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| # Reads: SLAllSort.csv # # Writes to: # DBTestM.csv # CalcList.csv # MultList.txt # MultSummary.txt |
== IronPython == IronPython is [[http://hugunin.net/index.html|JimHugunin's]] implementation of Python on the .NET CLR and on Mono. The project has a [[http://ironpython.codeplex.com/|workspace]] where you can get news and download the latest version. * Stable Version is 2.0.3 (targeting Python 2.5) * Developers Version is 2.6 Beta 3 (targeting Python 2.6) IronPython 2 (which uses the Dynamic Language Runtime, a framework for writing dynamic languages for .NET which was abstracted out of IronPython 1) runs on Silverlight, the Microsoft browser plugin that runs on Windows and the Mac (and a Mono port called Moonlight runs on Linux). This means that IronPython can be used for client-side scripting ''in the browser''. IronPython is a Python compiler. It compiles Python code to in memory bytecode before execution (which can be saved to disk, making binary only distributions possible). Performance is comparable to CPython - much faster for some things (where it can take advantage of the JIT compiler in the underlying platform), but slower for other things (particularly the built in container types where a lot of work has been done on optimising the CPython types). Reasons that CPython programmers might be interested in IronPython include: * Corporate credibility (introducing new technologies can be very difficult in some companies, if .NET is already established then you may need no excuse to start using IronPython) * No GlobalInterpreterLock - IronPython has ''no GIL'' and multi-threaded code can use multi core processors * The .NET framework library is ''very big''. Particularly the user interface library Windows Forms is very good. * IronPython is easy to embed in .NET applications as a scripting language * Easier to extend than CPython (C# is memory managed and C# types can be used directly in IronPython with no wrapping) * Silverlight! A book on IronPython for Python and .NET developers: [[http://www.ironpythoninaction.com/|IronPython in Action]]. A useful resource for IronPython code examples, is the [[http://www.ironpython.info|IronPython Cookbook]]. A book that introduces core concepts of IronPython programming using a .NET–centric approach is [[http://www.apress.com/book/view/9781430219620|Pro IronPython]]. [[http://www.zetcode.com/tutorials/ironpythontutorial/|IronPython Winforms tutorial]] at [[http://www.zetcode.com/|ZetCode]]. Mozilla announced a project to port the DLR (well, the underlying Core CLR that it uses in fact) to run on their Tamarin JIT. This means that IronPython could also run in future versions of Firefox. (See [[http://wiki.mozilla.org/Tamarin:IronMonkey|IronMonkey]]). Unfortunately this project has not made any progress since its announcement. == Other Python-Like Languages for .NET/Mono == Some other Python-like languages for .NET and Mono include: * BooLanguage - Syntax is very similar to Python's, yet the language is statically compiled. It implements many features that have been suggested for [[Python3.0]]. See [[http://boo.codehaus.org/Gotchas+for+Python+Users|Gotchas for Python Users]] for specific comparisons between boo and CPython. * [[http://cobra-language.com/|Cobra Language]] |
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| import os,sys from Tkinter import * from string import * from Permute import * |
== Accessing .NET from CPython == |
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| class FileCombo(Frame): | [[http://www.zope.org/Members/Brian/PythonNet/index_html|Python for .NET]] is the reverse of IronPython, it lets you access .NET assemblies from CPython. |
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| def __init__(self,parent=None): | ---- |
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| Frame.__init__(self,parent) print 'Choices are:' print ' 1. Convert Sorted Combined list to Species No. and Subspecies No' print ' creates DBTestM.csv ' print ' 2. Make two lists: All species detected - Species and All sites detected - Sites.' print ' Then Adds data from CDMS (Intensity,Smu2 and Einstein A) from DBTestM.csv' print ' creates CalcList.csv ' print ' 3. Reads CalcList.csv and identifies all lines in a site that have 3 or more lines' print ' creates MultList.txt and a Summary MultSummary.txt. ' print ' 4. Run each in sequence' ## Sel=raw_input('Choice') Ch=eval(Sel) if Ch==1: self.XDBAccess() exit() if Ch==2: self.MakeSiteList() self.CalculationList() quit() if Ch==3: self.FindMultiples() quit() if Ch==4: self.XDBAccess() self.MakeSiteList() self.CalculationList() self.FindMultiples() quit() def XDBAccess(self): # GoodCombineAllSorted is a combination of the three SLCombine files cleaned for errors. Sorted by: Species, RestF site. # Two columns are added at the beginning of each line of the form shown below. # The result is saved in Lines F1='/home/ghurtig3/Desktop/NewASAP_09/DATA/GoodCombineAllSorted.csv' FL1=open(F1,'r') sa=FL1.readlines() Lines2=[] la=len(sa) print len(sa) #Strip whitespaces i=0 while i < la: sb=sa[i].strip() Lines2.append(sb) i=i+1 continue Lines=[] #print len(Lines2) # Create a csv file Starting with [ 1, 0, Site, .....] i=0 for line in Lines2: line=line.split("\t") #line1=line[0][0:-1] #print line #Lis1="1"+","+"0"+"," Lis1= "0" line.insert(0,Lis1) Lis1="1" line.insert(0,Lis1) #print line #raw_input("Pause1") #Lines1=Lis1.split(",") #Now creatine file Lines Lines.append(line) i=i+1 continue #Lines[x][0]=Specie # #Lines[x][1]=Sub Specie #Lines[x][2]=Site #Lines[x][3]=Specie #Lines[x][4]=Rest Freq #Lines[x][5]=Obs Freq #Lines[x][6]=DelF #Lines[x][7]=Intensity #Lines[x][8]=FWHM #Lines[x][9]=DelV #Lines[x][10]=Area #Lines[x][11]=Offset #Lines[x][12]=Normalize FL1.close() #print i #raw_input("Pause2") # A sub specie is added to the masterdatabase and written to 'DBTestM.csv' i=0 #Line # LL=len(Lines) #print Lines #print LL #print Lines[LL-2] k=0 #SubSpecie # m=0 #Specie # while i< LL-3: #Line # #print "i= ",i if Lines[i][3]==Lines[i+1][3]: #Tests for specie change: Lines[i+1][1]=0 Lines[i][0]=m Lines[i+1][0]=m if Lines[i][4]==Lines[i+1][4]:#Tests for sub specie change Lines[i][1]=k Lines[i+1][1]=k else: Lines[i][1]=k Lines[i+1][1]=k+1 k=k+1 i=i+1 continue else: Lines[i+1][0]=m+1 Lines[i][1]=k k=0 Lines[i+1][1]=k m=m+1 k=k+1 i=i+1 #Lines[i][1]=k #k=0 continue print i, k, m raw_input("Pause3") F6='/home/ghurtig3/Desktop/NewASAP_09/DATA/DBTestM.csv' FL6=open(F6,'w') j=0 while j< LL-3: FR=str(Lines[j][0])+','+str(Lines[j][1])+','+str(Lines[j][2])+','+str(Lines[j][3])+','+str(Lines[j][4])+','+str(Lines[j][5])+','+str(Lines[j][6])+','+str(Lines[j][7])+','+str(Lines[j][8])+','+str(Lines[j][9])+','+str(Lines[j][10])+','+str(Lines[j][11])+"\n" FL6.write(FR) #print FR #print j #print Lines[j] #raw_input('Pause') j=j+1 continue FL6.close() return def MakeSiteList(self): # This creates two internal lists from DBTestM.csv. Species is # all of the species detected and Sites is all of the sites read. F1='/home/ghurtig3/Desktop/NewASAP_09/DATA/DBTestM.csv' FL1=open(F1,'r') Lines=[] Sites=[] Species=[] i=0 for line in FL1: line=line.split(',') Lines.append(line) if line[2] in Sites: i=i+1 continue else: Sites.append(line[2]) i=i+1 continue FL1.close() F1='/home/ghurtig3/Desktop/NewASAP_09/DATA/DBTestM.csv' FL1=open(F1,'r') i=0 for line in FL1: line=line.split(',') Lines.append(line) if line[3] in Species: i=i+1 continue else: Species.append(line[3]) i=i+1 continue FL1.close() self.Sites=Sites self.Species=Species print Sites print Species return def CalculationList(self): #This def takes the observation data that has been cleaned and put #into DBTestM.csv and combines each specie and sub-specie with the #data from CDMS (Intensity, Smu2 and Einsteins A. Puts data into # CalcList.csv. T1=[] F3='/home/ghurtig3/Desktop/NewASAP_09/DATA/DBTestM.csv' FL3=open(F3,'r') F2='/home/ghurtig3/Desktop/NewASAP_09/DATA/CalcList.csv' FL2=open(F2,'w') Lines=[] for line in FL3: T1.append("0") line1=line.split(',') Lines.append(line1) LL=len(Lines) print LL Sites=self.Sites A="" B="" print type(Sites) for Si in Sites: H1='Site= '+Si for Sp in self.Species: Head=' Species= '+Sp+'\n' i=1 while i< LL-1: if (Lines[i][2]==Si) and (Lines[i][3]==Sp): if (Lines[i][2] == A) is False: print '***** ',Lines[i][2],' *****' print Lines[i][3] Freq=eval(Lines[i][4]) L=Lines[i] E=L.pop() E=E[:-2] L.append(E) B=Lines[i][3] if((Lines[i][3]==B))is False: print Lines[i][3] Freq=eval(Lines[i][4]) L=Lines[i] E=L.pop() E=E[:-2] L.append(E) DBLine=self.ReadCDMS(Freq) print Freq if DBLine==None: DBLine=['Not in CDBMS'] print DBLine T1[i]=L+DBLine Ln=Lines[i] A=Lines[i][2] B=Lines[i][3] Ln=str(Ln) FL2.write(str(T1[i])+'\n') i=i+1 continue else: i=i+1 continue FL3.close() FL2.close() #Lines[x][0]=Specie # #Lines[x][1]=Sub Specie #Lines[x][2]=Site #Lines[x][3]=Specie #Lines[x][4]=Rest Freq #Lines[x][5]=Obs Freq #Lines[x][6]=DelF #Lines[x][7]=Intensity #Lines[x][8]=FWHM #Lines[x][9]=DelV #Lines[x][10]=Area #Lines[x][11]=Offset #Lines[x][12]=Normalize #Lines[x][13]=Rest Freq #Lines[x][14]=log(intensity) #Lines[x][15]=log(Smu2) #Lines[x][16]=log(A) #Lines[x][17]=El #Lines[x][18]=gup #Lines[x][19]=Quant Nos #Lines[x][20]=Species #Lines[x][21]=Vt #Lines[x][22]=V def FindMultiples(self): #This def is created by DBA.py and reads CalcList.csv #and then identifies all species that have 3 or more #lines in a site.It writes these in MultList.txt and #summarizes the data in MultSummary.txt #Species is entered at tests are reported. SP=raw_input('Species? ') F1='/home/ghurtig3/Desktop/NewASAP_09/DATA/MultList.txt' FL1=open(F1,'w') F2='/home/ghurtig3/Desktop/NewASAP_09/DATA/CalcList.csv' FL2=open(F2,'r') F3='/home/ghurtig3/Desktop/NewASAP_09/DATA/MultSummary.txt' FL3=open(F3,'w') F4='/home/ghurtig3/Desktop/NewASAP_09/DATA/MultLines.txt' FL4=open(F4,'w') Lines=[] Lines=FL2.readlines() LL=len(Lines) print LL L2=Lines[0].split(',') #print L2[2] N1=[] L4=[] N3=[] i=1 k=1 while i<LL: L1=Lines[i].split(',') if L1[12]==" ''": #Checks for a ratio. i=i+1 continue if L1[3]==L2[3]: k=k+1 if k==3: N1=[] FL1.write(Lines[i-2]+'\n') FL1.write(Lines[i-1]+'\n') FL1.write(Lines[i]+'\n') LM2=Lines[i-2].split(',') LM1=Lines[i-1].split(',') LM0=Lines[i].split(',') N6=LM2[12] N7=N6[1:] N7=N7[:-2] if N7 != "'Not in CDBMS'": N6=N6[1:] N6=eval(N6) N1.append(N6) N6=LM1[12] N7=N6[1:] N7=N7[:-2] if N7 != "'Not in CDBMS'": N6=N6[1:] N6=eval(N6) N1.append(N6) N6=LM0[12] N7=N6[1:] N7=N7[:-2] if N7 != "'Not in CDBMS'": N6=N6[1:] N6=eval(N6) N1.append(N6) if k>3: FL1.write(Lines[i]+'\n') #LM=Lines[i].split(',') N6=L1[12] N7=N6[1:] N7=N7[:-2] if N7 != "'Not in CDBMS'": N6=N6[1:] N6=eval(N6) N1.append(N6) L2=L1 i=i+1 continue else: if k>2: FL3.write(L2[2]+','+L2[3]+','+str(k)+'\n') L3=L2[3][2:] L3=L3[:-1] if L3==SP: N2=L2[2] N2=N2.replace('.','') N2=N2.replace('gau','') L4.append(N2) #L4 is a list of sites containing SP N3.append(N1) #N3 is a list of intensities for each site. k=1 L2=L1 i=i+1 continue FL1.close() FL2.close() FL3.close() #Perm(L4,N3)#Calculates pair statistics exit() def ReadCDMS(self,Freq): Lines1=[] Lines1=self.ReadCDMSData() DBLine=self.FindLine(Freq, Lines1) return DBLine def ReadCDMSData(self): F1='CDMS_ISA.txt' FL1=open(F1, 'r') Lines1=[] i=0 for line in FL1: line=capwords((line)) line=line.split(',') if line[0]=="": continue else: Lines1.append(line) i=i+1 continue return Lines1 def FindLine(self,Fr1,Lines1): #finds a line in the CDMS for a particular frequency. i=1 while i < len(Lines1): if abs(eval(Lines1[i][0])-Fr1)<0.25: #print Lines[i] return Lines1[i] else: i=i+1 continue #raw_input('P') return if __name__ == '__main__': FileCombo().mainloop() |
See also: PythonAndParrot, LoGix, IronPython IDE |
IronPython
IronPython is JimHugunin's implementation of Python on the .NET CLR and on Mono.
The project has a workspace where you can get news and download the latest version.
- Stable Version is 2.0.3 (targeting Python 2.5)
- Developers Version is 2.6 Beta 3 (targeting Python 2.6)
IronPython 2 (which uses the Dynamic Language Runtime, a framework for writing dynamic languages for .NET which was abstracted out of IronPython 1) runs on Silverlight, the Microsoft browser plugin that runs on Windows and the Mac (and a Mono port called Moonlight runs on Linux). This means that IronPython can be used for client-side scripting in the browser.
IronPython is a Python compiler. It compiles Python code to in memory bytecode before execution (which can be saved to disk, making binary only distributions possible).
Performance is comparable to CPython - much faster for some things (where it can take advantage of the JIT compiler in the underlying platform), but slower for other things (particularly the built in container types where a lot of work has been done on optimising the CPython types).
Reasons that CPython programmers might be interested in IronPython include:
Corporate credibility (introducing new technologies can be very difficult in some companies, if .NET is already established then you may need no excuse to start using IronPython)
No GlobalInterpreterLock - IronPython has no GIL and multi-threaded code can use multi core processors
The .NET framework library is very big. Particularly the user interface library Windows Forms is very good.
IronPython is easy to embed in .NET applications as a scripting language
Easier to extend than CPython (C# is memory managed and C# types can be used directly in IronPython with no wrapping)
- Silverlight!
A book on IronPython for Python and .NET developers: IronPython in Action.
A useful resource for IronPython code examples, is the IronPython Cookbook.
A book that introduces core concepts of IronPython programming using a .NET–centric approach is Pro IronPython.
IronPython Winforms tutorial at ZetCode.
Mozilla announced a project to port the DLR (well, the underlying Core CLR that it uses in fact) to run on their Tamarin JIT. This means that IronPython could also run in future versions of Firefox. (See IronMonkey). Unfortunately this project has not made any progress since its announcement.
Other Python-Like Languages for .NET/Mono
Some other Python-like languages for .NET and Mono include:
BooLanguage - Syntax is very similar to Python's, yet the language is statically compiled. It implements many features that have been suggested for Python3.0. See Gotchas for Python Users for specific comparisons between boo and CPython.
Accessing .NET from CPython
Python for .NET is the reverse of IronPython, it lets you access .NET assemblies from CPython.
See also: PythonAndParrot, LoGix, IronPython IDE