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Pythonic module for representing and manipulating file sizes with different prefix notations.

Project description

NOTE: If you’re viewing this page on PyPi I strongly urge you to read it on GitHub instead. Over there the Markdown formatting is rendered much more pleasantly.


bitmath simplifies many facets of interacting with file sizes in various units. Examples include: converting between SI and NIST prefix units (GiB to kB), converting between units of the same type (SI to SI, or NIST to NIST), basic arithmetic operations (subtracting 42KiB from 50GiB), and rich comparison operations (1024 Bytes == 1KiB).

In addition to the conversion and math operations, bitmath provides human readable representations of values which are suitable for use in interactive shells as well as larger scripts and applications.

In discussion we will refer to the NIST units primarily. I.e., instead of “megabyte” we will refer to “mibibyte”. The former is 10^3 = 1,000,000 bytes, whereas the second is 2^20 = 1,048,576 bytes. When you see file sizes in your file browser, or transfer rates in your web browser, what you’re really seeing are the base-2 sizes/rates.


Class Initializer Signature

BitMathType([value=0, [bytes=None, [bits=None]]])

A bitmath type may be initialized in four different ways:

  • Set no initial value

The default size is 0

zero_kib = KiB()
  • Set the value in current prefix units

That is to say, if you want to encapsulate 1KiB, initialize the bitmath type with 1:

one_kib = KiB(1)

one_kib = KiB(value=1)
  • Set the number of bytes

Use the bytes keyword

one_kib = KiB(bytes=1024)
  • Set the number of bits

Use the bits keyword

one_kib = KiB(bits=8192)

Available Classes

There are two fundamental classes available:

  • Bit(Byte)
  • Byte(object)

There are 24 other classes available, representing all the prefix units from “k” through “e” (kilo/kibi through exa/exbi).

Classes with ‘i’ in their names are NIST type classes. They were defined by the National Institute of Standards and Technolog (NIST) as the ‘Binary Prefix Units’. They are defined by increasing powers of 2.

Classes without the ‘i’ character are SI type classes. Though not formally defined by any standards organization, they follow the International System of Units (SI) pattern (commonly used to abbreviate base 10 values). You may hear these referred to as the “Decimal” or “SI” prefixes.

  • Eb(Bit)
  • EB(Byte)
  • Eib(Bit)
  • EiB(Byte)
  • Gb(Bit)
  • GB(Byte)
  • Gib(Bit)
  • GiB(Byte)
  • kb(Bit)
  • kB(Byte)
  • Kib(Bit)
  • KiB(Byte)
  • Mb(Bit)
  • MB(Byte)
  • Mib(Bit)
  • MiB(Byte)
  • Pb(Bit)
  • PB(Byte)
  • Pib(Bit)
  • PiB(Byte)
  • Tb(Bit)
  • TB(Byte)
  • Tib(Bit)
  • TiB(Byte)

Note: Yes, as per SI definition, the kB class begins with a lower-case ‘k’ character.

The majority of the functionality of bitmath object comes from their rich implementation of standard Python operations. You can use bitmath objects in almost all of the places you would normally use an integer or a float. See Usage below for more details.

Instance Methods

bitmath objects come with one basic method: to_THING().

Where THING is any of the bitmath types. You can even to_THING() an instance into itself again:

In [1]: from bitmath import *

In [2]: one_mib = MiB(1)

In [3]: one_mib_in_kb = one_mib.to_kb()

In [4]: one_mib == one_mib_in_kb

Out[4]: True

In [5]: another_mib = one_mib.to_MiB()

In [6]: print one_mib, one_mib_in_kb, another_mib

1.0MiB 8388.608kb 1.0MiB

In [7]: six_TB = TB(6)

In [8]: six_TB_in_bits = six_TB.to_Bit()

In [9]: print six_TB, six_TB_in_bits

6.0TB 4.8e+13Bit

In [10]: six_TB == six_TB_in_bits

Out[10]: True

Instance Attributes

bitmath objects have three public instance attributes:

  • bytes - The number of bytes in the object
  • bits - The number of bits in the object
  • value - The value of the instance in PREFIX units

For example:

In [13]: dvd_capacity = GB(4.7)

In [14]: print “Capacity in bits: %snbytes: %sn” %

(dvd_capacity.bits, dvd_capacity.bytes)

Capacity in bits: 37600000000.0

bytes: 4700000000.0

In [15]: dvd_capacity.value

Out[16]: 4.7


Supported operations:

  • Basic arithmetic: addition, subtraction, multiplication, division
  • Size comparison: LT, LE, EQ, NE, GT, GE
  • Unit conversion: from bytes through exibytes, supports conversion to any other unit (e.g., Megabytes to Kibibytes)

Instantiating any bitmath type is simple:

one_kib = KiB(1) KiB(1.0)

Likewise, if you want to represent the same thing in bytes:

one_kib_as_byte = Byte(1024) Byte(1024.0)

In these examples one_kib and one_kib_as_byte are equivalent if tested with the == operator.

See Examples for more examples of supported operations.


Basic unit conversion:

In [1]: from bitmath import *

In [2]: fourty_two_mib = MiB(42)

In [3]: fourty_two_mib_in_kib = fourty_two_mib.to_KiB()

In [4]: fourty_two_mib_in_kib

Out[4]: KiB(43008.0)

In [5]: fourty_two_mib

Out[5]: MiB(42.0)

Equality testing:

In [6]: fourty_two_mib == fourty_two_mib_in_kib

Out[6]: True

Basic math:

In [7]: eighty_four_mib = fourty_two_mib + fourty_two_mib_in_kib

In [8]: eighty_four_mib

Out[8]: MiB(84.0)

In [9]: eighty_four_mib == fourty_two_mib * 2

Out[9]: True

Real Life Examples

Example 1: Download Speeds

Let’s pretend that your Internet service provider (ISP) advertises your maximum downstream as 50Mbps [1] and you want to know how fast that is in mibibytes? bitmath can do that for you easily. Keeping in mind that 1 Byte = 8 bits you can calculate this as such:

from bitmath import *

downstream = MB(50)

downstream.to_MiB() / 8


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

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

Example 2: Calculating how many files fit on a device

Given that we have a thumb drive with 12GiB free, how many 4MiB audio files can we fit on it?

from bitmath import *

thumb_drive = GiB(12)

audio_file = MiB(4)

thumb_drive / audio_file


This tells us that we could fit 3072 4MiB audio files on a 12GiB thumb drive.

Example 3: Printing Human-Readable File Sizes in Python

In a Python script or intrepreter 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:

>>> 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()) - 3.048828125KiB - 0.1181640625KiB - 0.744140625KiB - 2.2119140625KiB

Example 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.

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 exceede 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), between the host we’re tuning and our target remote host 1. Measure/identify our network transfer rate 1. Calculate the BDP (multiply transfer rate by rtt) 1. Obtain our current kernel settings 1. Adjust settings as necessary

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


  • We have an average network transfer rate of 1Gb/sec (where Gb is the SI unit for Gigabits, not Gibibytes)
  • 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 Bytes:

tx_rate_GB = 1/8 = 0.125

Our equivalent transfer rate is 0.125GB/sec.

  • Convert our RTT from miliseconds 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 = 10^9B

BDP_bytes = 0.000024875 * 10^9 = 24875.0

Our BDP is 24875 bytes (or about 24.3KiB)

Calculate with bitmath

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

from bitmath import GB

tx = 1/8.0

rtt = 0.199 * 10**-3

bdp = (GB(tx * rtt)).to_Byte()




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()


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?



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


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()


print sys_buffer.to_GiB()


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.

On Units

As previously stated, in this module you will find two very similar sets of classes available. These are the NIST and SI prefixes. The NIST prefixes are all base 2 and have an ‘i’ character in the middle. The SI prefixes are base 10 and have no ‘i’ character.

For smaller values, these two systems of unit prefixes are roughly equivalent. The round() operations below demonstrate how close in a percent one “unit” of SI is to one “unit” of NIST.

In [15]: one_kilo = 1 * 10**3

In [16]: one_kibi = 1 * 2**10

In [17]: round(one_kilo / float(one_kibi), 2)

Out[17]: 0.98

In [18]: one_tera = 1 * 10**12

In [19]: one_tebi = 1 * 2**40

In [20]: round(one_tera / float(one_tebi), 2)

Out[20]: 0.91

In [21]: one_exa = 1 * 10**18

In [22]: one_exbi = 1 * 2**60

In [23]: round(one_exa / float(one_exbi), 2)

Out[23]: 0.87

They begin as roughly equivalent, however as you can see, they diverge significantly for higher values.

Why two unit systems? Why take the time to point this difference out? Why should you care? The Linux Documentation Project comments on that:

Before these binary prefixes were introduced, it was fairly common to use k=1000 and K=1024, just like b=bit, B=byte. Unfortunately, the M is capital already, and cannot be capitalized to indicate binary-ness.

At first that didn’t matter too much, since memory modules and disks came in sizes that were powers of two, so everyone knew that in such contexts “kilobyte” and “megabyte” meant 1024 and 1048576 bytes, respectively. What originally was a sloppy use of the prefixes “kilo” and “mega” started to become regarded as the “real true meaning” when computers were involved. But then disk technology changed, and disk sizes became arbitrary numbers. After a period of uncertainty all disk manufacturers settled on the standard, namely k=1000, M=1000k, G=1000M.

The situation was messy: in the 14k4 modems, k=1000; in the 1.44MB diskettes, M=1024000; etc. In 1998 the IEC approved the standard that defines the binary prefixes given above, enabling people to be precise and unambiguous.

Thus, today, MB = 1000000B and MiB = 1048576B.

In the free software world programs are slowly being changed to conform. When the Linux kernel boots and says

hda: 120064896 sectors (61473 MB) w/2048KiB Cache

the MB are megabytes and the KiB are kibibytes.

Furthermore, to quote the National Institute of Standards and Technology (NIST):

“Once upon a time, computer professionals noticed that 210 was very nearly equal to 1000 and started using the SI prefix “kilo” to mean 1024. That worked well enough for a decade or two because everybody who talked kilobytes knew that the term implied 1024 bytes. But, almost overnight a much more numerous “everybody” bought computers, and the trade computer professionals needed to talk to physicists and engineers and even to ordinary people, most of whom know that a kilometer is 1000 meters and a kilogram is 1000 grams.

“Then data storage for gigabytes, and even terabytes, became practical, and the storage devices were not constructed on binary trees, which meant that, for many practical purposes, binary arithmetic was less convenient than decimal arithmetic. The result is that today “everybody” does not “know” what a megabyte is. When discussing computer memory, most manufacturers use megabyte to mean 220 = 1 048 576 bytes, but the manufacturers of computer storage devices usually use the term to mean 1 000 000 bytes. Some designers of local area networks have used megabit per second to mean 1 048 576 bit/s, but all telecommunications engineers use it to mean 106 bit/s. And if two definitions of the megabyte are not enough, a third megabyte of 1 024 000 bytes is the megabyte used to format the familiar 90 mm (3 1/2 inch), “1.44 MB” diskette. The confusion is real, as is the potential for incompatibility in standards and in implemented systems.

“Faced with this reality, the IEEE Standards Board decided that IEEE standards will use the conventional, internationally adopted, definitions of the SI prefixes. Mega will mean 1 000 000, except that the base-two definition may be used (if such usage is explicitly pointed out on a case-by-case basis) until such time that prefixes for binary multiples are adopted by an appropriate standards body.”


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