Reading Large File from non local disk in Python
Copying a file is sequentially reading it and saving in another place.
The performance of application might vary depending on the data access patterns, computation to I/O time, network latency and network bandwidth.
If you execute your script once, and read through it sequentially it's the same as copying the file, except you perform computations on it instead of saving. Even if you process small chunks of data it probably gets buffered. In fact in case of a single execution, if you copy 1st you actually read the same data twice, once for copy, and once the copy for computation.
If you execute your script multiple times, then you need to check what is your data troughput.  For example, if you have a gigabit ethernet then 1GBit/s is 125MByte/s, if you process data slower, then you are not limited by the bandwidth.
Network latency comes into play when you send multiple requests for small chunks of data. Upon a read request you send a network request and get data back in a finite time, this is the latency. If you make a request for one big chunk of data you "pay" the latency limit once, if you ask 1000 times for 1/1000 of the big chunk you will need to "pay" it 1000 times. However, this is probably abstracted from you by the network file system and in case of a sequential read it will get buffered. It would manifest itself in randon jumping over file and reading small chunks of it.
You can check what you are limited by checking how much bytes you process per second and compare it to limits of the hardware. If it's close to HDD speed (which in your case i bet is not) you are bound by I/O - HDD. If it's lower, close to network bandwidth, you are limited by I/O - network. If it's even lower, it's either you are bound by processing speed of data or I/O network latency. However, if you were bound by I/O you should see difference between the two approaches, so if you are seeing the same results it's computation.
Sorry if the topic was already approached, I didn't find it.
I am trying to read with Python a bench of large csv files (>300 MB) that are not located in a local drive. 
I am not an expert in programming but I know that if you copy it into a local drive first it should take less time that reading it (or am I wrong?).
The thing is that I tested both methods and the computation times are similar.
Am I missing something? Can someone explain / give me a good method to read those file as fast as possible?
For copying to local drive I am using: shutil.copy2
For reading the file: for each line in MyFile
Thanks a lot for your help,
Christophe