I’m a Chinese reader of book “Applied Spatial Data Analysis with R”, which is very useful for spatial analysis work. I tried to translate the R code into python with the Rpy2, since python can handle more complex data sources. But I have a problem with the Rpy2 code. The NY8 data is attached with the email.
The R code is:
library(rgdal)
NY8<-readOGR(".","NY8_utm18")
Syracuse<-NY8[NY8$AREANAME=="Syracuse city",]
Sy2_nb<-poly2nb(Syracuse,queen=FALSE)
library(spdep)
Sy2_nb<-poly2nb(Syracuse,queen=FALSE)
Sy2_lw<-nb2listw(Sy2_nb)
moran.plot(NY$POP8,Sy2_lw)
When I translate it with Rpy2, the code is:
>>> from rpy2.robjects.packages import importr
>>> utils = importr('utils')
>>> utils.install_packages('rgdal')
>>> rgdal=importr('rgdal')
>>> import os
>>> os.chdir("C:\\PYDATA\\NY")
>>> NY8=rgdal.readOGR(".","NY8_utm18")
>>> print(robjects.r['summary'](NY8))
When I want to translate the code “Syracuse<-NY8[NY8$AREANAME=="Syracuse city",]
”, for example:
>>>Syracuse=NY8[NY8$AREANAME=="Syracuse city",]
The error message is shown: SyntaxError: invalid syntax
It seems I could not extract the “AREANAME” through “$”, because “$” is illegal in python.
Could not get the accepted answer to work so wrote this function:
def subset_RS4(rs4, subset):
subset_func = r("""function(o, s){
o[s]
}
""")
return subset_func(rs4, subset)
Now you can call subset_RS4 with your object as the first arg and the subset as the other.
I am using it like this:
subset1 = r[">"](r["width"](peaks1), args.min_width)
print(subset_RS4(peaks1, subset1))
Use the method rx2 (https://rpy2.github.io/doc/latest/html/vector.html#extracting-r-style):
NY8.rx2("AREANAME")
If this an S4 object (your comment suggests so), a simple way to proceed is to fetch the generic "$" and use it as a function.
base = importr("base")
# "$" is not a syntactically valid name for a Python function,
# so we fetch it form the instance's dictionary of attributes
dollar = base.__dict__["$"]
dollar(NY8, "AREANAME")
Related
I am new to python and wanted to store the recentAveragePrice inside a variable (from a string like this one)
{"assetStock":null,"sales":250694,"numberRemaining":null,"recentAveragePrice":731,"originalPrice":null,"priceDataPoints":[{"value":661,"date":"2022-08-11T05:00:00Z"},{"value":592,"date":"2022-08-10T05:00:00Z"},{"value":443,"date":"2022-08-09T05:00:00Z"}],"volumeDataPoints":[{"value":155,"date":"2022-08-11T05:00:00Z"},{"value":4595,"date":"2022-08-10T05:00:00Z"},{"value":12675,"date":"2022-08-09T05:00:00Z"},{"value":22179,"date":"2022-08-08T05:00:00Z"},{"value":15181,"date":"2022-08-07T05:00:00Z"},{"value":14541,"date":"2022-08-06T05:00:00Z"},{"value":15310,"date":"2022-08-05T05:00:00Z"},{"value":14146,"date":"2022-08-04T05:00:00Z"},{"value":13083,"date":"2022-08-03T05:00:00Z"},{"value":14460,"date":"2022-08-02T05:00:00Z"},{"value":16809,"date":"2022-08-01T05:00:00Z"},{"value":17571,"date":"2022-07-31T05:00:00Z"},{"value":23907,"date":"2022-07-30T05:00:00Z"},{"value":39007,"date":"2022-07-29T05:00:00Z"},{"value":38823,"date":"2022-07-28T05:00:00Z"}]}
My current solution is this:
var = sampleStr[78] + sampleStr[79] + sampleStr[80]
It works for the current string but if the recentAveragePrice was above 999 it would stop working and i was wondering if instead of getting a fixed number i could search for it inside the string.
Your replit code shows that you're acquiring JSON data from some website. Here's an example based on the URL that you're using. It shows how you check the response status, acquire the JSON data as a Python dictionary then print a value associated with a particular key. If the key is missing, it will print None:
import requests
(r := requests.get('https://economy.roblox.com/v1/assets/10159617728/resale-data')).raise_for_status()
jdata = r.json()
print(jdata.get('recentAveragePrice'))
Output:
640
Since this is json you should just be able to parse it and access recentAveragePrice:
import json
sample_string = '''{"assetStock":null,"sales":250694,"numberRemaining":null,"recentAveragePrice":731,"originalPrice":null,"priceDataPoints":[{"value":661,"date":"2022-08-11T05:00:00Z"},{"value":592,"date":"2022-08-10T05:00:00Z"},{"value":443,"date":"2022-08-09T05:00:00Z"}],"volumeDataPoints":[{"value":155,"date":"2022-08-11T05:00:00Z"},{"value":4595,"date":"2022-08-10T05:00:00Z"},{"value":12675,"date":"2022-08-09T05:00:00Z"},{"value":22179,"date":"2022-08-08T05:00:00Z"},{"value":15181,"date":"2022-08-07T05:00:00Z"},{"value":14541,"date":"2022-08-06T05:00:00Z"},{"value":15310,"date":"2022-08-05T05:00:00Z"},{"value":14146,"date":"2022-08-04T05:00:00Z"},{"value":13083,"date":"2022-08-03T05:00:00Z"},{"value":14460,"date":"2022-08-02T05:00:00Z"},{"value":16809,"date":"2022-08-01T05:00:00Z"},{"value":17571,"date":"2022-07-31T05:00:00Z"},{"value":23907,"date":"2022-07-30T05:00:00Z"},{"value":39007,"date":"2022-07-29T05:00:00Z"},{"value":38823,"date":"2022-07-28T05:00:00Z"}]}'''
data = json.loads(sample_string)
recent_price = data['recentAveragePrice']
print(recent_price)
outputs:
731
Your data is in a popular format called JSON (JavaScript Object Notation). It's commonly used to exchange data between different systems like a server and a client, or a Python program and JavaScript program.
Now Python doesn't use JSON per-se, but it has a data type called a dictionary that behaves very similarly to JSON. You can access elements of a dictionary as simply as:
print(my_dictionary["recentAveragePrice"])
Python has a built-in library meant specifically to handle JSON data, and it includes a function called loads() that can convert a string into a Python dictionary. We'll use that.
Finally, putting all that together, here is a more robust program to help parse your string and pick out the data you need. Dictionaries can do a lot more cool stuff, so make sure you take a look at the links above.
# import the JSON library
# specifically, we import the `loads()` function, which will convert a JSON string into a Python object
from json import loads
# let's store your string in a variable
original_string = """
{"assetStock":null,"sales":250694,"numberRemaining":null,"recentAveragePrice":731,"originalPrice":null,"priceDataPoints":[{"value":661,"date":"2022-08-11T05:00:00Z"},{"value":592,"date":"2022-08-10T05:00:00Z"},{"value":443,"date":"2022-08-09T05:00:00Z"}],"volumeDataPoints":[{"value":155,"date":"2022-08-11T05:00:00Z"},{"value":4595,"date":"2022-08-10T05:00:00Z"},{"value":12675,"date":"2022-08-09T05:00:00Z"},{"value":22179,"date":"2022-08-08T05:00:00Z"},{"value":15181,"date":"2022-08-07T05:00:00Z"},{"value":14541,"date":"2022-08-06T05:00:00Z"},{"value":15310,"date":"2022-08-05T05:00:00Z"},{"value":14146,"date":"2022-08-04T05:00:00Z"},{"value":13083,"date":"2022-08-03T05:00:00Z"},{"value":14460,"date":"2022-08-02T05:00:00Z"},{"value":16809,"date":"2022-08-01T05:00:00Z"},{"value":17571,"date":"2022-07-31T05:00:00Z"},{"value":23907,"date":"2022-07-30T05:00:00Z"},{"value":39007,"date":"2022-07-29T05:00:00Z"},{"value":38823,"date":"2022-07-28T05:00:00Z"}]}
"""
# convert the string into a dictionary object
dictionary_object = loads(original_string)
# access the element you need
print(dictionary_object["recentAveragePrice"])
Output upon running this program:
$ python exp.py
731
I'm trying to get used to the redis-py Python module. I just can't figure out how the "mrange" function has to be used to get one or more Time-Series by its labels.
In the CLI it looks like this and it works:
TS.MRANGE - + FILTER area_id=32
But I can't get it to work in Python (one of many things that I tried):
import redis
r = redis.Redis()
r.ts().mrange("-","+","area_id:32")
r.ts().mrange("-","+",filters="area_id:32")
r.ts().mrange("-","+",filters='{area_id}32')
#And I tried many more...
I get the following Error:
ResponseError: TSDB: failed parsing labels
r.ts().mrange('-','+',['area_id=32'])
you need [square brackets]
I'm using Python 3 for this.
Basically, I'm making a API call using urllib and getting the error:
"ValueError: Single '}' encountered in format string"
I have looked at a variety of other solutions but they don't seem to work.
Basically what I am doing is:
import urllib.request
import urllib.parse
def query_person(first, last):
person_request = urllib.request.urlopen('http://api.querysite.com/content/search/index:AUTHOR?query=authlast%28%27{last}}%27%29%20AND%20authfirst%28%27{first}}%27%29&'.format(first=first,last=last))
return(person_request)
print(query_person("John", "Doe"))
The actual API will not be reproducible since it requires an API key (ommited obviously) as well as the need to be on a verified network.
I think the issue has to do with "{last}}%27%29%20AND%20authfirst%28%27{first}}" having an extra bracket. For example, if I wanted to just query it in my url bar without python or .format(), it would look like:
http://api.querysite.com/content/search/index:AUTHOR?query=authlast%28%27Doe}%27%29%20AND%20authfirst%28%27John}%27%29&
or more specifically: Doe}%27%29%20AND%20authfirst%28%27John}%27%29&
If I use the latter method in python, I have no issues, but it does not allow me to input names to query of course.
You need to double up on your single brace if you want it to remain in the string:
For example:
'{first}}}'.format(first='John') == 'John}'
In your case:
person_request = urllib.request.urlopen('http://api.querysite.com/content/search/index:AUTHOR?query=authlast%28%27{last}}}%27%29%20AND%20authfirst%28%27{first}}}%27%29&'.format(first=first,last=last))
I'm new to Biopython. Using this code:
handle = Entrez.esearch(db="nuccore", term="complete", field="title", FILT="refseq", porgn="viruses", rettype='xml')
print Entrez.read(handle)[u'QueryTranslation']
I get:
complete[Title]
but I'm expecting sth like this:
complete[Title] AND "viruses"[porgn]
(QueryTranslation from search results on http://www.ncbi.nlm.nih.gov/nuccore)
The refseq filter also seems not to work. What am I doing wrong?
Thanks in advance!
According to the current NCBI documentation, there are no options FILT or progrn - the NCBI is probably silently ignoring them (personally I'd prefer an explicit error message from them).
Based on the http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch you can now do
>>> from Bio import Entrez
>>> handle = Entrez.esearch(db="nuccore", term="complete", field="title", rettype='xml')
>>> print Entrez.read(handle)[u'QueryTranslation']
complete[Title]
as an alternative to:
>>> from Bio import Entrez
>>> handle = Entrez.esearch(db="nuccore", term="complete[title]", rettype='xml')
>>> print Entrez.read(handle)[u'QueryTranslation']
complete[Title]
That field option is (I'm petty sure) a new feature from the NCBI, but doesn't actually add any new functionality. It would seem to only make sense for trivial searches.
In order to do the complex search you appear to want, do this:
>>> from Bio import Entrez
>>> handle = Entrez.esearch(db="nuccore", term="complete[title] AND viruses[porgn]", rettype='xml')
>>> print Entrez.read(handle)[u'QueryTranslation']
complete[title] AND viruses[porgn]
There are examples like this in the Biopython Tutorial. See also http://news.open-bio.org/news/2009/06/ncbi-einfo-biopython/ (also now in the Biopython Tutorial).
I think you need to edit your term key word argument. You need to include AND viruses[porgn]
>>> handle = Entrez.esearch(db="nuccore", term="complete AND viruses[porgn]", field="title", FILT="refseq", rettype='xml')
>>> print Entrez.read(handle)[u'QueryTranslation']
complete[Title] AND viruses[porgn]
To add the RefSeq requirement too, you can do
>>> from Bio import Entrez
>>> handle = Entrez.esearch(db="nuccore", term="complete[title] AND refeq[filter] AND viruses[porgn]", rettype='xml')
I am writing a game in python and have decided to create a DSL for the map data files. I know I could write my own parser with regex, but I am wondering if there are existing python tools which can do this more easily, like re2c which is used in the PHP engine.
Some extra info:
Yes, I do need a DSL, and even if I didn't I still want the experience of building and using one in a project.
The DSL contains only data (declarative?), it doesn't get "executed". Most lines look like:
SOMETHING: !abc #123 #xyz/123
I just need to read the tree of data.
I've always been impressed by pyparsing. The author, Paul McGuire, is active on the python list/comp.lang.python and has always been very helpful with any queries concerning it.
Here's an approach that works really well.
abc= ONETHING( ... )
xyz= ANOTHERTHING( ... )
pqr= SOMETHING( this=abc, that=123, more=(xyz,123) )
Declarative. Easy-to-parse.
And...
It's actually Python. A few class declarations and the work is done. The DSL is actually class declarations.
What's important is that a DSL merely creates objects. When you define a DSL, first you have to start with an object model. Later, you put some syntax around that object model. You don't start with syntax, you start with the model.
Yes, there are many -- too many -- parsing tools, but none in the standard library.
From what what I saw PLY and SPARK are popular. PLY is like yacc, but you do everything in Python because you write your grammar in docstrings.
Personally, I like the concept of parser combinators (taken from functional programming), and I quite like pyparsing: you write your grammar and actions directly in python and it is easy to start with. I ended up producing my own tree node types with actions though, instead of using their default ParserElement type.
Otherwise, you can also use existing declarative language like YAML.
I have written something like this in work to read in SNMP notification definitions and automatically generate Java classes and SNMP MIB files from this. Using this little DSL, I could write 20 lines of my specification and it would generate roughly 80 lines of Java code and a 100 line MIB file.
To implement this, I actually just used straight Python string handling (split(), slicing etc) to parse the file. I find Pythons string capabilities to be adequate for most of my (simple) parsing needs.
Besides the libraries mentioned by others, if I were writing something more complex and needed proper parsing capabilities, I would probably use ANTLR, which supports Python (and other languages).
For "small languages" as the one you are describing, I use a simple split, shlex (mind that the # defines a comment) or regular expressions.
>>> line = 'SOMETHING: !abc #123 #xyz/123'
>>> line.split()
['SOMETHING:', '!abc', '#123', '#xyz/123']
>>> import shlex
>>> list(shlex.shlex(line))
['SOMETHING', ':', '!', 'abc', '#', '123']
The following is an example, as I do not know exactly what you are looking for.
>>> import re
>>> result = re.match(r'([A-Z]*): !([a-z]*) #([0-9]*) #([a-z0-9/]*)', line)
>>> result.groups()
('SOMETHING', 'abc', '123', 'xyz/123')
DSLs are a good thing, so you don't need to defend yourself :-)
However, have you considered an internal DSL ? These have so many pros versus external (parsed) DSLs that they're at least worth consideration. Mixing a DSL with the power of the native language really solves lots of the problems for you, and Python is not really bad at internal DSLs, with the with statement handy.
On the lines of declarative python, I wrote a helper module called 'bpyml' which lets you declare data in python in a more XML structured way without the verbose tags, it can be converted to/from XML too, but is valid python.
https://svn.blender.org/svnroot/bf-blender/trunk/blender/release/scripts/modules/bpyml.py
Example Use
http://wiki.blender.org/index.php/User:Ideasman42#Declarative_UI_In_Blender
Here is a simpler approach to solve it
What if I can extend python syntax with new operators to introduce new functionally to the language? For example, a new operator <=> for swapping the value of two variables.
How can I implement such behavior? Here comes AST module.
The last module is a handy tool for handling abstract syntax trees. What’s cool about this module is it allows me to write python code that generates a tree and then compiles it to python code.
Let’s say we want to compile a superset language (or python-like language) to python:
from :
a <=> b
to:
a , b = b , a
I need to convert my 'python like' source code into a list of tokens.
So I need a tokenizer, a lexical scanner for Python source code. Tokenize module
I may use the same meta-language to define both the grammar of new 'python-like' language and then build the structure of the abstract syntax tree AST
Why use AST?
AST is a much safer choice when evaluating untrusted code
manipulate the tree before executing the code Working on the Tree
from tokenize import untokenize, tokenize, NUMBER, STRING, NAME, OP, COMMA
import io
import ast
s = b"a <=> b\n" # i may read it from file
b = io.BytesIO(s)
g = tokenize(b.readline)
result = []
for token_num, token_val, _, _, _ in g:
# naive simple approach to compile a<=>b to a,b = b,a
if token_num == OP and token_val == '<=' and next(g).string == '>':
first = result.pop()
next_token = next(g)
second = (NAME, next_token.string)
result.extend([
first,
(COMMA, ','),
second,
(OP, '='),
second,
(COMMA, ','),
first,
])
else:
result.append((token_num, token_val))
src = untokenize(result).decode('utf-8')
exp = ast.parse(src)
code = compile(exp, filename='', mode='exec')
def my_swap(a, b):
global code
env = {
"a": a,
"b": b
}
exec(code, env)
return env['a'], env['b']
print(my_swap(1,10))
Other modules using AST, whose source code may be a useful reference:
textX-LS: A DSL used to describe a collection of shapes and draw it for us.
pony orm: You can write database queries using Python generators and lambdas with translate to SQL query sting—pony orm use AST under the hood
osso: Role Based Access Control a framework handle permissions.