( YEAR FROM m.taken ) + greatest( -1 * sign( (extract( YEAR FROM m.taken )||'-12-31')::date - (extract( YEAR FROM m.taken )||'-01-01')::date ), 0 ) AS text)||'-12-31')::date The HashAggregate from the plan shows a cost of 10006220141.11, which is, I suspect, on the astronomically huge side. There is a full table scan on the measurement table (itself having neither data nor indexes) being performed. The table aggregates 237 million rows from its child tables. Question What is the proper way to index the dates to avoid full table scans? Options I have considered: GIN GiST Rewrite the WHERE clause Separate year_taken, month_taken, and day_taken columns to the tables What are your thoughts? Thank you!

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• mysql subselect alternative

  - by Arnold

  Hi, Lets say I am analyzing how high school sports records affect school attendance. So I have a table in which each row corresponds to a high school basketball game. Each game has an away team id and a home team id (FK to another "team table") and a home score and an away score and a date. I am writing a query that matches attendance with this seasons basketball games. My sample output will be (#_students_missed_class, day_of_game, home_team, away_team, home_team_wins_this_season, away_team_wins_this_season) I now want to add how each team did the previous season to my analysis. Well, I have their previous season stored in the game table but i should be able to accomplish that with a subselect. So in my main select statement I add the subselect: SELECT COUNT(*) FROM game_table WHERE game_table.date BETWEEN 'start of previous season' AND 'end of previous season' AND ( (game_table.home_team = team_table.id AND game_table.home_score > game_table.away_score) OR (game_table.away_team = team_table.id AND game_table.away_score > game_table.home_score)) In this case team-table.id refers to the id of the home_team so I now have all their wins calculated from the previous year. This method of calculation is neither time nor resource intensive. The Explain SQL shows that I have ALL in the Type field and I am not using a Key and the query times out. I'm not sure how I can accomplish a more efficient query with a subselect. It seems proposterously inefficient to have to write 4 of these queries (for home wins, home losses, away wins, away losses). I am sure this could be more lucid. I'll absolutely add color tomorrow if anyone has questions

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• gcc memory alignment pragma

  - by aaa

  hello. Does gcc have memory alignment pragma, akin #pragma vector aligned in Intel compiler? I would like to tell compiler to optimize particular loop using aligned loads/store instructions. Thanks

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• Complicated idea - how to create car racing for my RPG game's players

  - by Donator

  So, I want to create car racing for my RPG game's players. Player can create race and choose how many participants can participate in race. After race is being created, other people can join it. When the maximum participants are collected, race begins. My idea, when the last participant joins, then instantly choose the winner (who's car is the best, that person wins), but how can I do it? If I choose to pick the winner after the last participant joins, then I have to put many queries in one page (select data from table, then delete the race, then select players' cars' statistics and pick the winner and then again, using mysql, send message to everyone). But this idea is really not optimal and it will lag cruelly for that last person. Maybe you have any ideas how I can avoid lag and make it more optimal. Thank you very much.

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• What is the best algorithm for this array-comparison problem?

  - by mark

  What is the most efficient for speed algorithm to solve the following problem? Given 6 arrays, D1,D2,D3,D4,D5 and D6 each containing 6 numbers like: D1[0] = number D2[0] = number ...... D6[0] = number D1[1] = another number D2[1] = another number .... ..... .... ...... .... D1[5] = yet another number .... ...... .... Given a second array ST1, containing 1 number: ST1[0] = 6 Given a third array ans, containing 6 numbers: ans[0] = 3, ans[1] = 4, ans[2] = 5, ......ans[5] = 8 Using as index for the arrays D1,D2,D3,D4,D5 and D6, the number that goes from 0, to the number stored in ST1[0] minus one, in this example 6, so from 0 to 6-1, compare each res array against each D array My algorithm so far is: I tried to keep everything unlooped as much as possible. EML := ST1[0] //number contained in ST1[0] EML1 := 0 //start index for the arrays D While EML1 < EML if D1[ELM1] = ans[0] goto two if D2[ELM1] = ans[0] goto two if D3[ELM1] = ans[0] goto two if D4[ELM1] = ans[0] goto two if D5[ELM1] = ans[0] goto two if D6[ELM1] = ans[0] goto two ELM1 = ELM1 + 1 return 0 //If the ans[0] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers two: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[1] goto three if D2[ELM1] = ans[1] goto three if D3[ELM1] = ans[1] goto three if D4[ELM1] = ans[1] goto three if D5[ELM1] = ans[1] goto three if D6[ELM1] = ans[1] goto three ELM1 = ELM1 + 1 return 0 //If the ans[1] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers three: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[2] goto four if D2[ELM1] = ans[2] goto four if D3[ELM1] = ans[2] goto four if D4[ELM1] = ans[2] goto four if D5[ELM1] = ans[2] goto four if D6[ELM1] = ans[2] goto four ELM1 = ELM1 + 1 return 0 //If the ans[2] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers four: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[3] goto five if D2[ELM1] = ans[3] goto five if D3[ELM1] = ans[3] goto five if D4[ELM1] = ans[3] goto five if D5[ELM1] = ans[3] goto five if D6[ELM1] = ans[3] goto five ELM1 = ELM1 + 1 return 0 //If the ans[3] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers five: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[4] goto six if D2[ELM1] = ans[4] goto six if D3[ELM1] = ans[4] goto six if D4[ELM1] = ans[4] goto six if D5[ELM1] = ans[4] goto six if D6[ELM1] = ans[4] goto six ELM1 = ELM1 + 1 return 0 //If the ans[4] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers six: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[5] return 1 ////If the ans[1] number is not found in either D1[0-6]..... if D2[ELM1] = ans[5] return 1 which will then include ans[0-6] numbers return 1 if D3[ELM1] = ans[5] return 1 if D4[ELM1] = ans[5] return 1 if D5[ELM1] = ans[5] return 1 if D6[ELM1] = ans[5] return 1 ELM1 = ELM1 + 1 return 0 As language of choice, it would be pure c

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• c++ optimize array of ints

  - by a432511

  I have a 2D lookup table of int16_t. int16_t my_array[37][73] = {{**DATA HERE**}} I have a mixture of values that range from just above the range of int8_t to just below the range of int8_t and some of the values repeat themselves. I am trying to reduce the size of this lookup table. What I have done so far is split each int16_t value into two int8_t values to visualize the wasted bytes. int8_t part_1 = original_value >> 4; int8_t part_2 = original_value & 0x0000FFFF; // If the upper 4 bits of the original_value were empty if(part_1 == 0) wasted_bytes_count++; I can easily remove the zero value int8_t that are wasting a byte of space and I can also remove the duplicate values, but my question is how do I do remove those values while retaining the ability to lookup based on the two indices? I contemplated translating this into a 1D array and adding a number following each duplicated value that would represent the number of duplicates that were removed, but I am struggling with how I would then identify what is a lookup value and what is a duplicate count. Also, it is further complicated by stripping out the zero int8_t values that were wasted bytes. EDIT: This array is stored in ROM already. RAM is even more limited than ROM so it is already stored in ROM. EDIT: I am going to post a bounty for this question as soon as I can. I need a complete answer of how to store the information AND retrieve it. It does not need to be a 2D array as long as I can get the same values. EDIT: Adding the actual array below: {150,145,140,135,130,125,120,115,110,105,100,95,90,85,80,75,70,65,60,55,50,45,40,35,30,25,20,15,10,5,0,-4,-9,-14,-19,-24,-29,-34,-39,-44,-49,-54,-59,-64,-69,-74,-79,-84,-89,-94,-99,104,109,114,119,124,129,134,139,144,149,154,159,164,169,174,179,175,170,165,160,155,150}, \ {143,137,131,126,120,115,110,105,100,95,90,85,80,75,71,66,62,57,53,48,44,39,35,31,27,22,18,14,9,5,1,-3,-7,-11,-16,-20,-25,-29,-34,-38,-43,-47,-52,-57,-61,-66,-71,-76,-81,-86,-91,-96,101,107,112,117,123,128,134,140,146,151,157,163,169,175,178,172,166,160,154,148,143}, \ {130,124,118,112,107,101,96,92,87,82,78,74,70,65,61,57,54,50,46,42,38,34,31,27,23,19,16,12,8,4,1,-2,-6,-10,-14,-18,-22,-26,-30,-34,-38,-43,-47,-51,-56,-61,-65,-70,-75,-79,-84,-89,-94,100,105,111,116,122,128,135,141,148,155,162,170,177,174,166,159,151,144,137,130}, \ {111,104,99,94,89,85,81,77,73,70,66,63,60,56,53,50,46,43,40,36,33,30,26,23,20,16,13,10,6,3,0,-3,-6,-9,-13,-16,-20,-24,-28,-32,-36,-40,-44,-48,-52,-57,-61,-65,-70,-74,-79,-84,-88,-93,-98,103,109,115,121,128,135,143,152,162,172,176,165,154,144,134,125,118,111}, \ {85,81,77,74,71,68,65,63,60,58,56,53,51,49,46,43,41,38,35,32,29,26,23,19,16,13,10,7,4,1,-1,-3,-6,-9,-13,-16,-19,-23,-26,-30,-34,-38,-42,-46,-50,-54,-58,-62,-66,-70,-74,-78,-83,-87,-91,-95,100,105,110,117,124,133,144,159,178,160,141,125,112,103,96,90,85}, \ {62,60,58,57,55,54,52,51,50,48,47,46,44,42,41,39,36,34,31,28,25,22,19,16,13,10,7,4,2,0,-3,-5,-8,-10,-13,-16,-19,-22,-26,-29,-33,-37,-41,-45,-49,-53,-56,-60,-64,-67,-70,-74,-77,-80,-83,-86,-89,-91,-94,-97,101,105,111,130,109,84,77,74,71,68,66,64,62}, \ {46,46,45,44,44,43,42,42,41,41,40,39,38,37,36,35,33,31,28,26,23,20,16,13,10,7,4,1,-1,-3,-5,-7,-9,-12,-14,-16,-19,-22,-26,-29,-33,-36,-40,-44,-48,-51,-55,-58,-61,-64,-66,-68,-71,-72,-74,-74,-75,-74,-72,-68,-61,-48,-25,2,22,33,40,43,45,46,47,46,46}, \ {36,36,36,36,36,35,35,35,35,34,34,34,34,33,32,31,30,28,26,23,20,17,14,10,6,3,0,-2,-4,-7,-9,-10,-12,-14,-15,-17,-20,-23,-26,-29,-32,-36,-40,-43,-47,-50,-53,-56,-58,-60,-62,-63,-64,-64,-63,-62,-59,-55,-49,-41,-30,-17,-4,6,15,22,27,31,33,34,35,36,36}, \ {30,30,30,30,30,30,30,29,29,29,29,29,29,29,29,28,27,26,24,21,18,15,11,7,3,0,-3,-6,-9,-11,-12,-14,-15,-16,-17,-19,-21,-23,-26,-29,-32,-35,-39,-42,-45,-48,-51,-53,-55,-56,-57,-57,-56,-55,-53,-49,-44,-38,-31,-23,-14,-6,0,7,13,17,21,24,26,27,29,29,30}, \ {25,25,26,26,26,25,25,25,25,25,25,25,25,26,25,25,24,23,21,19,16,12,8,4,0,-3,-7,-10,-13,-15,-16,-17,-18,-19,-20,-21,-22,-23,-25,-28,-31,-34,-37,-40,-43,-46,-48,-49,-50,-51,-51,-50,-48,-45,-42,-37,-32,-26,-19,-13,-7,-1,3,7,11,14,17,19,21,23,24,25,25}, \ {21,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,21,20,18,16,13,9,5,1,-3,-7,-11,-14,-17,-18,-20,-21,-21,-22,-22,-22,-23,-23,-25,-27,-29,-32,-35,-37,-40,-42,-44,-45,-45,-45,-44,-42,-40,-36,-32,-27,-22,-17,-12,-7,-3,0,3,7,9,12,14,16,18,19,20,21,21}, \ {18,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,18,17,16,14,10,7,2,-1,-6,-10,-14,-17,-19,-21,-22,-23,-24,-24,-24,-24,-23,-23,-23,-24,-26,-28,-30,-33,-35,-37,-38,-39,-39,-38,-36,-34,-31,-28,-24,-19,-15,-10,-6,-3,0,1,4,6,8,10,12,14,15,16,17,18,18}, \ {16,16,17,17,17,17,17,17,17,17,17,16,16,16,16,16,16,15,13,11,8,4,0,-4,-9,-13,-16,-19,-21,-23,-24,-25,-25,-25,-25,-24,-23,-21,-20,-20,-21,-22,-24,-26,-28,-30,-31,-32,-31,-30,-29,-27,-24,-21,-17,-13,-9,-6,-3,-1,0,2,4,5,7,9,10,12,13,14,15,16,16}, \ {14,14,14,15,15,15,15,15,15,15,14,14,14,14,14,14,13,12,11,9,5,2,-2,-6,-11,-15,-18,-21,-23,-24,-25,-25,-25,-25,-24,-22,-21,-18,-16,-15,-15,-15,-17,-19,-21,-22,-24,-24,-24,-23,-22,-20,-18,-15,-12,-9,-5,-3,-1,0,1,2,4,5,6,8,9,10,11,12,13,14,14}, \ {12,13,13,13,13,13,13,13,13,13,13,13,12,12,12,12,11,10,9,6,3,0,-4,-8,-12,-16,-19,-21,-23,-24,-24,-24,-24,-23,-22,-20,-17,-15,-12,-10,-9,-9,-10,-12,-13,-15,-17,-17,-18,-17,-16,-15,-13,-11,-8,-5,-3,-1,0,1,1,2,3,4,6,7,8,9,10,11,12,12,12}, \ {11,11,11,11,11,12,12,12,12,12,11,11,11,11,11,10,10,9,7,5,2,-1,-5,-9,-13,-17,-20,-22,-23,-23,-23,-23,-22,-20,-18,-16,-14,-11,-9,-6,-5,-4,-5,-6,-8,-9,-11,-12,-12,-12,-12,-11,-9,-8,-6,-3,-1,0,0,1,1,2,3,4,5,6,7,8,9,10,11,11,11}, \ {10,10,10,10,10,10,10,10,10,10,10,10,10,10,9,9,9,7,6,3,0,-3,-6,-10,-14,-17,-20,-21,-22,-22,-22,-21,-19,-17,-15,-13,-10,-8,-6,-4,-2,-2,-2,-2,-4,-5,-7,-8,-8,-9,-8,-8,-7,-5,-4,-2,0,0,1,1,1,2,2,3,4,5,6,7,8,9,10,10,10}, \ {9,9,9,9,9,9,9,10,10,9,9,9,9,9,9,8,8,6,5,2,0,-4,-7,-11,-15,-17,-19,-21,-21,-21,-20,-18,-16,-14,-12,-10,-8,-6,-4,-2,-1,0,0,0,-1,-2,-4,-5,-5,-6,-6,-5,-5,-4,-3,-1,0,0,1,1,1,1,2,3,3,5,6,7,8,8,9,9,9}, \ {9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,8,7,5,4,1,-1,-5,-8,-12,-15,-17,-19,-20,-20,-19,-18,-16,-14,-11,-9,-7,-5,-4,-2,-1,0,0,1,1,0,0,-2,-3,-3,-4,-4,-4,-3,-3,-2,-1,0,0,0,0,0,1,1,2,3,4,5,6,7,8,8,9,9}, \ {9,9,9,8,8,8,9,9,9,9,9,8,8,8,8,7,6,5,3,0,-2,-5,-9,-12,-15,-17,-18,-19,-19,-18,-16,-14,-12,-9,-7,-5,-4,-2,-1,0,0,1,1,1,1,0,0,-1,-2,-2,-3,-3,-2,-2,-1,-1,0,0,0,0,0,0,0,1,2,3,4,5,6,7,8,8,9}, \ {8,8,8,8,8,8,9,9,9,9,9,9,8,8,8,7,6,4,2,0,-3,-6,-9,-12,-15,-17,-18,-18,-17,-16,-14,-12,-10,-8,-6,-4,-2,-1,0,0,1,2,2,2,2,1,0,0,-1,-1,-1,-2,-2,-1,-1,0,0,0,0,0,0,0,0,0,1,2,3,4,5,6,7,8,8}, \ {8,8,8,8,9,9,9,9,9,9,9,9,9,8,8,7,5,3,1,-1,-4,-7,-10,-13,-15,-16,-17,-17,-16,-15,-13,-11,-9,-6,-5,-3,-2,0,0,0,1,2,2,2,2,1,1,0,0,0,-1,-1,-1,-1,-1,0,0,0,0,-1,-1,-1,-1,-1,0,0,1,3,4,5,7,7,8}, \ {8,8,9,9,9,9,10,10,10,10,10,10,10,9,8,7,5,3,0,-2,-5,-8,-11,-13,-15,-16,-16,-16,-15,-13,-12,-10,-8,-6,-4,-2,-1,0,0,1,2,2,3,3,2,2,1,0,0,0,0,0,0,0,0,0,0,-1,-1,-2,-2,-2,-2,-2,-1,0,0,1,3,4,6,7,8}, \ {7,8,9,9,9,10,10,11,11,11,11,11,10,10,9,7,5,3,0,-2,-6,-9,-11,-13,-15,-16,-16,-15,-14,-13,-11,-9,-7,-5,-3,-2,0,0,1,1,2,3,3,3,3,2,2,1,1,0,0,0,0,0,0,0,-1,-1,-2,-3,-3,-4,-4,-4,-3,-2,-1,0,1,3,5,6,7}, \ {6,8,9,9,10,11,11,12,12,12,12,12,11,11,9,7,5,2,0,-3,-7,-10,-12,-14,-15,-16,-15,-15,-13,-12,-10,-8,-7,-5,-3,-1,0,0,1,2,2,3,3,4,3,3,3,2,2,1,1,1,0,0,0,0,-1,-2,-3,-4,-4,-5,-5,-5,-5,-4,-2,-1,0,2,3,5,6}, \ {6,7,8,10,11,12,12,13,13,14,14,13,13,11,10,8,5,2,0,-4,-8,-11,-13,-15,-16,-16,-16,-15,-13,-12,-10,-8,-6,-5,-3,-1,0,0,1,2,3,3,4,4,4,4,4,3,3,3,2,2,1,1,0,0,-1,-2,-3,-5,-6,-7,-7,-7,-6,-5,-4,-3,-1,0,2,4,6}, \ {5,7,8,10,11,12,13,14,15,15,15,14,14,12,11,8,5,2,-1,-5,-9,-12,-14,-16,-17,-17,-16,-15,-14,-12,-11,-9,-7,-5,-3,-1,0,0,1,2,3,4,4,5,5,5,5,5,5,4,4,3,3,2,1,0,-1,-2,-4,-6,-7,-8,-8,-8,-8,-7,-6,-4,-2,0,1,3,5}, \ {4,6,8,10,12,13,14,15,16,16,16,16,15,13,11,9,5,2,-2,-6,-10,-13,-16,-17,-18,-18,-17,-16,-15,-13,-11,-9,-7,-5,-4,-2,0,0,1,3,3,4,5,6,6,7,7,7,7,7,6,5,4,3,2,0,-1,-3,-5,-7,-8,-9,-10,-10,-10,-9,-7,-5,-4,-1,0,2,4}, \ {4,6,8,10,12,14,15,16,17,18,18,17,16,15,12,9,5,1,-3,-8,-12,-15,-18,-19,-20,-20,-19,-18,-16,-15,-13,-11,-8,-6,-4,-2,-1,0,1,3,4,5,6,7,8,9,9,9,9,9,9,8,7,5,3,1,-1,-3,-6,-8,-10,-11,-12,-12,-11,-10,-9,-7,-5,-2,0,1,4}, \ {4,6,8,11,13,15,16,18,19,19,19,19,18,16,13,10,5,0,-5,-10,-15,-18,-21,-22,-23,-22,-22,-20,-18,-17,-14,-12,-10,-8,-5,-3,-1,0,1,3,5,6,8,9,10,11,12,12,13,12,12,11,9,7,5,2,0,-3,-6,-9,-11,-12,-13,-13,-12,-11,-10,-8,-6,-3,-1,1,4}, \ {3,6,9,11,14,16,17,19,20,21,21,21,19,17,14,10,4,-1,-8,-14,-19,-22,-25,-26,-26,-26,-25,-23,-21,-19,-17,-14,-12,-9,-7,-4,-2,0,1,3,5,7,9,11,13,14,15,16,16,16,16,15,13,10,7,4,0,-3,-7,-10,-12,-14,-15,-14,-14,-12,-11,-9,-6,-4,-1,1,3}, \ {4,6,9,12,14,17,19,21,22,23,23,23,21,19,15,9,2,-5,-13,-20,-25,-28,-30,-31,-31,-30,-29,-27,-25,-22,-20,-17,-14,-11,-9,-6,-3,0,1,4,6,9,11,13,15,17,19,20,21,21,21,20,18,15,11,6,2,-2,-7,-11,-13,-15,-16,-16,-15,-13,-11,-9,-7,-4,-1,1,4}, \ {4,7,10,13,15,18,20,22,24,25,25,25,23,20,15,7,-2,-12,-22,-29,-34,-37,-38,-38,-37,-36,-34,-31,-29,-26,-23,-20,-17,-13,-10,-7,-4,-1,2,5,8,11,13,16,18,21,23,24,26,26,26,26,24,21,17,12,5,0,-6,-10,-14,-16,-16,-16,-15,-14,-12,-10,-7,-4,-1,1,4}, \ {4,7,10,13,16,19,22,24,26,27,27,26,24,19,11,-1,-15,-28,-37,-43,-46,-47,-47,-45,-44,-41,-39,-36,-32,-29,-26,-22,-19,-15,-11,-8,-4,-1,2,5,9,12,15,19,22,24,27,29,31,33,33,33,32,30,26,21,14,6,0,-6,-11,-14,-15,-16,-15,-14,-12,-9,-7,-4,-1,1,4}, \ {6,9,12,15,18,21,23,25,27,28,27,24,17,4,-14,-34,-49,-56,-60,-60,-60,-58,-56,-53,-50,-47,-43,-40,-36,-32,-28,-25,-21,-17,-13,-9,-5,-1,2,6,10,14,17,21,24,28,31,34,37,39,41,42,43,43,41,38,33,25,17,8,0,-4,-8,-10,-10,-10,-8,-7,-4,-2,0,3,6}, \ {22,24,26,28,30,32,33,31,23,-18,-81,-96,-99,-98,-95,-93,-89,-86,-82,-78,-74,-70,-66,-62,-57,-53,-49,-44,-40,-36,-32,-27,-23,-19,-14,-10,-6,-1,2,6,10,15,19,23,27,31,35,38,42,45,49,52,55,57,60,61,63,63,62,61,57,53,47,40,33,28,23,21,19,19,19,20,22}, \ {168,173,178,176,171,166,161,156,151,146,141,136,131,126,121,116,111,106,101,-96,-91,-86,-81,-76,-71,-66,-61,-56,-51,-46,-41,-36,-31,-26,-21,-16,-11,-6,-1,3,8,13,18,23,28,33,38,43,48,53,58,63,68,73,78,83,88,93,98,103,108,113,118,123,128,133,138,143,148,153,158,163,168}, \ Thanks for your time.

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• How to use constraint programming for optimizing shopping baskets?

  - by tangens

  I have a list of items I want to buy. The items are offered by different shops and different prices. The shops have individual delivery costs. I'm looking for an optimal shopping strategy (and a java library supporting it) to purchase all of the items with a minimal total price. Example: Item1 is offered at Shop1 for $100, at Shop2 for $111. Item2 is offered at Shop1 for $90, at Shop2 for $85. Delivery cost of Shop1: $10 if total order < $150; $0 otherwise Delivery cost of Shop2: $5 if total order < $50; $0 otherwise If I buy Item1 and Item2 at Shop1 the total cost is $100 + $90 +$0 = $190. If I buy Item1 and Item2 at Shop2 the total cost is $111 + $85 +$0 = $196. If I buy Item1 at Shop1 and Item2 at Shop2 the total cost is $100 + $10 + $85 + $0 = 195. I get the minimal price if I order Item1 and Item2 at Shop1: $190 What I tried so far I asked another question before that led me to the field of constraint programming. I had a look at cream and choco, but I did not figure out how to create a model to solve my problem. | shop1 | shop2 | shop3 | ... ----------------------------------------- item1 | p11 | p12 | p13 | item2 | p21 | p22 | p23 | . | | | | . | | | | ----------------------------------------- shipping | s1 | s2 | s3 | limit | l1 | l2 | l3 | ----------------------------------------- total | t1 | t2 | t3 | ----------------------------------------- My idea was to define these constraints: each price "p xy" is defined in the domain (0, c) where c is the price of the item in this shop only one price in a line should be non zero if one or more items are bought from one shop and the sum of the prices is lower than limit, then add shipping cost to the total cost shop total cost is the sum of the prices of all items in a shop total cost is the sum of all shop totals The objective is "total cost". I want to minimize this. In cream I wasn't able to express the "if then" constraint for conditional shipping costs. In choco these constraints exist, but even for 5 items and 10 shops the program was running for 10 minutes without finding a solution. Question How should I express my constraints to make this problem solvable for a constraint programming solver?

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• Good Starting Points for Optimizing Database Calls in Ruby on Rails?

  - by viatropos

  I have a menu in Rails which grabs a nested tree of Post models, each which have a Slug model associated via a polymorphic association (using the friendly_id gem for slugs and awesome_nested_set for the tree). The database output in development looks like this (here's the full gist): SQL (0.4ms) SELECT COUNT(*) AS count_id FROM "posts" WHERE ("posts".parent_id = 39) CACHE (0.0ms) SELECT "posts".* FROM "posts" WHERE ("posts"."id" = 13) LIMIT 1 CACHE (0.0ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 13 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 Slug Load (0.4ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 40 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 SQL (0.3ms) SELECT COUNT(*) AS count_id FROM "posts" WHERE ("posts".parent_id = 40) CACHE (0.0ms) SELECT "posts".* FROM "posts" WHERE ("posts"."id" = 13) LIMIT 1 CACHE (0.0ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 13 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 Slug Load (0.4ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 41 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 ... Rendered shared/_menu.html.haml (907.6ms) What are some quick things I should always do to optimize this from the start (easy things)? Some things I'm thinking now are: Can Rails 3 eager load the whole Post tree + associated Slugs in one DB call? Can I do that easily with named scopes or custom SQL? What is best practice in this situation? Not really thinking about memcached in this situation as that can be applied to much more than just this.

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• Can anyone recommend a decent tool for optimizing images other than Photoshop

  - by toomanyairmiles

  Can anyone recommend a decent tool for optimising images other than adobe photoshop, the gimp etc? I'm looking to optimise images for the web preferably online and free. Basically I have a client who can't install additional software on their work PC but needs to optimise photographs and other images for their website and is presently uploading 1 or 2 Mb files. On a personal level I'm interested to see what other people are using...

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• Database indexes - what should they be

  - by WebweaverD

  Most of my database tables have a clear unique index through which lookups are done 90% of the time but I am a bit unsure on this one - I have a table which keeps track of user rating totals for items in my database, I now want to add another table, to track individual ratings with an ip address column to make sure no one can rate something twice. Since I can see this becoming a big, high use table it is important to optimize it correctly. (MYSQL table) This table will have the following fields: rating_id(always - unique), item_id (always - not unique), user_id (optional - not unique), ip_address (always - not unique), rating_value(always - not unique), has_review(bool) Now I envisions 90% the queries going something like this: When a user rates something - select where item_id = x and ip_address = y, (if rows = 0) insert rating When in user account pages - select where ip_address = x or username = y Now none of the fields searched on are unique, can I still use them as indexes (for example item _id and ip_address), can I have two indexes and will this still improve performance over a non indexed table?

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• PHP Increasing write to page speed.

  - by Frederico

  I'm currently writing out xml and have done the following: header ("content-type: text/xml"); header ("content-length: ".strlen($xml)); $xml being the xml to be written out. I'm near about 1.8 megs of text (which I found via firebug), it seems as the writing is taking more time than the script to run.. is there a way to increase this write speed? Thank you in advance.

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• Memory efficient int-int dict in Python

  - by Bolo

  Hi, I need a memory efficient int-int dict in Python that would support the following operations in O(log n) time: d[k] = v # replace if present v = d[k] # None or a negative number if not present I need to hold ~250M pairs, so it really has to be tight. Do you happen to know a suitable implementation (Python 2.7)? EDIT Removed impossible requirement and other nonsense. Thanks, Craig and Kylotan! To rephrase. Here's a trivial int-int dictionary with 1M pairs: >>> import random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> d = {} >>> for _ in xrange(1000000): ... d[random.randint(0, sys.maxint)] = random.randint(0, sys.maxint) ... >>> h.heap() Partition of a set of 1999530 objects. Total size = 49161112 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 0 25165960 51 25165960 51 dict (no owner) 1 1999521 100 23994252 49 49160212 100 int On average, a pair of integers uses 49 bytes. Here's an array of 2M integers: >>> import array, random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> a = array.array('i') >>> for _ in xrange(2000000): ... a.append(random.randint(0, sys.maxint)) ... >>> h.heap() Partition of a set of 14 objects. Total size = 8001108 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 7 8000028 100 8000028 100 array.array On average, a pair of integers uses 8 bytes. I accept that 8 bytes/pair in a dictionary is rather hard to achieve in general. Rephrased question: is there a memory-efficient implementation of int-int dictionary that uses considerably less than 49 bytes/pair?

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• How efficient is PHP's substr?

  - by zildjohn01

  I'm writing a parser in PHP which must be able to handle large in-memory strings, so this is a somewhat important issue. (ie, please don't "premature optimize" flame me, please) How does the substr function work? Does it make a second copy of the string data in memory, or does it reference the original? Should I worry about calling, for example, $str = substr($str, 1); in a loop?

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• How to optimise MySQL query containing a subquery?

  - by aidan

  I have two tables, House and Person. For any row in House, there can be 0, 1 or many corresponding rows in Person. But, of those people, a maximum of one will have a status of "ACTIVE", the others will all have a status of "CANCELLED". e.g. SELECT * FROM House LEFT JOIN Person ON House.ID = Person.HouseID House.ID | Person.ID | Person.Status 1 | 1 | CANCELLED 1 | 2 | CANCELLED 1 | 3 | ACTIVE 2 | 1 | ACTIVE 3 | NULL | NULL 4 | 4 | CANCELLED I want to filter out the cancelled rows, and get something like this: House.ID | Person.ID | Person.Status 1 | 3 | ACTIVE 2 | 1 | ACTIVE 3 | NULL | NULL 4 | NULL | NULL I've achieved this with the following sub select: SELECT * FROM House LEFT JOIN ( SELECT * FROM Person WHERE Person.Status != "CANCELLED" ) Person ON House.ID = Person.HouseID ...which works, but breaks all the indexes. Is there a better solution that doesn't? I'm using MySQL and all relevant columns are indexed. EXPLAIN lists nothing in possible_keys. Thanks.

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• How to include NetBeans Platform Source code into module dependencies

  - by Ben Hammond

  I am debugging a NetBeans Platform application. I have downloaded the NetBeans Platform source code .zip file. I would really really like to attach the source code to the debugger so that I can seamlessly jump to internal NB source code. Normally I would edit the Library configuration to tell NB where to find the source code, and it would just work. However this is not possible for NetBeans Modules; when I look at the Utilities API module dependency it does not look like a normal NB library and there is nowhere to add in the source code. I suspect that if I were to rebuild my project using Maven this would work automatically. But thats a terrible reason to switch to maven. How can I get the NB Platform Source code included into my Module Dependencies ?

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• help optimize sql query

  - by msony

  I have tracking table tbl_track with id, session_id, created_date fields I need count unique session_id for one day here what i got: select count(0) from ( select distinct session_id from tbl_track where created_date between getdate()-1 and getdate() group by session_id )tbl im feeling that it could be better solution for it

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• jQuery - Multiple selectors & multiple values in ONE call

  - by ozke

  Hi, I was wondering whether there's a way of using multiple selectors in jQuery and setting different values for them IN ONE CALL. E.g.: $(selector1, selector2, selector3, ...).css({left:[532, 112, 453, ...]}); Thanks in advance

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• Does the .NET CLR Really Optimize for the Current Processor

  - by dewald

  When I read about the performance of JITted languages like C# or Java, authors usually say that they should/could theoretically outperform many native-compiled applications. The theory being that native applications are usually just compiled for a processor family (like x86), so the compiler cannot make certain optimizations as they may not truly be optimizations on all processors. On the other hand, the CLR can make processor-specific optimizations during the JIT process. Does anyone know if Microsoft's (or Mono's) CLR actually performs processor-specific optimizations during the JIT process? If so, what kind of optimizations?

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• The best way to implement drawing features like Keynote

  - by Shamseddine

  Hi all, I'm trying to make a little iPad tool's for drawing simple geometrical objects (rect, rounded rect, ellipse, star, ...). My goal is to make something very close to Keynote (drawing feature), i.e. let the user add a rect (for instance), resizing it and moving it. I want too the user can select many objects and move them together. I've thought about at least 3 differents ways to do that : Extends UIView for each object type, a class for Rect, another for Ellipse, ... With custom drawing method. Then add this view as subview of the global view. Extends CALayer for each object type, a class for Rect, another for Ellipse, ... With custom drawing method. Then add this layer as sublayer of the global view layer's. Extends NSObject for each object type, a class for Rect, another for Ellipse, ... With just a drawing method which will get as argument a CGContext and a Rect and draw directly the form in it. Those methods will be called by the drawing method of the global view. I'm aware that the two first ways come with functions to detect touch on each object, to add easily shadows,... but I'm afraid that they are a little too heavy ? That's why I thought about the last way, which it seems to be straight forward. Which way will be the more efficient ??? Or maybe I didn't thought another way ? Any help will be appreciated ;-) Thanks.

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• Is it better to echo javascript in raw format with php, or echo a script include that has been minif

  - by Scarface

  Hey guys quick question, I am currently echoing a lot of javascript that is based conditionally on login status and other variables. I was wondering if it would be better to simply echo the script include like <script type="text/javascript" src="javascript/openlogin.js"></script> that has been run through a minifying program and been gzipped or to echo the full script in raw format. The latter suggestion is messier to me but it reduces http requests while the latter would probably be smaller but take more cpu? Just wondering what some other people think. Thanks in advance for any advice.

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• SEO for Ultraseek 5.7

  - by Adam N

  We've got Ultraseek 5.7 indexing the content on our corporate intranet site, and we'd like to make sure our web pages are being optimized for it. Which SEO techniques are useful for Ultraseek, and where can I find documentation about these features? Features I've considered implementing: Make the title and first H1 contain the most valuable information about the page Implement a sitemap.xml file Ping the Ultraseek xpa interface when new content is added Use "SEO-Friendly" URL strings Add Meta keywords to the HTML pages.

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