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log, records user and workgroup transformation, user login authentication information, and/var/log/ Btmp records the user, time, and remote IP address of a Linux login failure, while/var/log/cron records the execution of scheduled tasks.The Syslog service is managed by two important configuration files, namely the/etc/syslog.conf Master profile and the/etc/sysconfig/syslog secondary configuration file, while/etc/init.d/syslog is the startup script.When the system is working for a certain period

:",data_stringOutput:DATA: [{‘a‘:‘A‘,‘c‘:3.0,‘b‘:(2,4)}] #python的dict类型的数据是没有顺序存储的JSON: [{"a":"A","c":3.0,"b":[2,4]}] The output of JSON is similar to data, except for some subtle changes such as Python's tuple type becoming an array of JSON, the code conversion rules for Python to JSON are:The Json.loads method handles decoding (decoding) conversions of simple data typesimport jsondata = [{‘a‘:"A",‘b‘:(2,4),‘c‘:3.0}] #list对象data_string = json.dumps(data)print "ENCODED:",data_stringdecoded = j

1,JSON module load/loads, Dump/dumps difference: (excerpt from here)JSON is actually a string representation of a Python dictionary, but a dictionary as a complex object is a string that cannot be converted directly into the code that defines it, and Python has a library called Simplejson that makes it easy to generate and parse JSON. This package is already contained in python2.6, which is called JSON consists of four methods: Dump and

normal data types, json.loads and eval, but when it comes to special types, eval doesn't work. So the focus of eval is usually to execute a string expression and return the value of the expression.code example:This example can be changed as follows:Import Jsonx = "[none,true,false,1]" Print (eval (x))Two modules for serialization:JSON, used to convert between string and Python data typesPickle for conversion between Python-specific types and Python data typesThe JSON module provides four functi

before, then pull from the site, and into the cache. The code is as follows: Copy Code code as follows: def get_dump_data (dir_name, URL): m = hashlib.md5 (URL) filename = M.hexdigest () Full_file_name = \ ' dumps/%s/%s\ '% (dir_name,filename) If Os.path.isfile (full_file_name): Return eval (file (full_file_name,\ ' r\ '). Read ()) Else Return None def set_dump_data (dir_name, URL, data): If not os.path.isdir (\ '

seconds, that is, we apply for an exclusive latch lock on page (1:19,239), but applied for 300 seconds (5 minutes), or did not apply. Here the flags are used to determine whether the latch is superlatch, and for the analysis latch Wait is not useful, so we do not further specific analysis. The task address and the owning task address are important in memory dump analysis. Especially the owning task, which is the task that blocks other processes from acquiring latch locks. "How To fix" Latch app

modules is loaded. If you were just curious about the internals of SQL Server, this is the type of dump you want to create. Using A debugger, such aswindbg, you can analyze a dump file. Remember that is looking at a snapshot in time of the process–but even then, just showing the call stacks can be quite enlightening. INNBSP;WINDDG, the command to show all call stacks is:~*kn. If you is the kind of person who likes to has a mental model of how a product works–minidump can help you deepen

Export the database data1 to a file in the shell with Command pg_dumppg_dump-d data1-f Test.txtOrpg_dump-d data1 > Test.sqlAnd then create an empty libraryCreatedb data2Import data1 data into data2 with the Psql commandpsql-d data2-D data2 Pg_dump More informationPg_dump dumps a database into plain text files or other formats.Usage: pg_dump [options] ... [Database name]General Options:-F,--file=filename output file or directory name-F,--format=c|d|t|

Pg_restore to choose what to restore, or even reorder the items that need to be recovered before resuming. Archive files can also be ported across platforms.D:\Program Files\powercmd>pg_dump--helpPg_dump dumps a database into plain text files or other formats.Usage: pg_dump [options] ... [Database name]General Options:-F,--file=filename output file or directory name-F,--format=c|d|t|p output file format (custom, directory, tar, plain text)-V,--verbos

save for the moment, is interested in the search engine):>>> Collection.replace_one (old_document, new_document)4.4 Delete:>>> Collection.remove (temp)//Even if the temp does not exist, there will be no error >>> collection.delete_one (temp) >> > Collection.delete_many (temp)//differs from. Insert_many () and does not error when temp is not a list typeAdd:1.JSON serialization and deserialization:If you want to serialize to a standard JSON format, two ways, one way ,

This article mainly describes the use of JSON in Python, sample code based on the python2.x version, the need for friends can refer to the JSON advanced Python's Dict objects can be serialized directly into JSON {}, but many times we prefer to use class to represent objects, such as defining student classes, and then serializing: ? 1 2 3 4 5 6 7 8 9 10 Import JSON class Student (object): Def __init__ (self, name, age, score): Self.name = name Self.age = Age Self.score = SC Or

A---dumps----(JSON string)----loads---B;OBJ---stringify---(JSON string)----Parse---str; (js at the front) var obj1={name: "WC", age:18};var str=json.stringify (OBJ1);Console.log (str);var str1= ' {' name ': ' WC ', ' age ': 18} ';var obj=json.parse (STR1);Console.log (obj);Serialization ModuleThe two modules used in Python for serialization: JSON cross-platform cross-language data transfer format for conversion between "string" and "Python Ba

In a project, you need to get a JSON-formatted data from the cloud, save it to a local file, and then read it, using the JSON dumps and loads methods to serialize and deserialize the data. Specifically, the Dumps method, which can sequence JSON-formatted data into Python-related data types, is typically used for printing, and the loads method instead converts the Python data type to the JSON corresponding d

‘:‘A‘,‘c‘:3.0,‘b‘:(2,4)}] #python的dict类型的数据是没有顺序存储的JSON: [{"a":"A","c":3.0,"b":[2,4]}] The output of JSON is similar to data, except for some subtle changes such as Python's tuple type becoming an array of JSON, the code conversion rules for Python to JSON are:The Json.loads method handles decoding (decoding) conversions of simple data typesimport jsondata = [{‘a‘:"A",‘b‘:(2,4),‘c‘:3.0}] #list对象data_string = json.dumps(data)print "ENCODED:",data_stringdecoded = json.loads(data_string)print "DE

I. Use of file JSONJSON introduction: JSON Full name JavaScripts object Notation, is a lightweight data interchange format, the most extensive application of JSON as a Web server and client communication in AIAX data format, is now also used in httpd requests, So the various learning of JSON is a natural thing. The following are the two most common ways of working in peacetime. #/usr/bin/python#coding =utf-8# @Time: 2017/11/12 22:27# @Auther: Liuzhenchuan# @File: json-on. PY#1. Four ways to JSO

oracle| Reference Oracle Internal Events: Introduction: (Introduction) There are four kinds of events: Immediate dumps Conditional dumps Trace dumps Events that change database behaviour Each event has a number that is the same as the Oracle error message. Such as 10046 and ORA-10046 Each event has a level, which can be the following: Range 1 to 10 Bit

I. Memory dumps 1). Global Area ALTER session SET EVENTS ' immediate trace name Global_area level n '; 1 contains PGA 2 contains SGA 4 contains UGA 8 contains indrect memory 2). Library CacheALTER session SET EVENTS ' immediate trace name Library_cache level n '; 1 Library Cache statistic Information 2 contains hash table histogram 3 contains object handle 4 contains object structure (Heap 0) 3). Row Cache ALTER session SET EVENTS ' immediate tra

illustration: The "Transshipment (factory)/in Transfer (plant)" Inventory for Materials Z303305 is 100 (in-transit inventory formed by MB1B Mobile Type 303 dumps)  the "interim plant/in Transfer (plant)" Inventory of material Z313315 (transfer between different location of the same factory) is 0  Inventory of "in-transit inventory/stock in Transit" for material ZSTO1 100 From this, we can conclude that the stock in transit (factory) in the factory

performance analysis and tuning. Background knowledge Main methods of performance analysis Monitoring: Monitoring is a common way to view the run-time behavior of an application. There are often multiple views (view) that display CPU usage, memory usage, thread state, and other useful information in real time, so that users can quickly discover the key to the problem. Dump: The profiling tool obtains current state data from memory and stores it in a file for static profiling. A Java program

Original link: http://blog.csdn.net/chendc201/article/details/22905511In the Java multithreaded application run, in most cases we do not know what exactly happened, only the wrong log, we know that the original code is deadlock. Aside from the code-checking tool, let's talk about using VISUALVM monitoring to analyze the operation of our multithreaded operations.Ad:51cto College: It quality courses online look!In the Java multithreaded application run, in most cases we do not know what exactly ha