This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
Latest Version Dependencies status unknown Test status unknown Test coverage unknown
Project Description

The performance project is intended to be an authoritative source of benchmarks for all Python implementations. The focus is on real-world benchmarks, rather than synthetic benchmarks, using whole applications when possible.

Other Python Benchmarks:

See also the Python speed mailing list and the Python perf module (used by performance).

Installation

Command to install performance:

python3 -m pip install performance

On Python 2, the virtualenv program (or the Python module) is required to create virtual environments. On Python 3, the venv module of the standard library is used.

At runtime, Python development files (header files) may be needed to install some dependencies like dulwich_log or psutil, to build their C extension. Commands on Fedora to install dependencies:

  • Python 2: sudo dnf install python-devel
  • Python 3: sudo dnf install python3-devel
  • PyPy: sudo dnf install pypy-devel

Run benchmarks

Commands to compare Python 2 and Python 3 performances:

pyperformance run --python=python2 -o py2.json
pyperformance run --python=python3 -o py3.json
pyperformance compare py2.json py3.json

Note: python3 -m performance ... syntax works as well (ex: python3 -m performance run -o py3.json), but requires to install performance on each tested Python version.

Actions:

run                 Run benchmarks on the running python
show                Display a benchmark file
compare             Compare two benchmark files
list                List benchmarks which run command would run
list_groups         List all benchmark groups
venv                Actions on the virtual environment

Common options

Options available to all commands:

-p PYTHON, --python PYTHON
                      Python executable (default: use running Python)
--venv VENV           Path to the virtual environment
--inherit-environ VAR_LIST
                      Comma-separated list of environment variable names
                      that are inherited from the parent environment when
                      running benchmarking subprocesses.

run

Options of the run command:

-r, --rigorous        Spend longer running tests to get more accurate
                      results
-f, --fast            Get rough answers quickly
-m, --track-memory    Track memory usage. This only works on Linux.
-b BM_LIST, --benchmarks BM_LIST
                      Comma-separated list of benchmarks to run. Can contain
                      both positive and negative arguments:
                      --benchmarks=run_this,also_this,-not_this. If there
                      are no positive arguments, we'll run all benchmarks
                      except the negative arguments. Otherwise we run only
                      the positive arguments.
--affinity CPU_LIST   Specify CPU affinity for benchmark runs. This way,
                      benchmarks can be forced to run on a given CPU to
                      minimize run to run variation. This uses the taskset
                      command.
-o FILENAME, --output FILENAME
                      Run the benchmarks on only one interpreter and write
                      benchmark into FILENAME. Provide only baseline_python,
                      not changed_python.
--append FILENAME     Add runs to an existing file, or create it if it
                      doesn't exist

show

Usage:

show FILENAME

compare

Options of the compare command:

-v, --verbose         Print more output
-O STYLE, --output_style STYLE
                      What style the benchmark output should take. Valid
                      options are 'normal' and 'table'. Default is normal.

list

Options of the list command:

-b BM_LIST, --benchmarks BM_LIST
                      Comma-separated list of benchmarks to run. Can contain
                      both positive and negative arguments:
                      --benchmarks=run_this,also_this,-not_this. If there
                      are no positive arguments, we'll run all benchmarks
                      except the negative arguments. Otherwise we run only
                      the positive arguments.

Use python3 -m performance list -b all to list all benchmarks.

venv

Options of the venv command:

-p PYTHON, --python PYTHON
                      Python executable (default: use running Python)
--venv VENV           Path to the virtual environment

Actions of the venv command:

show      Display the path to the virtual environment and it's status (created or not)
create    Create the virtual environment
recreate  Force the recreation of the the virtual environment
remove    Remove the virtual environment

How to get stable benchmarks

Advices helping to get make stable benchmarks:

  • Run python3 -m perf system tune command

  • See also advices in the perf documentation: Stable and reliable benchmarks

  • Compile Python using LTO (Link Time Optimization) and PGO (profile guided optimizations):

    ./configure --with-lto
    make profile-opt
    

    You should get the -flto option on GCC for example.

  • Use the --rigorous option of the run command

Notes:

  • Development versions of Python 2.7, 3.6 and 3.7 have a –with-optimization configure option
  • –with-optimization doesn’t enable LTO because of compiler bugs: http://bugs.python.org/issue28032 (see also: http://bugs.python.org/issue28605)
  • PGO is broken on Ubuntu 14.04 LTS with GCC 4.8.4-2ubuntu1~14.04: Modules/socketmodule.c:7743:1: internal compiler error: in edge_badness, at ipa-inline.c:895
  • If nohz_full kernel option is used, the CPU frequency must be fixed, otherwise the CPU frequency will be instable. See Bug 1378529: intel_pstate driver doesn’t support NOHZ_FULL.
  • ASLR must not be disabled manually! (it’s enabled by default on Linux)

Notes

Tool for comparing the performance of two Python implementations.

pyperformance will run Student’s two-tailed T test on the benchmark results at the 95% confidence level to indicate whether the observed difference is statistically significant.

Omitting the -b option will result in the default group of benchmarks being run Omitting -b is the same as specifying -b default.

To run every benchmark pyperformance knows about, use -b all. To see a full list of all available benchmarks, use –help.

Negative benchmarks specifications are also supported: -b -2to3 will run every benchmark in the default group except for 2to3 (this is the same as -b default,-2to3). -b all,-django will run all benchmarks except the Django templates benchmark. Negative groups (e.g., -b -default) are not supported. Positive benchmarks are parsed before the negative benchmarks are subtracted.

If --track_memory is passed, pyperformance will continuously sample the benchmark’s memory usage. This currently only works on Linux 2.6.16 and higher or Windows with PyWin32. Because --track_memory introduces performance jitter while collecting memory measurements, only memory usage is reported in the final report.

Benchmarks

Available Groups

Like individual benchmarks (see “Available benchmarks” below), benchmarks group are allowed after the -b option. Use python3 -m performance list_groups to list groups and their benchmarks.

Available benchmark groups:

  • 2n3: Benchmarks compatible with both Python 2 and Python 3
  • all: Group including all benchmarks
  • apps: “High-level” applicative benchmarks (2to3, Chameleon, Tornado HTTP)
  • calls: Microbenchmarks on function and method calls
  • default: Group of benchmarks run by default by the run command
  • etree: XML ElementTree
  • math: Float and integers
  • regex: Collection of regular expression benchmarks
  • serialize: Benchmarks on pickle and json modules
  • startup: Collection of microbenchmarks focused on Python interpreter start-up time.
  • template: Templating libraries

There is also a disabled threading group: collection of microbenchmarks for Python’s threading support. These benchmarks come in pairs: an iterative version (iterative_foo), and a multithreaded version (threaded_foo).

Available Benchmarks

  • 2to3 - have the 2to3 tool translate itself.
  • call_method - positional arguments-only method calls.
  • call_method_slots - method calls on classes that use __slots__.
  • call_method_unknown - method calls where the receiver cannot be predicted.
  • call_simple - positional arguments-only function calls.
  • chameleon - render a template using the chameleon module
  • chaos - create chaosgame-like fractals
  • crypto_pyaes - benchmark a pure-Python implementation of the AES block-cipher in CTR mode using the pyaes module.
  • deltablue - DeltaBlue benchmark
  • django_template - use the Django template system to build a 150x150-cell HTML table (django.template module).
  • dulwich_log: Iterate on commits of the asyncio Git repository using the Dulwich module
  • fannkuch
  • fastpickle - use the cPickle module to pickle a variety of datasets.
  • fastunpickle - use the cPickle module to unnpickle a variety of datasets.
  • float - artificial, floating point-heavy benchmark originally used by Factor.
  • genshi: Benchmark the genshi.template module
    • genshi_text: Render template to plain text
    • genshi_xml: Render template to XML
  • go: Go board game
  • hexiom - Solver of Hexiom board game (level 25 by default)
  • hg_startup - Get Mercurial’s help screen.
  • html5lib - parse the HTML 5 spec using html5lib.
  • json_dumps - Benchmark json.dumps()
  • json_loads - Benchmark json.loads()
  • logging - Benchmarks on the logging module
    • logging_format: Benchmark logger.warn(fmt, str)
    • logging_simple: Benchmark logger.warn(msg)
    • logging_silent: Benchmark logger.warn(msg) when the message is ignored
  • mako - use the Mako template system to build a 150x150-cell HTML table.
  • mdp - battle with damages and topological sorting of nodes in a graph
  • meteor_contest - solver for Meteor Puzzle board
  • nbody - the N-body Shootout benchmark. Microbenchmark for floating point operations.
  • normal_startup - Measure the Python startup time
  • nqueens - Simple, brute-force N-Queens solver
  • pathlib - Test the performance of operations of the pathlib module. This benchmark stresses the creation of small objects, globbing, and system calls.
  • pickle_dict - microbenchmark; use the cPickle module to pickle a lot of dicts.
  • pickle_list - microbenchmark; use the cPickle module to pickle a lot of lists.
  • pickle_pure_python - use the pure-Python pickle module to pickle a variety of datasets.
  • pidigits - Calculating 2,000 digits of π. This benchmark stresses big integer arithmetic.
  • pybench - run the standard Python PyBench benchmark suite. This is considered an unreliable, unrepresentative benchmark; do not base decisions off it. It is included only for completeness.
  • pyflate - Pyflate benchmark: tar/bzip2 decompressor in pure Python
  • raytrace - Simple raytracer.
  • regex_compile - stress the performance of Python’s regex compiler, rather than the regex execution speed.
  • regex_dna - regex DNA benchmark using “fasta” to generate the test case
  • regex_effbot - some of the original benchmarks used to tune mainline Python’s current regex engine.
  • regex_v8 - Python port of V8’s regex benchmark.
  • richards - the classic Richards benchmark.
  • scimark:
  • spambayes - run a canned mailbox through a SpamBayes ham/spam classifier.
  • spectral_norm - MathWorld: “Hundred-Dollar, Hundred-Digit Challenge Problems”, Challenge #3.
  • sqlalchemy_declarative - SQLAlchemy Declarative benchmark using SQLite
  • sqlalchemy_imperative - SQLAlchemy Imperative benchmark using SQLite
  • sqlite_synth - Benchmark Python aggregate for SQLite
  • startup_nosite - Measure the Python startup time without importing the site module (python -S)
  • sympy - Benchmark on the sympy module
    • sympy_expand: Benchmark sympy.expand()
    • sympy_integrate: Benchmark sympy.integrate()
    • sympy_str: Benchmark str(sympy.expand())
    • sympy_sum: Benchmark sympy.summation()
  • telco - Benchmark the decimal module
  • tornado_http - Benchmark HTTP server of the tornado module
  • unpack_sequence - microbenchmark for unpacking lists and tuples.
  • unpickle_list
  • unpickle_pure_python - use the pure-Python pickle module to unpickle a variety of datasets.
  • xml_etree: Benchmark the xml.etree module
    • xml_etree_generate: Create an XML document
    • xml_etree_iterparse: Benchmark etree.iterparse()
    • xml_etree_parse: Benchmark etree.parse()
    • xml_etree_process: Process an XML document

There are also two disabled benchmarks:

  • threading_threaded_count - spin in a while loop, counting down from a large number in a thread.
  • threading_iterative_count - spin in a while loop, counting down from a large number.

Changelog

Version 0.5.0 (2016-11-16)

  • Add mdp benchmark: battle with damages and topological sorting of nodes in a graph
  • The default benchmark group now include all benchmarks but pybench
  • If a benchmark fails, log an error, continue to execute following benchmarks, but exit with error code 1.
  • Remove deprecated benchmarks: threading_threaded_count and threading_iterative_count. It wasn’t possible to run them anyway.
  • dulwich requirement is now optional since its installation fails on Windows.
  • Upgrade requirements:
    • Mako: 1.0.5 => 1.0.6
    • Mercurial: 3.9.2 => 4.0.0
    • SQLAlchemy: 1.1.3 => 1.1.4
    • backports-abc: 0.4 => 0.5

Version 0.4.0 (2016-11-07)

  • Add sqlalchemy_imperative benchmark: it wasn’t registered properly
  • The list command now only lists the benchmark that the run command will run. The list command gets a new -b/--benchmarks option.
  • Rewrite the code creating the virtual environment to test correctly pip. Download and run get-pip.py if pip installation failed.
  • Upgrade requirements:
    • perf: 0.8.2 => 0.9.0
    • Django: 1.10.2 => 1.10.3
    • Mako: 1.0.4 => 1.0.5
    • psutil: 4.3.1 => 5.0.0
    • SQLAlchemy: 1.1.2 => 1.1.3
  • Remove virtualenv dependency

Version 0.3.2 (2016-10-19)

  • Fix setup.py: include also performance/benchmarks/data/asyncio.git/

Version 0.3.1 (2016-10-19)

  • Add regex_dna benchmark
  • The run command now fails with an error if no benchmark was run.
  • genshi, logging, scimark, sympy and xml_etree scripts now run all sub-benchmarks by default
  • Rewrite pybench using perf: remove the old legacy code to calibrate and run benchmarks, reuse perf.Runner API.
  • Change heuristic to create the virtual environment, tried commands:
    • python -m venv
    • python -m virtualenv
    • virtualenv -p python
  • The creation of the virtual environment now ensures that pip works to detect “python3 -m venv” which doesn’t install pip.
  • Upgrade perf dependency from 0.7.12 to 0.8.2: update all benchmarks to the new perf 0.8 API (which introduces incompatible changes)
  • Update SQLAlchemy from 1.1.1 to 1.1.2

Version 0.3.0 (2016-10-11)

New benchmarks:

  • Add crypto_pyaes: Benchmark a pure-Python implementation of the AES block-cipher in CTR mode using the pyaes module (version 1.6.0). Add pyaes dependency.
  • Add sympy: Benchmark on SymPy. Add scipy dependency.
  • Add scimark benchmark
  • Add deltablue: DeltaBlue benchmark
  • Add dulwich_log: Iterate on commits of the asyncio Git repository using the Dulwich module. Add dulwich (and mpmath) dependencies.
  • Add pyflate: Pyflate benchmark, tar/bzip2 decompressor in pure Python
  • Add sqlite_synth benchmark: Benchmark Python aggregate for SQLite
  • Add genshi benchmark: Render template to XML or plain text using the Genshi module. Add Genshi dependency.
  • Add sqlalchemy_declarative and sqlalchemy_imperative benchmarks: SQLAlchemy Declarative and Imperative benchmarks using SQLite. Add SQLAlchemy dependency.

Enhancements:

  • compare command now fails if the performance versions are different
  • nbody: add --reference and --iterations command line options.
  • chaos: add --width, --height, --thickness, --filename and --rng-seed command line options
  • django_template: add --table-size command line option
  • json_dumps: add --cases command line option
  • pidigits: add --digits command line option
  • raytrace: add --width, --height and --filename command line options
  • Port html5lib benchmark to Python 3
  • Enable pickle_pure_python and unpickle_pure_python on Python 3 (code was already compatible with Python 3)
  • Creating the virtual environment doesn’t inherit environment variables (especially PYTHONPATH) by default anymore: --inherit-environ command line option must now be used explicitly.

Bugfixes:

  • chaos benchmark now also reset the random module at each sample to get more reproductible benchmark results
  • Logging benchmarks now truncate the in-memory stream before each benchmark run

Rename benchmarks:

  • Rename benchmarks to get a consistent name between the command line and benchmark name in the JSON file.

  • Rename pickle benchmarks:

    • slowpickle becomes pickle_pure_python
    • slowunpickle becomes unpickle_pure_python
    • fastpickle becomes pickle
    • fastunpickle becomes unpickle
  • Rename ElementTree benchmarks: replace etree_ prefix with xml_etree_.
  • Rename hexiom2 to hexiom_level25 and explicitly pass --level=25 parameter
  • Rename json_load to json_loads
  • Rename json_dump_v2 to json_dumps (and remove the deprecated json_dump benchmark)
  • Rename normal_startup to python_startup, and startup_nosite to python_startup_no_site
  • Rename threaded_count to threading_threaded_count, rename iterative_count to threading_iterative_count
  • Rename logging benchmarks:
    • silent_logging to logging_silent
    • simple_logging to logging_simple
    • formatted_logging to logging_format

Minor changes:

  • Update dependencies
  • Remove broken --args command line option.

Version 0.2.2 (2016-09-19)

  • Add a new show command to display a benchmark file
  • Issue #11: Display Python version in compare. Display also the performance version.
  • CPython issue #26383; csv output: don’t truncate digits for timings shorter than 1 us
  • compare: Use sample unit of benchmarks, format values in the table output using the unit
  • compare: Fix the table output if benchmarks only contain a single sample
  • Remove unused -C/–control_label and -E/–experiment_label options
  • Update perf dependency to 0.7.11 to get Benchmark.get_unit() and BenchmarkSuite.get_metadata()

Version 0.2.1 (2016-09-10)

  • Add --csv option to the compare command
  • Fix compare -O table output format
  • Freeze indirect dependencies in requirements.txt
  • run: add --track-memory option to track the memory peak usage
  • Update perf dependency to 0.7.8 to support memory tracking and the new --inherit-environ command line option
  • If virtualenv command fail, try another command to create the virtual environment: catch virtualenv error
  • The first command to upgrade pip to version >= 6.0 now uses the pip binary rather than python -m pip to support pip 1.0 which doesn’t support python -m pip CLI.
  • Update Django (1.10.1), Mercurial (3.9.1) and psutil (4.3.1)
  • Rename --inherit_env command line option to --inherit-environ and fix it

Version 0.2 (2016-09-01)

  • Update Django dependency to 1.10
  • Update Chameleon dependency to 2.24
  • Add the --venv command line option
  • Convert Python startup, Mercurial startup and 2to3 benchmarks to perf scripts (bm_startup.py, bm_hg_startup.py and bm_2to3.py)
  • Pass the --affinity option to perf scripts rather than using the taskset command
  • Put more installer and optional requirements into performance/requirements.txt
  • Cached .pyc files are no more removed before running a benchmark. Use venv recreate command to update a virtual environment if required.
  • The broken --track_memory option has been removed. It will be added back when it will be fixed.
  • Add performance version to metadata
  • Upgrade perf dependency to 0.7.5 to get Benchmark.update_metadata()

Version 0.1.2 (2016-08-27)

  • Windows is now supported
  • Add a new venv command to show, create, recrete or remove the virtual environment.
  • Fix pybench benchmark (update to perf 0.7.4 API)
  • performance now tries to install the psutil module on CPython for better system metrics in metadata and CPU pinning on Python 2.
  • The creation of the virtual environment now also tries virtualenv and venv Python modules, not only the virtualenv command.
  • The development version of performance now installs performance with “pip install -e <path_to_performance>”
  • The GitHub project was renamed from python/benchmarks to python/performance.

Version 0.1.1 (2016-08-24)

  • Fix the creation of the virtual environment
  • Rename pybenchmarks script to pyperformance
  • Add -p/–python command line option
  • Add __main__ module to be able to run: python3 -m performance

Version 0.1 (2016-08-24)

  • First release after the conversion to the perf module and move to GitHub
  • Removed benchmarks
    • django_v2, django_v3
    • rietveld
    • spitfire (and psyco): Spitfire is not available on PyPI
    • pystone
    • gcbench
    • tuple_gc_hell

History

Projected moved to https://github.com/python/performance in August 2016. Files reorganized, benchmarks patched to use the perf module to run benchmark in multiple processes.

Project started in December 2008 by Collin Winter and Jeffrey Yasskin for the Unladen Swallow project. The project was hosted at https://hg.python.org/benchmarks until Feb 2016

Release History

Release History

0.5.0

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.4.0

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.3.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.3.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.3.0

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.1.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.1.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
performance-0.5.0-py3-none-any.whl (2.5 MB) Copy SHA256 Checksum SHA256 3.5 Wheel Nov 15, 2016
performance-0.5.0.tar.gz (2.5 MB) Copy SHA256 Checksum SHA256 Source Nov 15, 2016

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS HPE HPE Development Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting