# 6. Real Life Examples¶

Let’s pretend that your Internet service provider (ISP) advertises your maximum downstream as 50Mbps (50 Megabits per second)1 and you want to know how fast that is in Megabytes per second? bitmath can do that for you easily. We can calculate this as such:

 1 2 3 4 >>> import bitmath >>> downstream = bitmath.Mib(50) >>> print downstream.to_MB() MB(6.25) 

This tells us that if our ISP advertises 50Mbps we can expect to see download rates of over 6MB/sec.

1. Assuming your ISP follows the common industry practice of using SI (base-10) units to describe file sizes/rates

## 6.2. Calculating how many files fit on a device¶

In 2001 Apple® announced the iPod™. Their headline statement boasting:

”... iPod stores up to 1,000 CD-quality songs on its super-thin 5 GB hard drive, ...”

OK. That’s pretty simple to work backwards: capacity of disk drive divided by number of songs equals the average size of a song. Which in this case is:

 1 2 3 >>> song_size = GB(5) / 1000 >>> print song_size 0.005GB 

Or, using best_prefix, (line 2) to generate a more human-readable form:

 1 2 3 >>> song_size = GB(5) / 1000 >>> print song_size.best_prefix() 5.0MB 

That’s great, if you have normal radio-length songs. But how many of our favorite jam-band’s 15-30+ minute-long songs could we fit on this iPod? Let’s pretend we did the math and the average audio file worked out to be 18.6 MiB (19.5 MB) large.

 1 2 3 4 >>> ipod_capacity = GB(5) >>> bootleg_size = MB(19.5) >>> print ipod_capacity / bootleg_size 256.41025641 

The result on line 4 tells tells us that we could fit 256 average-quality songs on our iPod.

## 6.3. Printing Human-Readable File Sizes in Python¶

In a Python script or interpreter we may wish to print out file sizes in something other than bytes (which is what os.path.getsize returns). We can use bitmath to do that too:

  1 2 3 4 5 6 7 8 9 10 11 >>> import os >>> from bitmath import * >>> these_files = os.listdir('.') >>> for f in these_files: ... f_size = Byte(os.path.getsize(f)) ... print "%s - %s" % (f, f_size.to_KiB()) test_basic_math.py - 3.048828125 KiB __init__.py - 0.1181640625 KiB test_representation.py - 0.744140625 KiB test_to_Type_conversion.py - 2.2119140625 KiB 

Alternatively, we could simplify things and use bitmath.getsize() to read the file size directly into a bitmath object:

  1 2 3 4 5 6 7 8 9 10 >>> import os >>> import bitmath >>> these_files = os.listdir('.') >>> for f in these_files: ... print "%s - %s" % (f, bitmath.getsize(f)) test_basic_math.py - 3.048828125 KiB __init__.py - 0.1181640625 KiB test_representation.py - 0.744140625 KiB test_to_Type_conversion.py - 2.2119140625 KiB 

Instance Formatting
How to print results in a prettier format

## 6.4. Calculating Linux BDP and TCP Window Scaling¶

Say we’re doing some Linux Kernel TCP performance tuning. For optimum speeds we need to calculate our BDP, or Bandwidth Delay Product. For this we need to calculate certain values to set some kernel tuning parameters to. The point of this tuning is to send the most data we can during a measured round-trip-time without sending more than can be processed. To accomplish this we are resizing our kernel read/write networking/socket buffers.

We will see two ways of doing this. The tedious manual way, and the way with bitmath.

### 6.4.1. The Hard Way¶

Core Networking Values

• net.core.rmem_max - Bytes - Single Value - Default receive buffer size
• net.core.wmem_max - Bytes - Single Value - Default write buffer size

System-Wide Memory Limits

• net.ipv4.tcp_mem - Pages - Three Value Vector - The max field of the parameter is the number of memory pages allowed for queueing by all TCP sockets.

Per-Socket Buffers

Per-socket buffer sizes must not exceed the core networking buffer sizes.

• net.ipv4.tcp_rmem - Bytes - Three Field Vector - The max field sets the size of the TCP receive buffer
• net.ipv4.tcp_wmem - Bytes - Three Field Vector - As above, but for the write buffer

We would normally calculate the optimal BDP and related values following this approach:

1. Measure the latency, or round trip time (RTT, measured in milliseconds), between the host we’re tuning and our target remote host
2. Measure/identify our network transfer rate
3. Calculate the BDP (multiply transfer rate by rtt)
4. Obtain our current kernel settings

But for the sake brevity we’ll be working out of an example scenario with a pre-defined RTT and transfer rate.

Scenario

• We have an average network transfer rate of 1Gb/sec (where Gb is the SI unit for Gigabits, not Gibibytes: GiB)
• Our latency (RTT) is 0.199ms (milliseconds)

Calculate Manually

Lets calculate the BDP now. Because the kernel parameters expect values in units of bytes and pages we’ll have to convert our transfer rate of 1Gb/sec into B/s (Gigabits/second to Bytes/second):

• Convert 1Gb into an equivalent byte based unit

Remember 1 Byte = 8 Bits:

tx_rate_GB = 1/8 = 0.125


Our equivalent transfer rate is 0.125GB/sec.

• Convert our RTT from milliseconds into seconds

Remember 1ms = 10-3s:

window_seconds = 0.199 * 10^-3 = 0.000199


Our equivalent RTT window is 0.000199s

• Next we multiply the transfer rate by the length of our RTT window (in seconds)

(The unit analysis for this is GB/s * s leaving us with GB)

BDP = rx_rate_GB * window_seconds = 0.125 * 0.000199 = 0.000024875


Our BDP is 0.000024875GB.

• Convert 0.000024875GB to bytes:

Remember 1GB = 109B

BDP_bytes = 0.000024875 * 10^9 = 24875.0


Our BDP is 24875 bytes (or about 24.3KiB)

### 6.4.2. The bitmath way¶

All of this math can be done much quicker (and with greater accuracy) using the bitmath library. Let’s see how:

  1 2 3 4 5 6 7 8 9 10 11 >>> from bitmath import GB >>> tx = 1/8.0 >>> rtt = 0.199 * 10**-3 >>> bdp = (GB(tx * rtt)).to_Byte() >>> print bdp.to_KiB() KiB(24.2919921875) 

Note

To avoid integer rounding during division, don’t forget to divide by 8.0 rather than 8

We could shorten that even further:

>>> print (GB((1/8.0) * (0.199 * 10**-3))).to_Byte()
24875.0Byte


Get the current kernel parameters

Important to note is that the per-socket buffer sizes must not exceed the core network buffer sizes. Lets fetch our current core buffer sizes:

$sysctl net.core.rmem_max net.core.wmem_max net.core.rmem_max = 212992 net.core.wmem_max = 212992  Recall, these values are in bytes. What are they in KiB? >>> print Byte(212992).to_KiB() KiB(208.0)  This means our core networking buffer sizes are set to 208KiB each. Now let’s check our current per-socket buffer sizes: $ sysctl net.ipv4.tcp_rmem net.ipv4.tcp_wmem
net.ipv4.tcp_rmem = 4096        87380   6291456
net.ipv4.tcp_wmem = 4096        16384   4194304


Let’s double-check that our buffer sizes aren’t already out of wack (per-socket should be <= networking core)

>>> net_core_max = KiB(bytes=212992)

>>> ipv4_tcp_rmem_max = KiB(bytes=6291456)

>>> ipv4_tcp_rmem_max > net_core_max

True


It appears that my buffers aren’t sized appropriately. We’ll fix that when we set the tunable parameters.

Finally, how large is the entire system TCP buffer?

$sysctl net.ipv4.tcp_mem net.ipv4.tcp_mem = 280632 374176 561264  Our max system TCP buffer size is set to 561264. Recall that this parameter is measured in memory pages. Most of the time your page size is 4096 bytes, but you can check by running the command: getconf PAGESIZE. To convert the system TCP buffer size (561264) into a byte-based unit, we’ll multiply it by our pagesize (4096): >>> sys_pages = 561264 >>> page_size = 4096 >>> sys_buffer = Byte(sys_pages * page_size) >>> print sys_buffer.to_MiB() 2192.4375MiB >>> print sys_buffer.to_GiB() 2.14105224609GiB  The system max TCP buffer size is about 2.14GiB. In review, we discovered the following: • Our core network buffer size is insufficient (212992), we’ll set it higher • Our current per-socket buffer sizes are 6291456 and 4194304 And we calculated the following: • Our ideal max per-socket buffer size is 24875 bytes • Our ideal default per-socket buffer size (half the max): 12437 Finally: Set the new kernel parameters Set the core-network buffer sizes: $ sudo sysctl net.core.rmem_max=24875  net.core.wmem_max=24875
net.core.rmem_max = 4235
net.core.wmem_max = 4235


Set the per-socket buffer sizes:

\$ sudo sysctl net.ipv4.tcp_rmem="4096 12437 24875" net.ipv4.tcp_wmem="4096 12437 24875"
net.ipv4.tcp_rmem = 4096 12437 24875
net.ipv4.tcp_wmem = 4096 12437 24875


And it’s done! Testing this is left as an exercise for the reader. Note that in my experience this is less useful on wireless connections.

#!/usr/bin/env python
from __future__ import print_function
import logging
import time
import bitmath
import bitmath.integrations
import argparse
import requests
import progressbar
import os
import tempfile
import atexit
import random

# Files of various sizes to use in the demo.
#
# Moar here: https://www.kernel.org/pub/linux/kernel/v3.0/?C=S;O=D
REMOTES = [
# patch-3.0.70.gz         20-Mar-2013 20:02  1.0M
'https://www.kernel.org/pub/linux/kernel/v3.0/patch-3.4.92.xz',

# patch-3.16.gz           03-Aug-2014 22:39  8.0M
'https://www.kernel.org/pub/linux/kernel/v3.0/patch-3.16.gz',

# patch-3.2.gz            05-Jan-2012 00:43   22M
'https://www.kernel.org/pub/linux/kernel/v3.0/patch-3.2.gz',
]

######################################################################
p = argparse.ArgumentParser(description='bitmath demo suite')
type=bitmath.integrations.BitmathType,
default=bitmath.MiB(4))

help='Randomly pause to slow down the transfer rate',
action='store_true', default=False)

args = p.parse_args()

######################################################################
# Save our example files somewhere. And then clean up every trace that
# anything every happened there. shhhhhhhhhhhhhhhh
DESTDIR = tempfile.mkdtemp('demosuite', 'bitmath')
@atexit.register
def cleanup():
for f in os.listdir(DESTDIR):
os.remove(os.path.join(DESTDIR, f))
os.rmdir(DESTDIR)

######################################################################
for f in REMOTES:
print("""
######################################################################""")
fname = os.path.basename(f)
# An array of widgets to design our progress bar. Note how we use
# BitmathFileTransferSpeed
widgets = ['Bitmath Demo Suite (%s): ' % fname,
progressbar.Percentage(), ' ',
progressbar.Bar(marker=progressbar.RotatingMarker()), ' ',
progressbar.ETA(), ' ',
bitmath.integrations.BitmathFileTransferSpeed()]

# The 'stream' keyword lets us http GET files in
# chunks. http://docs.python-requests.org/en/latest/user/quickstart/#raw-response-content
r = requests.get(f, stream=True)
# We haven't began receiving the payload content yet, we have only
#

# Demonstrate 'with' context handler, allowing us to customize all
# bitmath string printing within the indented block. We don't need
# all that precision anyway, just two points should do.
#
with bitmath.format("{value:.2f} {unit}"):
size.best_prefix(),
args.down.best_prefix()))

# We have to save these files somewhere
save_path = os.path.join(DESTDIR, fname)
print("Saving to: %s" % save_path)
print("")

# OK. Let's create our actual progress bar now. See the 'maxval'
# keyword? That's the size of our payload in bytes.
pbar = progressbar.ProgressBar(
widgets=widgets,
maxval=int(size)).start()

######################################################################
# Open a new file for binary writing and write 'args.down' size
with open(save_path, 'wb') as fd:
# The 'iter_content' method accepts integer values of
# bytes. Lucky for us, 'args.down' is a bitmath instance and
# has a 'bytes' attribute we can feed into the method call.
for chunk in r.iter_content(int(args.down.bytes)):
fd.write(chunk)
# The progressbar will end the entire cosmos as we know it
# if we try to .update() it beyond it's MAXVAL
# parameter.
#
# That's something I'd like to avoid taking the
# responsibility for.
if (pbar.currval + args.down.bytes) < pbar.maxval:
pbar.update(pbar.currval + int(args.down.bytes))

# We can add an pause to artificially speed up/slowdown
# the transfer rate. Allows us to see different units.
if args.slowdown:
# randomly slow down 1/5 of the time
if random.randrange(0, 100) % 5 == 0:
time.sleep(random.randrange(0, 500) * 0.01)

# Nothing to see here. Go home.
pbar.finish()

######################################################################
print("""
######################################################################
* Filter for .xz files only
""")

for p,bm in bitmath.listdir(DESTDIR,
filter='*.xz'):
print(p, bm)

######################################################################
print("""
######################################################################
* Filter for .gz files only
* Print using best human readable prefix
""")

for p,bm in bitmath.listdir(DESTDIR,
filter='*.gz',
bestprefix=True):
print(p, bm)

######################################################################
print("""
######################################################################
* No filter set, to display all files
* Limit precision of printed file size to 3 digits
* Print using best human readable prefix
""")

for p,bm in bitmath.listdir(DESTDIR,
bestprefix=True):
with bitmath.format("{value:.3f} {unit}"):
print(p, bm)

######################################################################
print("""
######################################################################
* Print with best prefix and 3 digits of precision
""")

discovered_files = [f[1] for f in bitmath.listdir(DESTDIR)]
total_size = reduce(lambda x,y: x+y, discovered_files).best_prefix().format("{value:.3f} {unit}")

• View the the source for the demo suite on GitHub

## 6.6. Reading a Devices Storage Capacity¶

Important

Superuser (root/admin) privileges are required to allow bitmath.query_device_capacity() to make the low-level system calls to read a devices capacity. Use of this function on a device the user does not have access to will result in run-time errors.

Using bitmath.query_device_capacity() we can read the size of a storage device or a partition on a device.

Examples of supported devices include:

• Standard Hard Drives/External Drives
• Filesystem Partitions
• Loop Devices
• LVM Logical Volumes
• Encrypted LUKS Volumes
• iSCSI Devices

Usage is fairly straight-forward. Create an open file handle of the device you want to read the capacity of and then create a bitmath object with the query_device_capacity function. Here’s an example where we read the capacity of device sda, the first device on the example system.

>>> import bitmath
>>> fh = open('/dev/sda', 'r')
>>> sda_capacity = bitmath.query_device_capacity(fh)
>>> fh.close()
>>> print sda_capacity.best_prefix()
238.474937439 GiB


We can simplify this so that the file handle is automatically closed for us by using the with context manager.

>>> with open('/dev/sda', 'r') as fh:
...     sda_capacity = bitmath.query_device_capacity(fh)
>>> print sda_capacity.best_prefix()
238.474937439 GiB