Python

I’ve been working on a Python port of the R package taxize that I maintain. It’s still early days with this Python library, I’d love to know what people think. For example, I’m giving back Pandas DataFrame’s from most functions. Does this make sense? Installation sudo pip install git+git://github.com/sckott/pytaxize.git#egg=pytaxize Or git clone the repo down, and python setup.py build && python setup.py install Load library import pytaxize ITIS ping pytaxize.itis_ping() 'This is the ITIS Web Service, providing access to the data behind www.itis.gov. The database contains 665,266 scientific names (501,207 of them valid/accepted) and 122,735 common names.' Get hierarchy down from tsn pytaxize.gethierarchydownfromtsn(tsn = 161030) tsn rankName taxonName parentName parentTsn 0 161048 Class Sarcopterygii Osteichthyes 161030 1 161061 Class Actinopterygii Osteichthyes 161030 Get hierarchy up from tsn pytaxize.gethierarchyupfromtsn(tsn = 37906) author parentName parentTsn rankName taxonName tsn 0 Gaertn. ex Schreb. Asteraceae 35420 Genus Liatris 37906 Get rank names pytaxize.getranknames() kingdomname rankid rankname 0 Bacteria 10 Kingdom 1 Bacteria 20 Subkingdom 2 Bacteria 30 Phylum 3 Bacteria 40 Subphylum 4 Bacteria 50 Superclass 5 Bacteria 60 Class 6 Bacteria 70 Subclass 7 Bacteria 80 Infraclass 8 Bacteria 90 Superorder 9 Bacteria 100 Order 10 Bacteria 110 Suborder 11 Bacteria 120 Infraorder 12 Bacteria 130 Superfamily 13 Bacteria 140 Family 14 Bacteria 150 Subfamily 15 Bacteria 160 Tribe 16 Bacteria 170 Subtribe 17 Bacteria 180 Genus 18 Bacteria 190 Subgenus 19 Bacteria 220 Species 20 Bacteria 230 Subspecies 21 Protozoa 10 Kingdom 22 Protozoa 20 Subkingdom 23 Protozoa 25 Infrakingdom 24 Protozoa 30 Phylum 25 Protozoa 40 Subphylum 26 Protozoa 45 Infraphylum 27 Protozoa 47 Parvphylum 28 Protozoa 50 Superclass 29 Protozoa 60 Class .. ... ... ... 150 Chromista 190 Subgenus 151 Chromista 200 Section 152 Chromista 210 Subsection 153 Chromista 220 Species 154 Chromista 230 Subspecies 155 Chromista 240 Variety 156 Chromista 250 Subvariety 157 Chromista 260 Form 158 Chromista 270 Subform 159 Archaea 10 Kingdom 160 Archaea 20 Subkingdom 161 Archaea 30 Phylum 162 Archaea 40 Subphylum 163 Archaea 50 Superclass 164 Archaea 60 Class 165 Archaea 70 Subclass 166 Archaea 80 Infraclass 167 Archaea 90 Superorder 168 Archaea 100 Order 169 Archaea 110 Suborder 170 Archaea 120 Infraorder 171 Archaea 130 Superfamily 172 Archaea 140 Family 173 Archaea 150 Subfamily 174 Archaea 160 Tribe 175 Archaea 170 Subtribe 176 Archaea 180 Genus 177 Archaea 190 Subgenus 178 Archaea 220 Species 179 Archaea 230 Subspecies Search by scientific name pytaxize.searchbyscientificname(x="Tardigrada") combinedname tsn 0 Rotaria tardigrada 58274 1 Notommata tardigrada 58898 2 Pilargis tardigrada 65562 3 Tardigrada 155166 4 Heterotardigrada 155167 5 Arthrotardigrada 155168 6 Mesotardigrada 155358 7 Eutardigrada 155362 8 Scytodes tardigrada 866744 Get accepted names from tsn pytaxize.getacceptednamesfromtsn('208527') If accepted, returns the same id ...

The Lagotto application is a Rails app that collects and serves up via RESTful API article level metrics data for research objects. So far, this application has only been applied to scholarly articles, but will see action on datasets soon. Martin Fenner has lead the development of Lagotto. He recently set up a discussion site if you want to chat about it. The application has a nice GUI interface, and a quite nice RESTful API. ...

Eduard Szöcs and I started developing a taxonomic toolbelt for the R language a while back , which lets you interact with a multitude of taxonomic databases on the web. We have a paper in F1000Research if you want to find out more (see here). I thought it would be fun to rewrite some of taxize in other languages to learn more languages. Ruby and Python made the most sense to try. I did try others (Julia, Node), but gave up on those for now. The goal here isn’t to port taxize to Python and Ruby right now - it’s for me to learn myself some coding. ...

Many R packages/tools have come out recently for doing ecology and evolution. All of the below were described in Methods in Ecology and Evolution, except for spider, which came out in Molecular Ecology Resources. Here are some highlights. mvabund paper - get R pkg Model-based analysis of multivariate abundance data. Visualising data, fitting predictive models, checking assumptions, hypothesis testing. popdemo paper - get R pkg Population demography using projection matrix analysis. motmot paper - get R pkg Models of trait macroevolution on trees spider paper - get R pkg Analysis of species identity and evolution, with particular reference to DNA barcoding BaSTA paper - get R pkg Bayesian estimation of age-specific survival from incomplete mark–recapture/recovery data with covariates abc paper - get R pkg Approximate Bayesian Computation (ABC) RNetLogo paper - get R pkg Running and exploring individual-based models implemented in NetLogo phytools paper - get R pkg Tools for phylogenetic comparative biology smatr paper - get R pkg Estimation and inference about allometric lines RBrownie paper - get R pkg ? Testing hypotheses about rates of evolutionary change polytomy resolver paper - get R pkg Resolve polytomies on dated phylogenies with their R scripts [here][]. And a cool tool came out for the Python programming language. ...