python使用pickle,json等序列化dict
2017-04-07 19:01
615 查看
import pickle, json, csv, os, shutil class PersistentDict(dict): ''' Persistent dictionary with an API compatible with shelve and anydbm. The dict is kept in memory, so the dictionary operations run as fast as a regular dictionary. Write to disk is delayed until close or sync (similar to gdbm's fast mode). Input file format is automatically discovered. Output file format is selectable between pickle, json, and csv. All three serialization formats are backed by fast C implementations. ''' def __init__(self, filename, flag='c', mode=None, format='pickle', *args, **kwds): self.flag = flag # r=readonly, c=create, or n=new self.mode = mode # None or an octal triple like 0644 self.format = format # 'csv', 'json', or 'pickle' self.filename = filename if flag != 'n' and os.access(filename, os.R_OK): fileobj = open(filename, 'rb' if format=='pickle' else 'r') with fileobj: self.load(fileobj) dict.__init__(self, *args, **kwds) def sync(self): 'Write dict to disk' if self.flag == 'r': return filename = self.filename tempname = filename + '.tmp' fileobj = open(tempname, 'wb' if self.format=='pickle' else 'w') try: self.dump(fileobj) except Exception: os.remove(tempname) raise finally: fileobj.close() shutil.move(tempname, self.filename) # atomic commit if self.mode is not None: os.chmod(self.filename, self.mode) def close(self): self.sync() def __enter__(self): return self def __exit__(self, *exc_info): self.close() def dump(self, fileobj): if self.format == 'csv': csv.writer(fileobj).writerows(self.items()) elif self.format == 'json': json.dump(self, fileobj, separators=(',', ':')) elif self.format == 'pickle': pickle.dump(dict(self), fileobj, 2) else: raise NotImplementedError('Unknown format: ' + repr(self.format)) def load(self, fileobj): # try formats from most restrictive to least restrictive for loader in (pickle.load, json.load, csv.reader): fileobj.seek(0) try: return self.update(loader(fileobj)) except Exception: pass raise ValueError('File not in a supported format') if __name__ == '__main__': import random # Make and use a persistent dictionary with PersistentDict('/tmp/demo.json', 'c', format='json') as d: print(d, 'start') d['abc'] = '123' d['rand'] = random.randrange(10000) print(d, 'updated') # Show what the file looks like on disk with open('/tmp/demo.json', 'rb') as f: print(f.read())
相关文章推荐
- python 使用 simplejson 将字符串转换成字典dict
- Python 之 pickle/json序列化 之 2
- Python--模块之sys模块、logging模块、序列化json模块、序列化pickle模块
- Python3. 4000 5——Json与pickle数据序列化
- [python]使用pickle进行序列化
- python使用pickle序列化对象至文件
- 详解Python之数据序列化(json、pickle、shelve)
- python序列化模块json和pickle
- Python中使用pickle对内建类型(built in types)进行对象序列化(object serialization and deseirialzation)
- python中使用pickle进行序列化
- python中使用pickle进行序列化
- Python之数据序列化(json、pickle、shelve)
- python 之序列化(pickle模块和json模块)
- Python学习心得(五) random生成验证码、MD5加密、pickle与json的序列化和反序列化
- Python 序列化 pickle/cPickle模块使用介绍
- python序列化模块json和pickle
- python基础6之迭代器&生成器、json&pickle数据序列化
- Python之数据序列化(json、pickle、shelve)
- python3.6使用pickle序列化class
- python--json和pickle序列化