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from memory to storage or transmission is called serialization and picking in python. After serialization, The serialized content can be written to the disk or transmitted to another machine over the network.In turn, it is called deserialization to re-read the variable content from the serialized object to the memory.Python provides two modules for serialization.CPickle, pickle Import Module: DOut [11]: {'age': 20, 'name': 'jack', 'score ': 88} In [12]: try:...: Import cPickle as pickle...: R

This article mainly introduces the example of using the Pythonjson module. This article provides multiple code examples. For more information, see JSON, which is a string representation of the Python dictionary, however, the dictionary cannot be directly transmitted as a complex object, so it must be converted into a string. the conversion process is also a serialization process. Serialized in json. dumps format The code is as follows: >>> Import js

Java.lang.OutOfMemoryError:unable to create native thread The exception is to say that if you have a large number of threads, or if local memory is exhausted, new threads are thrown when they attempt to create.What is Java Heap Dump? We know that Java Heap is a runtime data area allocated by all class instances and array objects, in which all Java VM threads share data from the Heap during execution. Then a Java heap dump is equivalent to a snapshot generated at a particular point

makes it possible to exchange a data format between programming languages that are also based on these structures. Json official instructions see: http://json.org/ Python to operate json standard api library reference: http://docs.python.org/library/json.html Encoding and decoding for simple data types: The simple json. dumps method is used to encode the simple data type, for example: import jsonobj = [[1,2,3],123,123.123,'abc',{'key1':(1,2,3),'key2'

mechanism design are: first, how to build redundant data, and secondly, how to use these redundant data to implement database recovery. The implementation technology of recovery Data dumps Data dumps are the basic technique used in database recovery, where a DBA periodically copies an entire database to a tape or another disk. Dumps are time-consuming and resou

python object encoding to a json string. deserialization can be understood as decoding a json string into a python data object. In the standard python library, the json Library and the pickle library are provided to process this part. Json dumps and loads methods can be used to serialize and deserialize data. Specifically, the dumps method can convert the data sequence in json format to the relevant data t

reduces the time that is not available to the database for backup copies. In many cases, the time savings are measured in hours, and concurrent copies greatly increase the flexibility of the scheduling of online operations and batching in a os/390 environment. Prior to the occurrence of concurrent copies, alternate transposition between physical and logical information dumps is often required. In the dump process, the data is not available for other

Translated from MoS article: Under Win2003 SP1, encountering unexplained database performance degradationUnexplained Database slowdown Seen on Windows 2003 Service Pack 1 (Doc ID 464683.1)Applies To:Oracle server-enterprise edition-version 9.2.0.1 to 11.1.0.6 [Release 9.2 to 11.1]Z*obsolete:microsoft Windows Server 2003Microsoft Windows Itanium (64-bit)Z*obsolete:microsoft Windows XP (64-bit AMD64 and Intel EM64T)Microsoft Windows Server 2003 (64-bit Itanium) Microsoft Windows Server 2003Microso

As mentioned above, the dump file can save the Process status for easy analysis. Because the dump file records the specific information of a process at a certain time point, it is very important to save the dump. For exampleProgramCrash: dump should be obtained when the command that causes the crash is executed (that is, when the 1st chance exception occurs), so that the direct cause of the problem can be seen during dump analysis. Adplus is a vbs script in the same directory as windbg. Adplus

bandwidth, so the appropriate time also to compress the data. The separator parameter can play the role of a tuple that contains a string that splits the object.print ' data: ', repr (data) print ' repr (data): ', Len (repr (data)) print ' Dumps (data): ', Len (json.dumps (data)) print ' Dumps (data, indent=2): ', Len (json.dumps (data, indent=4)) print ' Dumps

$ python json_simple_types.py DATA: [{' A]: ' A ', ' C ': 3.0, ' B ': (2, 4)}] JSON: [{"A]: "A", "C": 3.0, "B": [2, 4]}] The value obtained by decoding after encoding may not be exactly the same as the original object. [python] view plain copy import JSON data = [{' A ': ' A ', ' B ':(2, 4), ' C ': 3.0}] data_string = Json.dumps (dat A) print ' encoded: ', data_string decoded = Json.loads (data_string) print ' decoded: ', decoded print ' ORIGINAL: ', Ty PE (data[0][' B ']) print ' decoded: ', t

}53 if (_ baseURL = "t @ 128 ")54 {55 url = "http: // mt" + (col % 4) + ".google.cn/vt/lyrs=" + _ baseURL + ", r @ 169000000 v = w2.114 hl = zh-CN gl = cn "+" x = "+ col +" "+" y = "+ row + " "+" z = "+ level +" s = Galil ";56}57 if (_ baseURL = "m @ 161000000 ")58 {59 url = "http: // mt" + (col % 4) + ".google.cn/vt/lyrs=" + _ baseURL + " v = w2.114 hl = zh-CN gl = cn " + "x =" + col + "" + "y = "+ row +" "+" z = "+ level +" s = Galil ";60}61 return new URLRequest (url );62}6364 priva

Serialization related 1. Json Application Scenarios: The JSON module is primarily used to process data in JSON format, can convert JSON-formatted data into a Python dictionary, facilitates python processing, and can convert objects such as a Python dictionary or list into JSON-formatted data for cross-platform or cross-language data interaction Function: The JSON module provides four functions: dumps, dump, loads, load

1. How to set up redundant data Data dump (Backup) Log in log file (logging) 1. Data dumpsCharacteristics: The backup copy can be re-loaded after the database has been compromised Reloading a backup copy only restores the database to the state at the time of the dump Method: Static dumps and dynamic dumps Mass

Python learning path ----- serialization, python ----- serialization The process of changing variables from memory to storage or transmission is called serialization. in Python, it is called pickling. In other languages, it is also called serialization, alling, flattening, and so on. After serialization, The serialized content can be written to the disk or transmitted to another machine over the network. In turn, it is called deserialization to re-read the variable content from the serialized ob

performance. Below we discuss the provided interface, and only show the necessary parameters, the other keyword parameters will be expressed as **kwargs; Simplejson. Dump (obj, fp, **kwargs): Writes Python objects to a file (in JSON format) Simplejson. dumps (obj, **kwargs): Represents a Python object as a string (in JSON format) Simplejson. Load (FP, **kwargs): read from a file (containing a JSON structure) as a Python object Simplejson. l

One, JSON Pickle Shelve ModuleJSON, used to convert between string and Python data typesPickle for conversion between Python-specific types and Python data typesThe JSON module provides four functions: dumps, dump, loads, loadThe Pickle module provides four functions: dumps, dump, loads, loadJSON module:Here are some examples to learn:First, let's look at the JSON dum