tungwaiyip.info

home

about me

links

Blog

< May 2010 >
SuMoTuWeThFrSa
       1
2 3 4 5 6 7 8
9101112131415
16171819202122
23242526272829
3031     

past articles »

Click for San Francisco, California Forecast

San Francisco, USA

 

Python CSV reader is much faster than pickle

If you are considering to serialize a large amount of data to the disk, performance may become a concern to you. Python provides a serialization tool in the pickle module. There is also an optimized version called the cPickle. But how do they perform?

The data of concern to me is tabular data. In order to do a bake off, I have generated 50,000 records of sample data. The CSV representation is shown below:

seq, name, address, city, age, birthday
1000,John M. Doe,2147 Main St.,Middle Town 14,47,1985-05-15
1001,John N. Doe,2148 Main St.,Middle Town 15,48,1985-05-16
1002,John O. Doe,2149 Main St.,Middle Town 16,49,1985-05-17
1003,John P. Doe,2150 Main St.,Middle Town 17,50,1985-05-18
1004,John Q. Doe,2151 Main St.,Middle Town 18,51,1985-05-19
1005,John R. Doe,2152 Main St.,Middle Town 19,52,1985-05-20
1006,John S. Doe,2153 Main St.,Middle Town 20,53,1985-05-21
1007,John T. Doe,211 Main St.,Middle Town 21,1,1985-05-22
...

Naturally, CSV is a contender for storing tabular data. (Indeed the data source I'm working with is in CSV format.) The two pickle modules produce identical data output. In addition, Python 2.6 also provides a JSON module that do the similar task as pickle but outputs a standard text based format. I included it in the comparison below.

First observation, CSV output the most compact data at 3MB. Pickle output is 40% larger at 4.2MB. JSON is somewhere in between. The speed? CSV is the winner among them all.


Method Load Time (ms) File size (MB)
CSV 188 3
CSV int 289 3
cPickle 692 4.2
pickle 1,815 4.2
JSON 4,975 3.9

Note that CSV reader create data items as string. In the sample data, two out of the six columns are integer fields. In order to do an apple-to-apple comparison I have another test that do integer conversion after loading such that the data loaded is identical to pickle's. This impacted the performance somewhat. But it is still more than twice as fast as the faster cPickle module. The standard library's JSON's performance trailing far behind, making it unsuitable for anything performance intensive. FYI, unlike the other modules, JSON's output is in unicode.

The test is done by Python 2.6 on Windows XP machine with 2.33GHz Core2 CPU (Download source code).


2010.05.12 [, ] - comments

 

 

blog comments powered by Disqus

past articles »

 

BBC News

 

Brexit: Cabinet considering ramping up no-deal plans (18 Dec 2018)

 

Yemen war: Ceasefire takes effect in Hudaydah after skirmishes (18 Dec 2018)

 

Jose Mourinho: Manchester United sack manager (18 Dec 2018)

 

Gently stroking babies 'provides pain relief' (18 Dec 2018)

 

China 'will not seek to dominate' (18 Dec 2018)

 

Women shave their heads to protest lawyer's detention in China (18 Dec 2018)

 

Russian cargo ship runs aground off Cornwall coast (18 Dec 2018)

 

El Salvador court frees woman jailed under anti-abortion laws (18 Dec 2018)

 

Two Scandinavian women tourists found dead in Morocco (18 Dec 2018)

 

Former CBS boss Les Moonves denied exit pay (18 Dec 2018)

more »

 

SF Gate

 

For retailers, smartphone is the future of store expierience (17 Dec 2018)

 

Ship traffic, December 18 (17 Dec 2018)

 

Equifax failed to match security to its growth, report says (16 Dec 2018)

 

Hertz teams up with Clear to speed rentals with biometric scans (16 Dec 2018)

 

Analysis: Is tech too easy to use? (16 Dec 2018)

 

San Franciscans Googled some weird stuff in 2018 (15 Dec 2018)

more »


Site feed Updated: 2018-Dec-18 03:00