#!/usr/bin/env python
###### WARNING #######
### This script is obsoleted ###
### If you get it working again, please drop me a line
### F. Alted 2004-01-27
from tables import *
import numarray as NA
import struct, sys
import cPickle
try:
    # For Python 2.3
    from bsddb import db
except ImportError:
    # For earlier Pythons w/distutils pybsddb
    from bsddb3 import db
import psyco


# This class is accessible only for the examples
class Small(IsDescription):
    """ A record has several columns. They are represented here as
    class attributes, whose names are the column names and their
    values will become their types. The IsColDescr class will take care
    the user will not add any new variables and that its type is
    correct."""

    var1 = StringCol(itemsize=16)
    var2 = Int32Col()
    var3 = Float64Col()

# Define a user record to characterize some kind of particles
class Medium(IsDescription):
    name        = StringCol(itemsize=16, pos=0)  # 16-character String
    #float1      = Float64Col(shape=2, dflt=2.3)
    float1      = Float64Col(dflt=1.3, pos=1)
    float2      = Float64Col(dflt=2.3, pos=2)
    ADCcount    = Int16Col(pos=3)    # signed short integer
    grid_i      = Int32Col(pos=4)    # integer
    grid_j      = Int32Col(pos=5)    # integer
    pressure    = Float32Col(pos=6)    # float  (single-precision)
    energy      = Float64Col(pos=7)    # double (double-precision)

# Define a user record to characterize some kind of particles
class Big(IsDescription):
    name        = StringCol(itemsize=16)  # 16-character String
    #float1      = Float64Col(shape=32, dflt=NA.arange(32))
    #float2      = Float64Col(shape=32, dflt=NA.arange(32))
    float1      = Float64Col(shape=32, dflt=range(32))
    float2      = Float64Col(shape=32, dflt=[2.2]*32)
    ADCcount    = Int16Col()    # signed short integer
    grid_i      = Int32Col()    # integer
    grid_j      = Int32Col()    # integer
    pressure    = Float32Col()    # float  (single-precision)
    energy      = Float64Col()    # double (double-precision)

def createFile(filename, totalrows, recsize, verbose):

    # Open a 'n'ew file
    dd = db.DB()
    if recsize == "big":
        isrec = Description(Big)
    elif recsize == "medium":
        isrec = Medium()
    else:
        isrec = Description(Small)
    #dd.set_re_len(struct.calcsize(isrec._v_fmt))  # fixed length records
    dd.open(filename, db.DB_RECNO, db.DB_CREATE | db.DB_TRUNCATE)

    rowswritten = 0
    # Get the record object associated with the new table
    if recsize == "big":
        isrec = Big()
        arr = NA.array(NA.arange(32), type=NA.Float64)
        arr2 = NA.array(NA.arange(32), type=NA.Float64)
    elif recsize == "medium":
        isrec = Medium()
        arr = NA.array(NA.arange(2), type=NA.Float64)
    else:
        isrec = Small()
    #print d
    # Fill the table
    if recsize == "big" or recsize == "medium":
        d = {"name": " ",
             "float1": 1.0,
             "float2": 2.0,
             "ADCcount": 12,
             "grid_i": 1,
             "grid_j": 1,
             "pressure": 1.9,
             "energy": 1.8,
             }
        for i in xrange(totalrows):
            #d['name']  = 'Particle: %6d' % (i)
            #d['TDCcount'] = i % 256
            d['ADCcount'] = (i * 256) % (1 << 16)
            if recsize == "big":
                #d.float1 = NA.array([i]*32, NA.Float64)
                #d.float2 = NA.array([i**2]*32, NA.Float64)
                arr[0] = 1.1
                d['float1'] = arr
                arr2[0] = 2.2
                d['float2'] = arr2
                pass
            else:
                d['float1'] = float(i)
                d['float2'] = float(i)
            d['grid_i'] = i
            d['grid_j'] = 10 - i
            d['pressure'] = float(i*i)
            d['energy'] = d['pressure']
            dd.append(cPickle.dumps(d))
#             dd.append(struct.pack(isrec._v_fmt,
#                                   d['name'], d['float1'], d['float2'],
#                                   d['ADCcount'],
#                                   d['grid_i'], d['grid_j'],
#                                   d['pressure'],  d['energy']))
    else:
        d = {"var1": " ", "var2": 1, "var3": 12.1e10}
        for i in xrange(totalrows):
            d['var1'] = str(i)
            d['var2'] = i
            d['var3'] = 12.1e10
            dd.append(cPickle.dumps(d))
            #dd.append(struct.pack(isrec._v_fmt, d['var1'], d['var2'], d['var3']))

    rowswritten += totalrows


    # Close the file
    dd.close()
    return (rowswritten, struct.calcsize(isrec._v_fmt))

def readFile(filename, recsize, verbose):
    # Open the HDF5 file in read-only mode
    #fileh = shelve.open(filename, "r")
    dd = db.DB()
    if recsize == "big":
        isrec = Big()
    elif recsize == "medium":
        isrec = Medium()
    else:
        isrec = Small()
    #dd.set_re_len(struct.calcsize(isrec._v_fmt))  # fixed length records
    #dd.set_re_pad('-') # sets the pad character...
    #dd.set_re_pad(45)  # ...test both int and char
    dd.open(filename, db.DB_RECNO)
    if recsize == "big" or recsize == "medium":
        print isrec._v_fmt
        c = dd.cursor()
        rec = c.first()
        e = []
        while rec:
            record = cPickle.loads(rec[1])
            #record = struct.unpack(isrec._v_fmt, rec[1])
            #if verbose:
            #    print record
            if record['grid_i'] < 20:
                e.append(record['grid_j'])
            #if record[4] < 20:
            #    e.append(record[5])
            rec = c.next()
    else:
        print isrec._v_fmt
        #e = [ t[1] for t in fileh[table] if t[1] < 20 ]
        c = dd.cursor()
        rec = c.first()
        e = []
        while rec:
            record = cPickle.loads(rec[1])
            #record = struct.unpack(isrec._v_fmt, rec[1])
            #if verbose:
            #    print record
            if record['var2'] < 20:
                e.append(record['var1'])
            #if record[1] < 20:
            #    e.append(record[2])
            rec = c.next()

    print "resulting selection list ==>", e
    print "last record read ==>", record
    print "Total selected records ==> ", len(e)

    # Close the file (eventually destroy the extended type)
    dd.close()


# Add code to test here
if __name__=="__main__":
    import sys
    import getopt
    import time

    usage = """usage: %s [-v] [-s recsize] [-i iterations] file
            -v verbose
            -s use [big] record, [medium] or [small]
            -i sets the number of rows in each table\n""" % sys.argv[0]

    try:
        opts, pargs = getopt.getopt(sys.argv[1:], 's:vi:')
    except:
        sys.stderr.write(usage)
        sys.exit(0)

    # if we pass too much parameters, abort
    if len(pargs) <> 1:
        sys.stderr.write(usage)
        sys.exit(0)

    # default options
    recsize = "medium"
    iterations = 100
    verbose = 0

    # Get the options
    for option in opts:
        if option[0] == '-s':
            recsize = option[1]
            if recsize not in ["big", "medium", "small"]:
                sys.stderr.write(usage)
                sys.exit(0)
        elif option[0] == '-i':
            iterations = int(option[1])
        elif option[0] == '-v':
            verbose = 1

    # Catch the hdf5 file passed as the last argument
    file = pargs[0]

    t1 = time.clock()
    psyco.bind(createFile)
    (rowsw, rowsz) = createFile(file, iterations, recsize, verbose)
    t2 = time.clock()
    tapprows = round(t2-t1, 3)

    t1 = time.clock()
    psyco.bind(readFile)
    readFile(file, recsize, verbose)
    t2 = time.clock()
    treadrows = round(t2-t1, 3)

    print "Rows written:", rowsw, " Row size:", rowsz
    print "Time appending rows:", tapprows
    if tapprows > 0.:
        print "Write rows/sec: ", int(iterations / float(tapprows))
        print "Write KB/s :", int(rowsw * rowsz / (tapprows * 1024))
    print "Time reading rows:", treadrows
    if treadrows > 0.:
        print "Read rows/sec: ", int(iterations / float(treadrows))
        print "Read KB/s :", int(rowsw * rowsz / (treadrows * 1024))
