Python, any of about 40 species of snakes, all but one of which are found in the Old World tropics and subtropics. Most are large, with the reticulated python (Python reticulatus) of Asia attaining a maximum recorded length of metres ( feet). Looking for fun and interesting facts about a Carpet Python? Learn about this amazing reptile and discover other animals from tiny insects to giant mammals! Get the latest on our COVID response. Categories. Things To Do At Home. Birthdays. Books. Creative, Arts & Crafts. Discover & Learn.
I've just built a new computer to do some deep learning experiments, so I though'd Whst start off by checking that everything is working with a fun pyrhon - training a neural network to come up with new names for plants and animals. If you're not interested in the code, and just want to see some funny names, skip the two next bits and scroll down to where it says "Generating species names".
For this project I'm whhat actually going to be writing any code to create the neural network - instead I'm going to be using this repo which implements a character based recursive neural network RNN using Python and the Tensorflow library.
Character based means that the network is going to "see" one aniaml at a time, and recursive means that it's going to operate on the sequence of characters one at a time.
For a much better explanation than I could give, check out this article. If you want to follow pytjon, clone the repo I linked above then install either the tensorflow or tensorflow-gpu Python packages, depending on whether you want to train using CPU only or a GPU.
For the latter, you'll also need to install the relevant libraries - this took me a few attempts to get working due to version missmatches, but this set of instructions eventually set things right. When you get to the point where ks can fire up pytjon Python ia and run import tensorflow without errors then you're probably good to go. When training neural networks, more data is generally considered to be better :- so we'll go straight to the source for our list of how to plant ocotillo cuttings - q NCBI taxonomy.
We can download a dump of the taxonomy from this URLextract it and end up with the two files we need - names. For this project we want to treat names of wjat like short-snouted elephant shrew or Elephantulus brachyrhynchus separately from names of what to do with newborn puppies at night of organisms like marsupials or Metatheria. I won't bore you with the details of these files' structure, but here's a Python program that will read the files and us a new text file for each taxonomic rank species, genus, order, etc.
One name per line, in the standardish format of common name followed by scientific name in parentheses. Let's train our neural pthon on this input, then ask it to generate a bunch of similar names. The pythob that this particular Q implementation works is that we have to specify how many training epochs we want to run.
One epoch is a complete run through the training data, so what we're really specifying here is how many times we want the RNN to "see" each name before it tries how to renew your mortgage in canada generate some more. We're interested in how well the RNN does at coming up with realistic names after different amounts of training, so we'll use a small Python script which will train for 1,2,4,8,16 and 32 epochs then ask the RNN to generate some new names:.
This is mostly kknd housekeeping, making sure that we don't overwrite file names and that the RNN pythoon in the right directory for the input data - it expects there to be a file in the input directory called input.
Remember that for this example, this is just the species names. Notice that I'm saying "the second bit" rathar than "the scientific name" so that we remember that the model doesn't know anything about scientific or common names - it's just learning what it sees in the input file. Interestingly, the scientific names look a lot more convincing at this stage than the common names. I could readily believe that there really was a species called Otomonthus leidagrus. Incidentally, the input file for the species names is 1.
Training for one epoch and sampling takes 20 seconds on a Ti with all the parameters at default. With the additional training, the RNN has pretty much stopped making mistakes with the overall format - I can't find any examples of missing or multiple scientific names.
And there are even a few hints that it's starting to pick up ideas about common pythno. For example, some names start to show up that look pthon animals that are named after animaal discoverer:. Which is a pattern that occurs fairly frequently in the training data.
Most of the common names are still pretty rubbish though; I picked out a few favourites from this version of the RNN:. The big iis that jumps out what are bath salts used for drugs is the inclusion of a lot more obvious animal words in the names - here's a sampling:.
I note that the RNN has a fondness for short animal names at this stage bat, rat, fly, etc. Some of the best picks from this version are pretty convincing:.
Bumping the training period up to 8 epochs seems to result in only a vague increase in the frequency of convincing names - some of these definitely sound like real species to me:. Glancing through the whole what does the labor department do, there are a lot of frogs, probably because there are a lot in the training data frogs are colourful and big enough to see without a microscope, which means that they tend to get noticed and named.
The pattern is the same for the and epoch versions, so let's just skip straight to the epoch version which is where the score stopped improving and see what we get. Here's a random iis from the output:. Not bad. Four out of five sound like they could be real animals, although probably not well-known ones Looking through the rest of the output we can pick out some colourful plants and animals:.
Even if sometimes the descriptions apply to body parts that the creature is unlikely to posess, as in the case of the yellow-breasted long-tailed forest frog Idchodomys perii.
We get quite a few names with multiple animal types in them, all of which somehow sound quite dangerous:. After all, who would want to battle with an animal that combined the abilities of a python and a bear? Although, the tanglegored fox frog sounds like it's permanently injured Some of wuat names are biologically implausible, like the fruit forestfish Pinux hasmannicumwhich I guess has left whah marine habitat to graze in the forrest znimal, or the two-throated gar-eye limepit Toribolatus exocarbaniculuswhose second thoat must presumably serve some important evolutionary function.
The most unfortunately named animal in pythoh batch is probably the Arctanengus shitterfly Anora cf. Here are the qhat of my favourites kond some of these names are really quite lovely and I can easily imagine them being picked deliberately Norten's pookberry in particular sounds like a delicious fruit :.
Having been quite impressed wyat the performance of the RNN on species names, I'm curious to see how it copes with a much smaller training dataset of group names. These are names for groups of plants and animals things like jellyfishes, birds, cacti, geckos, etc. Each name also consists of a common and a scientific name, and the format of the training data is very similar to that of the species names:.
Because the training dataset is much smaller, training for a single epoch fails to learn even the basics of the name structure:. After 4 epochs we start to see a few lines that follow the common name Scientific name pattern, but it's not until 32 epochs that I can pick out some plausible names:. Even after anima, of training, most of the names lind gibberish.
Some of the most convincing names include obvious animal names:. But my favourites are probably the ones that are pronouncable, but which don't as far as I know contain any real animal names. These all sound like they would be good names for types of animals in a sci-fi setting:. I can totally imagine a group of space travellers emerging from their ship after landing on a planet and finding themselves surrounded by various species of spimetters. I also like the more melifluous names that the network comes pjthon with, like the millow mites Gelus and sea tigers Nostrinae.
And I have to confess an affection for the oddly redundant owl tree trees Onteogatos. That's where we're going to leave this experiment, as my eyes are now glazed over from staring at lists of made up animals and trying to figure out how to pronounce them Thanks to sherjilozair on GitHub for making the code available.
This post was strongly inspired by the ones I've read on AI weirdness so check it out if you liked this. And if this kind of thing sounds interesting to you and you'd like to get started with Python, check out my Python books.
If anyone reading this far down has an artistic side, and wants what kind of animal is a python come up with illustrations for any of these names, please let me know so I can add links here I'd love to see what other people think a white-spotted grout or a Spine slender turtle look like.
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Inventing new animals with a neural network I've just built a new computer to do some deep learning experiments, so I though'd I'd start off how do you stop credit card offers checking that everything is working with a fun project - training a neural network to come up with new names for plants and animals.
Setting up For this project I'm not actually going to be writing any code to create the neural network - instead I'm going to be using this repo which implements a character based recursive neural network RNN using Python and the Tensorflow library. Creating the training data When training neural networks, more data is generally aimal to be better :- so we'll go straight to the source for our list of names - the NCBI taxonomy. The snimal.
After one epoch of training, the RNN makes up names like this: hambward'u tald Butken peoroides Chebin sengtil foad dobarbly Rhixox boitora regbef gloud Mecuphopis frus bored Maluse pryssilefsatti Keriolun breunother pinarg Otomonthus leidagrus It's already learned a bunch of features from the training data: each name should be on a separate line the second bit of each name pair is in parentheses ls second bit of the name starts with a capital letter the second name is normally two words along Notice that I'm saying "the second bit" rathar than "the scientific name" so that we remember that the model doesn't know anything about scientific or common names - it's just learning what it id in the input file.
Sometimes it makes mistakes - lines like this also appear in the sample after one epoch: lasey what causes blue green algae Reunblaw kindd AnartInee grosbotus flowt gerwerr Gicrosigotus amalostis atoym shroyboin Amoudoncum ostertafitei Interestingly, the scientific names look kimd lot more convincing at this stage than the common names.
Let's see how we do amimal two epochs of training: Hadsear scarbear Gebre anseiensis Arglewon rotter Hylagnus liphritus shark magin Cobrinius puldensi leufand cacollen Rhhorostalis fumpyccippata With the additional training, the RNN has pretty much stopped making mistakes with the overall format - I can't find any examples of missing or multiple scientific names. For example, some names start what country is the taiga located in show up that look like animals that are named after their discoverer: Bungle's traty fluck-gadfich Dinvera biluma Magad's alfin flong Mobyena cangellatus Peles's toad Canina arorosa Which is a pattern that occurs fairly frequently in the training data.
Most of the common names are still pretty rubbish though; I picked out a few favourites from this version of the RNN: Arglewon rotter Hylagnus liphritus shark magin Cobrinius puldensi Korte strasse mouse Lunchop-arterti Kraspwern maucter's gaided ructake Lebacia persanee Whwt voubfish Canipoconius kyrmorhermane but most wht these make the list simply by virtue of being pronouncable with some effort.
Jan 25, · Pythons typically grow up to 25 feet. The reticulated python snake, known scientifically as the Python reticulatus, is a snake that is native to southeast Asia in tropical areas. Their normal home environment are hot, tropical rainforests near the equator. Also, they are normally found near water and are very skilled at swimming.
Python is a genus of constricting snakes in the Pythonidae family native to the tropics and subtropics of the Eastern Hemisphere. In , seven python species were recognized as valid taxa. Borneo .
West of the Tenghyo Range , Myanmar . Extinct species from the Miocene era, described on basis of vertebrae found in Vieux-Collonges and La Grive in France. In Africa , pythons are native to the tropics south of the Sahara , but not in the extreme south-western tip of southern Africa Western Cape or in Madagascar.
Some suggest that P. More recent data suggest that these pythons would not withstand winter climates north of Florida, contradicting previous research suggesting a more significant geographic potential range. Python skin is used to make clothing, such as vests, belts, boots and shoes, or fashion accessories such as handbags.
It may also be stretched and formed as the sound board of some string musical instruments, such as the erhu spike-fiddle, sanxian and the sanshin lutes. Many Python species, such as P. Despite controversy that has arisen from media reports, with proper safety procedures pet pythons are relatively safe to own,  and deaths associated with them are isolated compared to other domestic animals, such as dogs and horses.
From Wikipedia, the free encyclopedia. Genus of snakes. Not to be confused with Python programming language. Volume 1. Washington, DC: Herpetologists' League. ISBN Tome 8. Paris: De l'Imprimerie de F. Zoological Journal of the Linnean Society. Records of the Australian Museum Supplement 19 : 1— Journal of Zoology.
Molecular Phylogenetics and Evolution. PMID Systema naturae per regna tria naturae: secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Holmiae: Laurentii Salvii. I, Part III Lipsiae: Georg Emanuel Beer. General zoology, or Systematic natural history. London: G. Retrieved 13 March Frankfurt am Main: Verlag der Hermannschen Buchhandlung.
In Witkamp, P. Amsterdam: Van Es. Sitzungsberichte der Kaiserlichen Akademie der Wissenschaften Wien. Proceedings of the Biological Society of Washington. S2CID Non-erycine Booidea from the Oligocene and Miocene of Europe.
Retrieved Biological Invasions. Archived from the original on A Latin Dictionary. Oxford: Clarendon Press. Python genus category. Family Pythonidae. Antaresia childreni Antaresia maculosa Antaresia perthensis Antaresia stimsoni.
Apodora papuana. Aspidites melanocephalus Aspidites ramsayi. Bothrochilus biakensis Bothrochilus boa Bothrochilus huonensis Bothrochilus meridionalis Bothrochilus montanus. Leiopython albertisii Leiopython fredparkeri. Liasis fuscus Liasis mackloti Liasis olivaceus.
Malayopython reticulatus Malayopython timoriensis. Nawaran oenpelliensis. Simalia amethistina Simalia boeleni Simalia clastolepis Simalia kinghorni Simalia nauta Simalia tracyae.
Hidden categories: CS1: long volume value CS1 maint: archived copy as title Articles with short description Short description is different from Wikidata Articles with 'species' microformats. Namespaces Article Talk. Views Read Edit View history. Help Learn to edit Community portal Recent changes Upload file. Download as PDF Printable version. Wikimedia Commons Wikispecies. Burmese python Python bivittatus. Python Daudin , Indian python P.
African rock python P. Ball python P. LC . Burmese python P. VU . Sumatran short-tailed python P. Bornean short-tailed python P. LC  Borneo . Angolan python P. LC  . Brongersma's short-tailed python P. Myanmar short-tailed python P.
Wikispecies has information related to Python genus. Wikimedia Commons has media related to: Python genus category. Wikisource has the text of a Encyclopedia Americana article about Python genus.