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COLLECTED BY
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
ArchiveBot is an IRC bot designed to automate the archival of smaller websites (e.g. up to a few hundred thousand URLs). You give it a URL to start at, and it grabs all content under that URL, records it in a WARC, and then uploads that WARC to ArchiveTeam servers for eventual injection into the Internet Archive (or other archive sites).
To use ArchiveBot, drop by #archivebot on EFNet. To interact with ArchiveBot, you issue commands by typing it into the channel. Note you will need channel operator permissions in order to issue archiving jobs. The dashboard shows the sites being downloaded currently.
There is a dashboard running for the archivebot process at http://www.archivebot.com.
ArchiveBot's source code can be found at https://github.com/ArchiveTeam/ArchiveBot.
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Python Data Science Handbook: full text in Jupyter Notebooks
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This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.
Read the book in its entirety online at https://jakevdp.github.io/PythonDataScienceHandbook/
Run the code using the Jupyter notebooks available in this repository's notebooks directory.
Launch executable versions of these notebooks using Google Colab:
Launch a live notebook server with these notebooks using binder:
Buy the printed book through O'Reilly Media
The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages. Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, A Whirlwind Tour of Python: it's a fast-paced introduction to the Python language aimed at researchers and scientists.
See Index.ipynb for an index of the notebooks available to accompany the text.
The code in the book was tested with Python 3.5, though most (but not all) will also work correctly with Python 2.7 and other older Python versions.
The packages I used to run the code in the book are listed in requirements.txt (Note that some of these exact version numbers may not be available on your platform: you may have to tweak them for your own use). To install the requirements using conda, run the following at the command-line:
$ conda install --file requirements.txt
To create a stand-alone environment named PDSH with Python 3.5 and all the required package versions, run the following:
$ conda create -n PDSH python=3.5 --file requirements.txt
You can read more about using conda environments in the Managing Environments section of the conda documentation.
The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.
The text content of the book is released under the CC-BY-NC-ND license. Read more at Creative Commons.
