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Capital district and departments of Colombia Distrito Capital y los Departamentos de Colombia (Spanish)
Clash Royale CLAN TAG #URR8PPP Executable numpy error I'm trying to create an executable file for my code. I've already tried with cx_Freeze and with pyinstaller. Both gives me the same error, which is: "Missing required dependencies 0.format(missing_dependencies))" PS C:UsersGustavoDesktopbuildexe.win32-3.6> python AgendaOficial.py C:UsersGustavoAppDataLocalProgramsPythonPython36-32python.exe: can't open file 'AgendaOficial.py': [Errno 2] No such file or directory PS C:UsersGustavoDesktopbuildexe.win32-3.6> .AgendaOficial.exe Traceback (most recent call last): File "C:UsersGustavoAppDataLocalProgramsPythonPython36-32libsite-packagescx_Freezeinitscripts__startup__.py", line 14, in run module.run() File "C:UsersGustavoAppDataLocalProgramsPythonPython36-32libsite-packagescx_FreezeinitscriptsConsole.py", line 26, in run exec(code, m. dict ) File "AgendaOficial.py", line 8, in File "C:UsersGustavoAppDataLocal...
Clash Royale CLAN TAG #URR8PPP Hystrix command on request collapser fallback I have a scenario where I want to apply hystrix on the fallback (and process one-by-one) of a hystrix request collapser's batch method. The fallback method ( processEntryBatch_fallback ) is invoked. But the hystrix command ( processEntryBackup ) in turn the fallback invokes is not reported (doesn't even appear on dashboard). And the fallback method ( finalFallback ) is not invoked either. I would like to know what am I missing here ? I referred javanica documentation processEntryBatch_fallback processEntryBackup finalFallback @Service public class DummyService private static final Logger log = LoggerFactory.getLogger(DummyService.class); //batch processing method public void processEntry(List<String> msg) //batch processing throw new RuntimeException("Exception while batch processing"); //processing one-by-one @HystrixCommand(fallbackMethod="finalFallback") public ...
Clash Royale CLAN TAG #URR8PPP PySpark count values by condition I have a DataFrame, a snippet here: [['u1', 1], ['u2', 0]] basically one string ('f') and either a 1 or a 0 for second element ('is_fav'). What I need to do is grouping on the first field and counting the occurrences of 1s and 0s. I was hoping to do something like num_fav = count((col("is_fav") == 1)).alias("num_fav") num_nonfav = count((col("is_fav") == 0)).alias("num_nonfav") df.groupBy("f").agg(num_fav, num_nonfav) It does not work properly, I get in both cases the same result which amounts to the count for the items in the group, so the filter (whether it is a 1 or a 0) seems to be ignored. Does this depend on how count works? count 1 Answer 1 There is no filter here. Both col("is_fav") == 1 and col("is_fav") == 0) are just boolean expressions and count doesn't really care about their value as long a...
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