I am running on following config:
Cluster type: E64_v3 (1 driver + 3 workers)
other spark cnfigs:
spark.shuffle.io.connectionTimeout 1200s
spark.databricks.io.cache.maxMetaDataCache 40g
spark.rpc.askTimeout 1200s
spark.databricks.delta.snapshotPartitions 576
spark.databricks.optimizer.rangeJoin.binSize 256
spark.sql.inMemoryColumnarStorage.batchSize 10000
spark.sql.legacy.parquet.datetimeRebaseModeInWrite CORRECTED
spark.executor.cores 16
spark.executor.memory 54g
spark.rpc.lookupTimeout 1200s
spark.driver.maxResultSize 220g
spark.databricks.io.cache.enabled true
spark.rpc.io.backLog 256
spark.sql.shuffle.partitions 576
spark.network.timeout 1200s
spark.sql.inMemoryColumnarStorage.compressed true
spark.databricks.io.cache.maxDiskUsage 220g
spark.storage.blockManagerSlaveTimeoutMs 1200s
spark.executor.instances 12
spark.sql.windowExec.buffer.in.memory.threshold 524288
spark.executor.heartbeatInterval 100s
spark.default.parallelism 576
spark.core.connection.ack.wait.timeout 1200s
and this is my error stack:
---> 41 df.write.format("delta").mode("overwrite").save(path)
/databricks/spark/python/pyspark/sql/readwriter.py in save(self, path, format, mode, partitionBy, **options)
825 self._jwrite.save()
826 else:
--> 827 self._jwrite.save(path)
Py4JJavaError: An error occurred while calling o784.save.
: org.apache.spark.SparkException: Job aborted.
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:230)
.
.
.
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 13 (execute at DeltaInvariantCheckerExec.scala:88) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Failed to connect to /10.179....
Any idea how to mitigate this?
Related
When using AlphaFold Colab (https://colab.research.google.com/github/deepmind/alphafold/blob/main/notebooks/AlphaFold.ipynb), I am getting the following error on step 4 ("Search against genetic databases"):
printscreen of error message
KeyError Traceback (most recent call last)
<ipython-input-12-a4ead9510dc9> in <module>
145 for db_name, db_results in raw_msa_results.items():
146 merged_msa = notebook_utils.merge_chunked_msa(
--> 147 results=db_results, max_hits=MAX_HITS.get(db_name))
148 if merged_msa.sequences and db_name != 'uniprot':
149 single_chain_msas.append(merged_msa)
1 frames
/opt/conda/lib/python3.7/site-packages/alphafold/notebooks/notebook_utils.py in merge_chunked_msa(results, max_hits)
105 e_values_dict = parsers.parse_e_values_from_tblout(chunk['tbl'])
106 # Jackhmmer lists sequences as <sequence name>/<residue from>-<residue to>.
--> 107 e_values = [e_values_dict[t.partition('/')[0]] for t in msa.descriptions]
108 chunk_results = zip(
109 msa.sequences, msa.deletion_matrix, msa.descriptions, e_values)
/opt/conda/lib/python3.7/site-packages/alphafold/notebooks/notebook_utils.py in <listcomp>(.0)
105 e_values_dict = parsers.parse_e_values_from_tblout(chunk['tbl'])
106 # Jackhmmer lists sequences as <sequence name>/<residue from>-<residue to>.
--> 107 e_values = [e_values_dict[t.partition('/')[0]] for t in msa.descriptions]
108 chunk_results = zip(
109 msa.sequences, msa.deletion_matrix, msa.descriptions, e_values)
KeyError: '0000|query')
Notably, this error seems to be dependent on the input sequence, because I get it with some sequences but not with others. I am using ColabPro and I have tried to tweak parameters like the amount of computing power but it did not help. I have never experienced this error before switching to ColabPro. Any help would be appreaciated.
i face the following error
2022-05-30 15:00:26,943 1940 WARNING ? odoo.service.server: Server memory limit (4934283264) reached.
2022-05-30 15:00:26,954 1940 INFO ? odoo.service.server: Dumping stacktrace of limit exceeding threads before reloading
2022-05-30 15:00:26,997 1940 INFO ? odoo.tools.misc:
# Thread: <_MainThread(MainThread, started 140592199739200)> (db:n/a) (uid:n/a) (url:n/a)
File: "/opt/odoo/odoo14/odoo-bin", line 8, in <module>
odoo.cli.main()
File: "/opt/odoo/odoo14/odoo/cli/command.py", line 61, in main
o.run(args)
File: "/opt/odoo/odoo14/odoo/cli/server.py", line 178, in run
main(args)
File: "/opt/odoo/odoo14/odoo/cli/server.py", line 172, in main
rc = odoo.service.server.start(preload=preload, stop=stop)
File: "/opt/odoo/odoo14/odoo/service/server.py", line 1298, in start
rc = server.run(preload, stop)
File: "/opt/odoo/odoo14/odoo/service/server.py", line 546, in run
dumpstacks(thread_idents=[thread.ident for thread in self.limits_reached_threads])
File: "/opt/odoo/odoo14/odoo/tools/misc.py", line 957, in dumpstacks
for line in extract_stack(stack):
2022-05-30 15:00:27,007 1940 INFO ? odoo.service.server: Initiating server reload
and i tried several solutions like increase
limit_request = 8192
limit_time_cpu = 600
limit_time_real = 1200
max_cron_threads = 1
limit_memory_hard = 536870637100
limit_memory_soft = 483183573400
but still facing same issue as error log, also i try to run the server after 30 mins as maximum i got same error again & again..
Best Regards.
Brother take a look at this link Configuration suggestions for Odoo server
If you have a VPS with 4 CPU cores and 16 GB of RAM, the number of workers should be 9 (CPU cores * 2 + 1), total limit-memory-soft value will be 640MB x 9 = 5760 MB , and total limit-memory-hard 768MB x 9 = 6912 MB,
so Odoo will use maximum 5.4 GB of RAM.
You server is 4vCPUs so try the below in your config file:
limit_memory_hard = 640MB * 9 * 1024 * 1024 = 7247757312
limit_memory_soft = 768MB * 9 * 1024 * 1024 = 6039797760
max_cron_threads = 1
workers = 8
How to deal with the error when using Gurobi with cvxpy ：AttributeError: Unable to retrieve attribute 'BarIterCount'.
I have an Integer programming problem, using cvxpy and set gurobi as a solver.
When the number of variables is small, the result is ok. After the number of variables reaches a level of like 43*13*6, then the error occurred. I suppose it may be caused by the scale of the problem, in which the gurobi solver can not estimate the BarIterCount, which is the max Iterations needed.
Thus, I wonder, is there any way to manually set the BarItercount attribute of gurobi through the interface of the CVX? Or whether there exists another way to solve this problem?
Thanks for any suggestions you may provide for me.
The trace log is as follows:
If my model is small, like I set a number which indicates the scale of model as 3, then the program is ok. The trace is :
Using license file D:\software\lib\site-packages\gurobipy\gurobi.lic
Restricted license - for non-production use only - expires 2022-01-13
Parameter OutputFlag unchanged
Value: 1 Min: 0 Max: 1 Default: 1
D:\software\lib\site-packages\cvxpy\reductions\solvers\solving_chain.py:326: DeprecationWarning: Deprecated, use Model.addMConstr() instead
solver_opts, problem._solver_cache)
Changed value of parameter QCPDual to 1
Prev: 0 Min: 0 Max: 1 Default: 0
Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 16 physical cores, 32 logical processors, using up to 32 threads
Optimize a model with 126 rows, 370 columns and 2689 nonzeros
Model fingerprint: 0x70d49530
Variable types: 0 continuous, 370 integer (369 binary)
Coefficient statistics:
Matrix range [1e+00, 7e+00]
Objective range [1e+00, 1e+00]
Bounds range [1e+00, 1e+00]
RHS range [1e+00, 6e+00]
Found heuristic solution: objective 7.0000000
Presolve removed 4 rows and 90 columns
Presolve time: 0.01s
Presolved: 122 rows, 280 columns, 1882 nonzeros
Variable types: 0 continuous, 280 integer (279 binary)
Root relaxation: objective 4.307692e+00, 216 iterations, 0.00 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 4.30769 0 49 7.00000 4.30769 38.5% - 0s
H 0 0 6.0000000 4.30769 28.2% - 0s
0 0 5.00000 0 35 6.00000 5.00000 16.7% - 0s
0 0 5.00000 0 37 6.00000 5.00000 16.7% - 0s
0 0 5.00000 0 7 6.00000 5.00000 16.7% - 0s
Cutting planes:
Gomory: 4
Cover: 9
MIR: 4
StrongCG: 1
GUB cover: 9
Zero half: 1
RLT: 1
Explored 1 nodes (849 simplex iterations) in 0.12 seconds
Thread count was 32 (of 32 available processors)
Solution count 2: 6 7
Optimal solution found (tolerance 1.00e-04)
Best objective 6.000000000000e+00, best bound 6.000000000000e+00, gap 0.0000%
If the number is 6, then error occurs:
-------------------------------------------------------
Using license file D:\software\lib\site-packages\gurobipy\gurobi.lic
Restricted license - for non-production use only - expires 2022-01-13
Parameter OutputFlag unchanged
Value: 1 Min: 0 Max: 1 Default: 1
D:\software\lib\site-packages\cvxpy\reductions\solvers\solving_chain.py:326: DeprecationWarning: Deprecated, use Model.addMConstr() instead
solver_opts, problem._solver_cache)
Changed value of parameter QCPDual to 1
Prev: 0 Min: 0 Max: 1 Default: 0
Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 16 physical cores, 32 logical processors, using up to 32 threads
Traceback (most recent call last):
File "model.py", line 274, in <module>
problem.solve(solver=cp.GUROBI,verbose=True)
File "D:\software\lib\site-packages\cvxpy\problems\problem.py", line 396, in solve
return solve_func(self, *args, **kwargs)
File "D:\software\lib\site-packages\cvxpy\problems\problem.py", line 754, in _solve
self.unpack_results(solution, solving_chain, inverse_data)
File "D:\software\lib\site-packages\cvxpy\problems\problem.py", line 1058, in unpack_results
solution = chain.invert(solution, inverse_data)
File "D:\software\lib\site-packages\cvxpy\reductions\chain.py", line 79, in invert
solution = r.invert(solution, inv)
File "D:\software\lib\site-packages\cvxpy\reductions\solvers\qp_solvers\gurobi_qpif.py", line 59, in invert
s.NUM_ITERS: model.BarIterCount,
File "src\gurobipy\model.pxi", line 343, in gurobipy.gurobipy.Model.__getattr__
File "src\gurobipy\model.pxi", line 1842, in gurobipy.gurobipy.Model.getAttr
File "src\gurobipy\attrutil.pxi", line 100, in gurobipy.gurobipy.__getattr
AttributeError: Unable to retrieve attribute 'BarIterCount'
Hopefully this can provide more hint for solution.
BarIterCount is the number of barrier iterations performed to solve an LP. This is not a limit on the number of iterations and it should only be queried when the current optimization process has been finished. You cannot set this attribute either, of course.
To actually limit the number of iterations the barrier algorithm is allowed to take, you can use the parameter BarIterLimit.
Please inspect your log file for further information about the solver's behavior.
I have a created a dataframe using spark.sql that has values like below:
obj_ds = spark.sql(obj_sql)
obj_ds.show(5)
+----------+-----------+-----------+
| obj_type| lat2| lon2|
+----------+-----------+-----------+
|prox_24hrs| -41.45012|147.0977983|
|prox_24hrs|-41.1914214| 146.337882|
|prox_24hrs|-41.1576422|146.1689051|
|prox_24hrs| -38.072615|145.3897115|
|prox_24hrs|-38.0641925|144.3400812|
+----------+-----------+-----------+
I am trying to select distinct obj_type from it using below commands:
obj=obj_ds.select("obj_type","lat2","lon2")
obj_list=obj.select("obj_type").distinct().rdd.map(lambda row : row[0]).collect()
It is failing. I tried count() and show() as well instead of collect() and they are failing too with error:
An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
The same command is working fine with other datasource that I had. Even if i run it just for some 5-10 records, it's throwing the same error. I am not able to figure out why would it fail. I tried alternate options like groupBy, but even they did not help. Why it might be failing? I am using Pyspark 2.1.0
Full error log:
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-52-39f9709c3dd5> in <module>()
1
2 obj=obj_ds.select("obj_type","lat2","lon2")
----> 3 obj_list=obj.select("obj_type").distinct().rdd.map(lambda row : row[0]).collect()
/home/mbansa001c/spark-2.1.0-bin-hadoop2.6/python/pyspark/rdd.pyc in collect(self)
807 """
808 with SCCallSiteSync(self.context) as css:
--> 809 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
810 return list(_load_from_socket(port, self._jrdd_deserializer))
811
/home/mbansa001c/spark-2.1.0-bin-hadoop2.6/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/home/mbansa001c/spark-2.1.0-bin-hadoop2.6/python/pyspark/sql/utils.pyc in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/home/mbansa001c/spark-2.1.0-bin-hadoop2.6/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 39.0 failed 4 times, most recent failure: Lost task 0.3 in stage 39.0 (TID 428, ebdp-avdc-d233p.sys.comcast.net, executor 2): java.lang.NullPointerException
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:504)
at org.apache.spark.api.python.PythonRunner$WriterThread$$anonfun$run$3.apply(PythonRDD.scala:328)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1951)
at org.apache.spark.api.python.PythonRunner$WriterThread.run(PythonRDD.scala:269)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:934)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:504)
at org.apache.spark.api.python.PythonRunner$WriterThread$$anonfun$run$3.apply(PythonRDD.scala:328)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1951)
at org.apache.spark.api.python.PythonRunner$WriterThread.run(PythonRDD.scala:269)
Surprisingly changing this worked:
obj.select("obj_type").distinct().rdd
to>>
obj.select("obj_type").rdd.distinct()
>>> import pylab as pl
>>> x = np.linspace(0,4*np.pi, 100)
>>> pl.plot(x, np.sin(x))
[<matplotlib.lines.Line2D object at 0x025B8350>]
after install numpy, scipy, sympy, matplotlib, ipython
---------------------------------------------------------------------------
TypeError Python 2.7.3: C:\Python27\python.exe
Fri Sep 28 09:59:01 2012
A problem occured executing Python code. Here is the sequence of function
calls leading up to the error, with the most recent (innermost) call last.
C:\Python27\scripts\ipython.py in <module>()
13
14 [or simply IPython.Shell.IPShell().mainloop(1) ]
15
16 and IPython will be your working environment when you start python. The final
17 sys.exit() call will make python exit transparently when IPython finishes, so
18 you don't have an extra prompt to get out of.
19
20 This is probably useful to developers who manage multiple Python versions and
21 don't want to have correspondingly multiple IPython versions. Note that in
22 this mode, there is no way to pass IPython any command-line options, as those
23 are trapped first by Python itself.
24 """
25
26 import IPython.Shell
27
---> 28 IPython.Shell.start().mainloop()
global IPython.Shell.start.mainloop = undefined
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
C:\Python27\lib\site-packages\IPython\Shell.pyc in start(user_ns=None)
1244
1245 # New versions of pygtk don't need the brittle threaded support.
1246 th_mode = check_gtk(th_mode)
1247 return th_shell[th_mode]
1248
1249
1250 # This is the one which should be called by external code.
1251 def start(user_ns = None):
1252 """Return a running shell instance, dealing with threading options.
1253
1254 This is a factory function which will instantiate the proper IPython shell
1255 based on the user's threading choice. Such a selector is needed because
1256 different GUI toolkits require different thread handling details."""
1257
1258 shell = _select_shell(sys.argv)
-> 1259 return shell(user_ns = user_ns)
1260
1261 # Some aliases for backwards compatibility
1262 IPythonShell = IPShell
1263 IPythonShellEmbed = IPShellEmbed
1264 #************************ End of file <Shell.py> ***************************
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
C:\Python27\lib\site-packages\IPython\Shell.pyc in __init__(self=<IPython.Shell.IPShell instance>, argv=None, user_ns=None, user_global_ns=None, debug=1, shell_class=<class 'IPython.iplib.InteractiveShell'>)
58 # Default timeout for waiting for multithreaded shells (in seconds)
59 GUI_TIMEOUT = 10
60
61 #-----------------------------------------------------------------------------
62 # This class is trivial now, but I want to have it in to publish a clean
63 # interface. Later when the internals are reorganized, code that uses this
64 # shouldn't have to change.
65
66 class IPShell:
67 """Create an IPython instance."""
68
69 def __init__(self,argv=None,user_ns=None,user_global_ns=None,
70 debug=1,shell_class=InteractiveShell):
71 self.IP = make_IPython(argv,user_ns=user_ns,
72 user_global_ns=user_global_ns,
---> 73 debug=debug,shell_class=shell_class)
global For = undefined
global more = undefined
global details = undefined
global see = undefined
global the = undefined
global __call__ = undefined
global method = undefined
global below. = undefined
74
75 def mainloop(self,sys_exit=0,banner=None):
76 self.IP.mainloop(banner)
77 if sys_exit:
78 sys.exit()
79
80 #-----------------------------------------------------------------------------
81 def kill_embedded(self,parameter_s=''):
82 """%kill_embedded : deactivate for good the current embedded IPython.
83
84 This function (after asking for confirmation) sets an internal flag so that
85 an embedded IPython will never activate again. This is useful to
86 permanently disable a shell that is being called inside a loop: once you've
87 figured out what you needed from it, you may then kill it and the program
88 will then continue to run without the interactive shell interfering again.
C:\Python27\lib\site-packages\IPython\ipmaker.pyc in make_IPython(argv=[r'C:\Python27\scripts\ipython.py'], user_ns=None, user_global_ns=None, debug=1, rc_override=None, shell_class=<class 'IPython.iplib.InteractiveShell'>, embedded=False, **kw={})
506 # tweaks. Basically options which affect other options. I guess this
507 # should just be written so that options are fully orthogonal and we
508 # wouldn't worry about this stuff!
509
510 if IP_rc.classic:
511 IP_rc.quick = 1
512 IP_rc.cache_size = 0
513 IP_rc.pprint = 0
514 IP_rc.prompt_in1 = '>>> '
515 IP_rc.prompt_in2 = '... '
516 IP_rc.prompt_out = ''
517 IP_rc.separate_in = IP_rc.separate_out = IP_rc.separate_out2 = '0'
518 IP_rc.colors = 'NoColor'
519 IP_rc.xmode = 'Plain'
520
--> 521 IP.pre_config_initialization()
522 # configure readline
523
524 # update exception handlers with rc file status
525 otrap.trap_out() # I don't want these messages ever.
526 IP.magic_xmode(IP_rc.xmode)
527 otrap.release_out()
528
529 # activate logging if requested and not reloading a log
530 if IP_rc.logplay:
531 IP.magic_logstart(IP_rc.logplay + ' append')
532 elif IP_rc.logfile:
533 IP.magic_logstart(IP_rc.logfile)
534 elif IP_rc.log:
535 IP.magic_logstart()
536
C:\Python27\lib\site-packages\IPython\iplib.pyc in pre_config_initialization(self=<IPython.iplib.InteractiveShell object>)
820 self.user_ns, # globals
821 # Skip our own frame in searching for locals:
822 sys._getframe(depth+1).f_locals # locals
823 ))
824
825 def pre_config_initialization(self):
826 """Pre-configuration init method
827
828 This is called before the configuration files are processed to
829 prepare the services the config files might need.
830
831 self.rc already has reasonable default values at this point.
832 """
833 rc = self.rc
834 try:
--> 835 self.db = pickleshare.PickleShareDB(rc.ipythondir + "/db")
global Optional = undefined
global inputs = undefined
836 except exceptions.UnicodeDecodeError:
837 print "Your ipythondir can't be decoded to unicode!"
838 print "Please set HOME environment variable to something that"
839 print r"only has ASCII characters, e.g. c:\home"
840 print "Now it is",rc.ipythondir
841 sys.exit()
842 self.shadowhist = IPython.history.ShadowHist(self.db)
843
844 def post_config_initialization(self):
845 """Post configuration init method
846
847 This is called after the configuration files have been processed to
848 'finalize' the initialization."""
849
850 rc = self.rc
C:\Python27\lib\site-packages\IPython\Extensions\pickleshare.pyc in __init__(self=PickleShareDB('C:\Documents and Settings\martinhylee\_ipython\db'), root=u'C:\\Documents and Settings\\martinhylee\\_ipython/db')
38 import cPickle as pickle
39 import UserDict
40 import warnings
41 import glob
42
43 def gethashfile(key):
44 return ("%02x" % abs(hash(key) % 256))[-2:]
45
46 _sentinel = object()
47
48 class PickleShareDB(UserDict.DictMixin):
49 """ The main 'connection' object for PickleShare database """
50 def __init__(self,root):
51 """ Return a db object that will manage the specied directory"""
52 self.root = Path(root).expanduser().abspath()
---> 53 if not self.root.isdir():
54 self.root.makedirs()
55 # cache has { 'key' : (obj, orig_mod_time) }
56 self.cache = {}
57
58
59 def __getitem__(self,key):
60 """ db['key'] reading """
61 fil = self.root / key
62 try:
63 mtime = (fil.stat()[stat.ST_MTIME])
64 except OSError:
65 raise KeyError(key)
66
67 if fil in self.cache and mtime == self.cache[fil][1]:
68 return self.cache[fil][0]
TypeError: _isdir() takes exactly 1 argument (0 given)
**********************************************************************
Oops, IPython crashed. We do our best to make it stable, but...
A crash report was automatically generated with the following information:
- A verbatim copy of the crash traceback.
- A copy of your input history during this session.
- Data on your current IPython configuration.
It was left in the file named:
'C:\Documents and Settings\martinhylee\_ipython\IPython_crash_report.txt'
If you can email this file to the developers, the information in it will help
them in understanding and correcting the problem.
You can mail it to: Fernando Perez at fperez.net#gmail.com
with the subject 'IPython Crash Report'.
If you want to do it now, the following command will work (under Unix):
mail -s 'IPython Crash Report' fperez.net#gmail.com < C:\Documents and Settings\martinhylee\_ipython\IPython_crash_report.txt
To ensure accurate tracking of this issue, please file a report about it at:
https://bugs.launchpad.net/ipython/+filebug
Error in sys.excepthook:
Traceback (most recent call last):
File "C:\Python27\lib\site-packages\IPython\CrashHandler.py", line 157, in __call__
report.write(self.make_report(traceback))
File "C:\Python27\lib\site-packages\IPython\CrashHandler.py", line 215, in make_report
rpt_add('BZR revision : %s \n\n' % Release.revision)
AttributeError: 'module' object has no attribute 'revision'
Original exception was:
Traceback (most recent call last):
File "C:\Python27\scripts\ipython.py", line 28, in <module>
IPython.Shell.start().mainloop()
File "C:\Python27\lib\site-packages\IPython\Shell.py", line 1259, in start
return shell(user_ns = user_ns)
File "C:\Python27\lib\site-packages\IPython\Shell.py", line 73, in __init__
debug=debug,shell_class=shell_class)
File "C:\Python27\lib\site-packages\IPython\ipmaker.py", line 521, in make_IPython
IP.pre_config_initialization()
File "C:\Python27\lib\site-packages\IPython\iplib.py", line 835, in pre_config_initialization
self.db = pickleshare.PickleShareDB(rc.ipythondir + "/db")
File "C:\Python27\lib\site-packages\IPython\Extensions\pickleshare.py", line 53, in __init__
if not self.root.isdir():
TypeError: _isdir() takes exactly 1 argument (0 given)
Try this:
from pylab import *
x = np.linspace(0.4 * np.pi, 100)
plot(x, np.sin(x))
show()