def cover_search_2_images(path):
cover_search = OpenExcel(path)
if cover_search.read(
"A1") == "ENGLISH HERITAGE - NATIONAL MONUMENTS RECORD":
return type_one_cover_search_2_images(path)
elif cover_search.read("B13") == "Sortie number":
return type_two_cover_search_2_images(path)
elif cover_search.read("B10") == "Sortie number":
return type_two_cover_search_2_images(path)
else:
raise UnknownFormatError
class XLSXOpenExcel(IO):
def read(self, filename):
self.sheet = OpenExcel(filename)
self.row_count = self.sheet.read().nrows
self.col_count = self.sheet.read().ncols
def _float_to_string(self, sheet, col):
values = sheet.read(col)
if values[0] in self.column_names:
return values
for i, value in enumerate(values):
if isinstance(value, float):
values[i] = str(int(value))
elif isinstance(value, unicode):
values[i] = str(value)
return values
def column_heading_letter(self, heading_name):
for letter in self.column_letters():
if self.sheet.read(letter)[0] == heading_name:
return letter
@property
def column_names(self):
return tuple([
col[0] for col in [
self.sheet.sheets.col_values(i)
for i in range(self.sheet.getCols())
]
])
@property
def column_letters(self):
_letters = letters[26:]
num_cols = self.sheet.read().ncols
double_letters, triple_letters = ([], ) * 2
for l in _letters:
for m in _letters:
double_letters += [l + m]
for l in _letters:
for m in _letters:
for n in _letters:
triple_letters += [l + m + n]
_letters = list(_letters) + double_letters + triple_letters
res = zip(_letters, range(1, num_cols))
return tuple([r[0] for r in res])
def type_two_cover_search_2_images(path):
cover_search = OpenExcel(path)
row = 15
done = False
images = []
while not done:
row_data = cover_search.read(row)
if row_data[1] == "":
done = True
else:
new_image = AerialImage(row_data[1], int(row_data[2]),
int(row_data[4]), row_data[6],
int(row_data[8]), row_data[9],
row_data[12], int(row_data[14]),
int(row_data[15]), row_data[16])
images.append(new_image)
row += 1
return images
def type_one_cover_search_2_images(path):
cover_search = OpenExcel(path)
starts = []
for r in range(cover_search.getRows()):
pass
# Todo
row = 15
done = False
images = []
while not done:
row_data = cover_search.read(row)
if row_data[1] == "":
done = True
else:
new_image = AerialImage(row_data[1], int(row_data[2]),
int(row_data[4]), row_data[6],
int(row_data[8]), row_data[9],
row_data[12], int(row_data[14]),
int(row_data[15]), row_data[16])
images.append(new_image)
row += 1
return images
def analise_cover_search(path):
random_ref = hex(random.randint(1, 4294967296)).upper().strip("0X")
cover_search = OpenExcel(path)
data = cover_search.read()
# Find Table Starts
found_start = False
table_starts = []
sheet_width = cover_search.getCols()
sheet_height = cover_search.getRows()
for c in range(sheet_width):
for r in range(sheet_height):
cell_data = cover_search.read("{}{}".format(ALPHABET[c], r + 1))
if ("SORTIE" in str(cell_data).upper()) and (
"TOTAL" not in str(cell_data).upper()):
found_start = True
table_starts.append((c, r))
if found_start:
break
else:
pass
items = []
for start in table_starts:
headers = [] # To be list of (column, "header text")
current_row = start[1]
data_started = False
while not data_started:
current_row += 1
first_cell_address = "{}{}".format(ALPHABET[start[0]],
current_row + 1)
try:
cell_data = cover_search.read(first_cell_address)
except IndexError:
print("Failed at: {}".format(first_cell_address))
raise
if cell_data.count("/") > 0:
data_started = True
else:
pass
empty_cols = []
for c in range(sheet_width):
cell_data = cover_search.read("{}{}".format(
ALPHABET[c], current_row + 1))
if cell_data == "":
empty_cols.append(c)
else:
headers.append([ALPHABET[c], ""])
for c, h in enumerate(headers):
cell_data = cover_search.read("{}{}".format(h[0], start[1] + 1))
if cell_data == "":
headers[c][1] = "{}:{}".format(random_ref, [c][0])
else:
headers[c][1] = cell_data.strip()
data_started = False
data_finished = False
current_row = start[1] + 1
while not data_finished:
first_cell_address = "{}{}".format(headers[0][0], current_row + 1)
try:
cell_data = cover_search.read(first_cell_address)
except IndexError:
data_finished = True
break
if cell_data.count("/") > 0:
data_started = True
else:
pass
new_item = dict()
for i, h in enumerate(headers):
cell_address = "{}{}".format(h[0], current_row + 1)
cell_data = cover_search.read(cell_address)
if not data_started:
if cell_data != "":
headers[i][1] += " {}".format(cell_data)
else:
pass
else:
if (i == 0) and (cell_data.count("/") < 1):
data_finished = True
break
else:
new_item[h[1]] = cell_data
if new_item == dict():
pass
else:
new_item["originating_file"] = path
items.append(new_item)
current_row += 1
return items
#!/usr/bin/env python
from excel import OpenExcel
f = OpenExcel('namesdb.xls')
print f.read('A') # read 'A' row
print f.read('B')
print "{} is gender {}".format(f.read('A2'), f.read('B2'))
#!/usr/bin/python
from excel import OpenExcel
f = OpenExcel('namesdb.xls')
print f.read('A')
print f.read('B')
print f.read('A4')
#!/bin/python3
from excel import OpenExcel
fh = OpenExcel("/home/eddy/Downloads/financial_sample.xlsx")
print(fh.read("17B"))
# A package contains all the files you need for a module.
#
# Modules are Python code libraries you can include in your project.
# Check if PIP is Installed
# pip --version
# Download a Package
# Downloading a package is very easy.
#
# Open the command line interface and tell PIP to download the package you want.
#
# Navigate your command line to the location of Python's script directory, and type the following:
pip install Camelcase - This will install the camelcase package
"""
import camelcase
c = camelcase.CamelCase()
d = "hello world"
print(c.hump(d))
from humps.camel import case
print(case('madhu 2mallidi hyderabad'))
from excel import OpenExcel
f = OpenExcel('TEST.xlsx')
print(f.read('A')) # read 'A' row
self.weight = weight
self.layout = layout
self.coordinateX = coordinateX
self.coordinateY = coordinateY
self.bigVectorX = bigVectorX
self.bigVectorY = bigVectorY
self.smallVectorX = smallVectorX
self.smallVectorY = smallVectorY
self.startCorner = startCorner #I don't know maybe it's not necessary
self.axlesRelation = axlesRelation #I don't know maybe it's not necessary
self.bigR_axles = bigR_axles #I don't know maybe it's not necessary
self.smallR_axles = smallR_axles #I don't know maybe it's not necessary
# a = f.read() # read all
b = f.read('A') # read 'A' row
c = f.read(1) # f.read('1'), read '1' column
# d = f.read('A5')# read 'A5' position
# print (a)
print(b, "\n", type(b), "\n\n")
print(c, "\n", type(c))
# print (d)
nCols = len(b) # return number of columns
nRows = len(c) # return number of rows
print(nCols)
print(nRows)
#!/usr/bin/python
from excel import OpenExcel
f = OpenExcel('names.xls')
print f.read('A')
print "my name is {} and my gender is {}".format(f.read('A3'), f.read('B3'))
#!/usr/bin/env python
from excel import OpenExcel
f = OpenExcel('names.xls')
print f.read('A')
print f.read('B')
name=f.read('A3')
gender=f.read('B3')
print "my name is {} and gender is {}".format(name,gender)
def read_xls(xls_file):
from excel import OpenExcel
xls = OpenExcel(xls_file)
nrows = len(xls.read('A'))
for irow in range(1, nrows + 1):
yield xls.read(irow)
from excel import OpenExcel
f = OpenExcel('Zeszyt1.xls')
f.read() # read all
x = f.read('A') # read 'A' row
print(x)
f.read(1) # f.read('1'), read '1' column
f.read('A5') # read 'A5' position
#!/usr/bin/python
from excel import OpenExcel
f = OpenExcel('namesdb.xls')
print f.read('A2')
print f.read('B2')
print f.read('A')
print f.read('B')
#!/usr/bin/python
from excel import OpenExcel
f = OpenExcel('namesdb.xls')
#name = raw_input("please enter the name of the student:")
print f.read('A') # read 'A' row
print f.read('A7'), f.read('B7') # read 'A' row
#!/usr/bin/python
# https://github.com/tuxfux-hlp/Python-examples/blob/master/files/my_read.py
from excel import OpenExcel
f = OpenExcel('names.xls')
print f.read('A')
print f.read('B')
print "{} is a {}".format(f.read('A8'), f.read('B8'))
import math
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
from excel import OpenExcel
NAZWA_PLIKU = 'dane-covid-usa.xlsx'
print('Obliczanie regresji liniowej,')
print('dane są czytane z pliku', NAZWA_PLIKU)
rozszerzenie = NAZWA_PLIKU[-5:].lower()
if rozszerzenie == '.xlsx':
plik = OpenExcel(NAZWA_PLIKU)
x = plik.read('A')
y = plik.read('B')
for i in range(len(y)):
if type(y[i]) == str:
y[i] = float(y[i].replace('\xa0', ''))
x = np.array(x)
y = np.array(np.log10(y))
elif rozszerzenie == '.txt':
x, y = np.loadtxt(NAZWA_PLIKU, unpack=True)
else:
raise RuntimeError('nieznany typ pliku')
n = len(x)