workbook data related operations

Access individual cells

WS = C [ ' A4 ' ] # returns the cell A4, if the cell does not exist, it is created automatically 
WS [ ' A4 ' ]. 4 =   # is assigned cell A4. 4 
    
D = ws.cell (Row =. 4, = 2 column, value = 10)   # to B4 assigned to the cell 10

　　When a worksheet created in memory, does not contain any cell, only when the first visit would be created
　　when the function to access large quantities of cells through cell (), although these cells have not been assigned yet these cells already created in memory

for X in Range (1,101 ):
     for Y in Range (1,101 ): 
        ws.cell (Row = X, Y = column) # creates 100 * 100 cells in memory

Access to multiple cells

CELL_RANGE = WS [ ' A1 ' : ' C2 ' ]   # access from A1 to C2 of all cells 

colC = WS [ ' C ' ]   # access column C all cells 
col_range = WS [ ' C: D ' ]   # access all the cells in column C and row D 

row10 = WS [10]   # all the cells of row 10 access 
row_range WS = [5:10]   # access line 5 to line 10 of all of the cells 

# use Worksheet.iter_rows () method to the behavior unit, traversing the plurality of cells 
for Row in ws.iter_rows (min_row =. 1, max_col =. 3, MAX_ROW = 2 ):
     for cell in row:
        print(cell)
'''
输出：
<Cell Sheet1.A1>
<Cell Sheet1.B1>
<Cell Sheet1.C1>
<Cell Sheet1.A2>
<Cell Sheet1.B2>
<Cell Sheet1.C2>
'''

#使用Worksheet.iter_cols()方法以列为单位,遍历多个单元格
for col in ws.iter_cols(min_row=1, max_col=3, max_row=2):
    for cell in col:
        print(cell)
'''
输出：
<Cell Sheet1.A1>
<Cell Sheet1.A2>
<Cell Sheet1.B1>
<Cell Sheet1.B2>
<Cell Sheet1.C1>
<Cell Sheet1.C2>
'''

　　For performance reasons, Worksheet.iter_cols () in read-only mode is not available
　　I think this may be because the size of the memory is limited, due to the size of the file can not be predicted in advance, if the file has a billion lines data
　　is iter_cols method at the time to traverse the file as a unit, the first to traverse the first column, may traverse the ten millionth row, memory is no longer enough

The bulk access cell

ws['C9'] = 'hello world'
tuple(ws.rows) #获取A1到C9的所有单元格，以行为单位
'''
输出：
((<Cell Sheet.A1>, <Cell Sheet.B1>, <Cell Sheet.C1>),
(<Cell Sheet.A2>, <Cell Sheet.B2>, <Cell Sheet.C2>),
(<Cell Sheet.A3>, <Cell Sheet.B3>, <Cell Sheet.C3>),
(<Cell Sheet.A4>, <Cell Sheet.B4>, <Cell Sheet.C4>),
(<Cell Sheet.A5>, <Cell Sheet.B5>, <Cell Sheet.C5>),
(<Cell Sheet.A6>, <Cell Sheet.B6>, <Cell Sheet.C6>),
(<Cell Sheet.A7>, <Cell Sheet.B7>, <Cell Sheet.C7>),
(<Cell Sheet.A8>, <Cell Sheet.B8>, <Cell Sheet.C8>),
(<Cell Sheet.A9>, <Cell Sheet.B9>, <Cell Sheet.C9>))
'''

tuple(ws.columns) #获取A1到C9的所有单元格，以列为单位
'''
输出：
((<Cell Sheet.A1>,
<Cell Sheet.A2>,
<Cell Sheet.A3>,
<Cell Sheet.A4>,
<Cell Sheet.A5>,
<Cell Sheet.A6>,
...
<Cell Sheet.B7>,
<Cell Sheet.B8>,
<Cell Sheet.B9>),
(<Cell Sheet.C1>,
<Cell Sheet.C2>,
<Cell Sheet.C3>,
<Cell Sheet.C4>,
<Cell Sheet.C5>,
<Cell Sheet.C6>,
<Cell Sheet.C7>,
<Cell Sheet.C8>,
<Cell Sheet.C9>))
'''

　　For performance reasons, Worksheet.columns in read-only mode is unavailable

Cell value processing
value if the value of the cell to process only, can use the property Worksheet.values, which returns only the cell

# This method iterates only cell values 
for Row in ws.values:
    for value in Row:
      Print (value) 

# Worksheet.iter_rows () and Worksheet.iter_cols () method can be acquired by way of the development of the cell parameters only value 
for Row in ws.iter_rows (min_row =. 1, max_col =. 3, MAX_ROW = 2, values_only = True):
     Print (Row)
 '' ' 
output: 
(None, None, None) 
(None, None, None) 
' ' '

data storage

WS = C [ ' A4 ' ] 
c.value = ' Hello, World '  # to the assigned cell A4

Save the file
using the save () function is the easiest and safest way

wb = Workbook()
wb.save('balances.xlsx')

Note:
　　1) saved in this way will overwrite the original file of the same name without warning, so be careful
　　extension 2) file does not have to xlsx, but if not, could lead to open office

Save streaming

If you save the file into a stream, such as when using the Pyramid, Flask or Django and other applications, you can simply provide a NamedTemporaryFile () function

from tempfile Import NamedTemporaryFile
 from openpyxl Import Workbook 

wb = Workbook () 
with NamedTemporaryFile () AS tmp: 
    wb.save (tmp.name) 
    tmp.seek (0) 
    Stream = tmp.read () 
    
# load a document, by specifying the attribute template True, the workbook can be saved as a template 
WB = load_workbook ( ' document.xlsx ' ) 
wb.template = True 
wb.save ( ' document_template.xltx ' ) 

# load a template file, template by specifying the property is False, can save the workbook document to 
WB = load_workbook ( 'document_template.xltx')
wb.template = False 
wb.save('document.xlsx', as_template=False)

　　You should monitor and document data attribute extension, in order to save a document in a template, or save the template in the document,
　　otherwise the result will not open the document table engine

　　The following situations will save failed

load_workbook = wb ( ' document.xlsx ' ) 
wb.save ( ' new_document.xlsm ' ) # to be saved as an extension xlsx, or excel can not open the 

wb = load_workbook ( ' document.xlsm ' ) 
wb.save ( ' new_document. xlsm ' ) # need to specify the property keep_vba = True, otherwise excel can not open the 

wb = load_workbook ( ' document.xltm ' , keep_vba = True) 
wb.save ( ' new_document.xlsm ' ) # If you need a template, you need to specify the extension is * .xltm

Load file

It also could openpyxl.load_workbook () to open a file

from openpyxl Import load_workbook # load the class file to be imported load_workbook 

WB2 = load_workbook ( ' test.xlsx ' )
 Print (wb2.sheetnames)   # Output: [ 'Sheet2', 'New Title', 'Sheet1'], the output of the workbook's worksheet first name

workbook data related operations

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