python anaconda 3 install simplehttpserver mac

#Python anaconda 3 install simplehttpserver mac how to#
#Python anaconda 3 install simplehttpserver mac mac#

While we continue to support Python 2.7 installations for the time being, this will not continue indefinitely.īelow we offer guidance for installing the Python 2.7 version alongside Python 3 using Anaconda, and for installing without Anaconda, with notes on dependencies. We highly recommend using the Anaconda Python 3.7 Distribution using the straightforward instructions provided above.

The optional -dirty flag indicates that the local repository has uncommitted changes.

The next is the hash of the most recent commit.

The second part is the number of commits since the tag.

The first part is the most recent release tag.

Note: When using a developer install topicexplorer version will print in the following format: 1.0b39-1-g7c834bf-dirty. This will ensure that we can quickly diagnose your issue. In your report, please include the error message, the command you ran, your operating system, and the output of the command topicexplorer version. Please report issues on the issue tracker or contact Jaimie directly (contact info at bottom of README).

#Python anaconda 3 install simplehttpserver mac how to#

See the sample configuration files in the config directory for examples of how to extend the topic explorer. Launch the topic explorer: topicexplorer launch CONFIG

Train LDA models using the on-screen instructions: topicexplorer train CONFIG This will generate a configuration file called CONFIG.

Initialize the Topic Explorer on a file, folder of text files, or folder of folders: topicexplorer init PATH

Test installation by typing topicexplorer -h to print usage instructions.

Open a terminal and run pip install -src.

Install the Anaconda Python 3.7 Distribution.

Test installation by typing topicexplorer -h to print usage instructions. When the 1.0 release happens, -pre will no longer be necessary. Open a Terminal (Mac and Linux) or PowerShell (Windows). (Windows users: during installation, during 'Advanced Options' choose 'Add Anaconda to my PATH environment variable' and don't worry about the warning.) Go to the Anaconda website and choose the Python 3.7 Distribution. Default Install (Windows users should use Developer Install until further notice) Our pypi server requires port 8080 to be accessible, and this is sometimes blocked on public networks. Note: If you attempt to install this while connected to the Internet by way of a restricted network (such as eduroam) you may experience difficulty.

#Python anaconda 3 install simplehttpserver mac mac#

Before installing, Mac users should install XCode from Apple and Windows users should install a Python compiler such as Microsoft Visual C_ Compiler Currently we are debugging the Windows Default installation. There are two types of install: Default and Developer. The original sort order can be restored with the 'Reset Topic Sort' button. When a topic is selected, clicking 'Top Documents for ' will take you to a new page showing the most similar documents to that topic's word distribution. By clicking a topic, the documents will reorder acoording to that topic's weight and topic bars will reorder according to the topic weights in the highest weighted document. By normalizing topics, the combined width of each bar expands so that topic weights per document can be compared. Each topic's label and color is arbitrarily assigned, but is consistent across articles in the browser.ĭisplay options include topic normalization, alphabetical sort and topic sort. The total width of each row indicates similarity to the focal topic or document, measured by the quantity sim(doc) = 1 – JSD(doc, focus entity), where JSD is the Jensen-Shannon distance between the word probability distributions of each item. The relative lengths of each segment of the bar indicates the weight of the topic in that document. Each document is represented by a multi-colored, horizontal bar representing the overall topic distribution for the document, with different colors representing the topics. The Hypershelf provides an interactive, document-centered visualization of the topic models. Live demos trained on the Stanford Encyclopedia of Philosophy, a selection of books from the HathiTrust Digital Library, and the original LDA training set of Associated Press articles are available at. More advanced analysis is made possible by a built-in pipeline to Jupyter (iPython) notebooks. The InPhO Topic Explorer provides an integrated system for text modeling making it simple to go from a set of documents to an interactive visualization of LDA topic models generated using the InPhO VSM module.