numbers-parser
is a Python module for parsing Apple Numbers
.numbers
files. It supports Numbers files generated by Numbers version 10.3, and up with the latest tested version being 12.2
(current as of October 2022).
It supports and is tested against Python versions from 3.8 onwards. It is not compatible with earlier versions of Python.
Currently supported features of Numbers files are:
- Multiple sheets per document
- Multiple tables per sheet
- Text, numeric, date, currency, duration, percentage cell types
Formulas rely on Numbers storing current values which should usually be the case. Formulas themselves rather than the computed values can optionally be extracted. Styles are not supported.
As of version 3.0, numbers-parser
has limited support for creating Numbers files.
python3 -m pip install numbers-parser
A pre-requisite for this package is python-snappy which will be installed by Python automatically, but python-snappy also requires that the binary libraries for snappy compression are present.
The most straightforward way to install the binary dependencies is to use Homebrew and source Python from Homebrew rather than from macOS as described in the python-snappy github:
For Intel Macs:
brew install snappy python3
CPPFLAGS="-I/usr/local/include -L/usr/local/lib" python3 -m pip install python-snappy
And on Apple Silicon:
brew install snappy python3
CPPFLAGS="-I/opt/homebrew/include -L/opt/homebrew/lib" python3 -m pip install python-snappy
On Windows, you will need to either arrange for snappy to be found for VSC++ or you can install python binary libraries compiled by Christoph Gohlke. You must select the correct python version for your installation. For example for python 3.11:
C:\Users\Jon>pip install C:\Users\Jon\Downloads\python_snappy-0.6.1-cp311-cp311-win_amd64.whl
Reading documents:
from numbers_parser import Document
doc = Document("my-spreasdsheet.numbers")
sheets = doc.sheets
tables = sheets[0].tables
rows = tables[0].rows()
Both sheets and names can be accessed from lists of these objects using an integer index (list
syntax) and using the name
of the sheet/table (dict
syntax):
# list access method
sheet_1 = doc.sheets[0]
print("Opened sheet", sheet_1.name)
# dict access method
table_1 = sheets["Table 1"]
print("Opened table", table_1.name)
As of version 3.0, the Document.sheets()
and Sheet.tables()
methods are deprecated and will issue a DeprecationWarning
if used. Instead of these functions, you should use the properties as demonstrated above. The legacy methods will be removed in a future version of numbers-parser
.
Table
objects have a rows
method which contains a nested list with an entry for each row of the table. Each row is
itself a list of the column values. Empty cells in Numbers are returned as None
values.
data = sheets["Table 1"].rows()
print("Cell A1 contains", data[0][0])
print("Cell C2 contains", data[2][1])
Cells are objects with a common base class of Cell
. All cell types have a property value
which returns the contents of the cell in as a native Python datatype. DurationCell
object values are datetime.timedelta
objects which are additionally available as a formatted value matching that stored in the Numbers spreadsheet. The formatted value is returned using the formatted_value
property.
In addition to extracting all data at once, individual cells can be referred to as methods
doc = Document("my-spreasdsheet.numbers")
sheets = doc.sheets
tables = sheets["Sheet 1"].tables
table = tables["Table 1"]
# row, column syntax
print("Cell A1 contains", table.cell(0, 0))
# Excel/Numbers-style cell references
print("Cell C2 contains", table.cell("C2"))
When extracting data using rows()
merged cells are ignored since only text values
are returned. The cell()
method of Table
objects returns a Cell
type
object which is typed by the type of cell in the Numbers table. MergeCell
objects
indicates cells removed in a merge.
doc = Document("my-spreasdsheet.numbers")
sheets = doc.sheets
tables = sheets["Sheet 1"].tables
table = tables["Table 1"]
cell = table.cell("A1")
print(cell.merge_range)
print(f"Cell A1 merge size is {cell.size[0]},{cell.size[1]})
Tables have iterators for row-wise and column-wise iteration with each iterator returning a list of the cells in that row or column
for row in table.iter_rows(min_row=2, max_row=7, values_only=True):
sum += row
for col in table.iter_cols(min_row=2, max_row=7):
sum += col.value
Since the return value of data()
is a list of lists, you can pass this directly to pandas. Assuming you have a Numbers table with a single header which contains the names of the pandas series you want to create you can construct a pandas dataframe using:
import pandas as pd
doc = Document("simple.numbers")
sheets = doc.sheets
tables = sheets[0].tables
data = tables[0].rows(values_only=True)
df = pd.DataFrame(data[1:], columns=data[0])
Cells that contain bulleted or numbered lists can be identified by the is_bulleted
property. Data from such cells is returned using the value
property as with other cells, but can additionally extracted using the bullets
property. bullets
returns a list of the paragraphs in the cell without the bullet or numbering character. Newlines are not included when bullet lists are extracted using bullets
.
doc = Document("bullets.numbers")
sheets = doc.sheets
tables = sheets[0].tables
table = tables[0]
if not table.cell(0, 1).is_bulleted:
print(table.cell(0, 1).value)
else:
bullets = ["* " + s for s in table.cell(0, 1).bullets]
print("\n".join(bullets))
Bulleted and numbered data can also be extracted with the bullet or number characters present in the text for each line in the cell in the same way as above but using the formatted_bullets
property. A single space is inserted between the bullet character and the text string and in the case of bullets, this will be the Unicode character seen in Numbers, for example "• some text"
.
Querying cell formats is currently limited to image backrgounds only. If a cell has no background image, None
is returned for all calls.
cell = table.cell("B1")
with open (cell.image_filename, "wb") as f:
f.write(cell.image_data)
print("Wrote file of type", cell.image_type)
This is considered experimental: you are highly recommened not to overwrite working Numbers files and instead save data to a new file.
Since version 3.4.0, adding tables and sheets is supported. Known limitations to write support are:
- Creating cells of type
BulletedTextCell
is not supported - Formats cannot be defined for
DurationCell
orDateCell
- New tables are inserted with a fixed offset below the last table in a worksheet which does not take into account title or caption size
- New sheets insert tables with formats copied from the first table in the previous sheet rather than default table formats
numbers-parser
will automatically empty rows and columns for any cell references that are out of range of the current table. The write
method accepts the same cell numbering notation as cell
plus an additional argument representing the new cell value. The type of the new value will be used to determine the cell type.
doc = Document("old-sheet.numbers")
sheets = doc.sheets
tables = sheets[0].tables
table = tables[0]
table.write(1, 1, "This is new text")
table.write("B7", datetime(2020, 12, 25))
doc.save("new-sheet.numbers")
Sheet names and table names can be changed by assigning a new value to the name
of each:
sheets[0].name = "My new sheet"
tables[0].name = "Edited table"
Additional tables and worksheets can be added to a Document
before saving. If no sheet name or table name is supplied, numbers-parser
will use Sheet 1
, Sheet 2
, etc.
doc = Document()
doc.add_sheet("New Sheet", "New Table")
sheet = doc.sheets["New Sheet"]
table = sheet.tables["New Table"]
table.write(1, 1, 1000)
table.write(1, 2, 2000)
table.write(1, 3, 3000)
doc.save("sheet.numbers")
numbers-parser
can query and change the position and size of tables. Changes made to a table's row height or column width is retained when files are saved.
Row heights and column widths are queried and set using the row_height
and col_width
methods:
doc = Document("sheet.numbers")
table = doc.sheets[0].tables[0]
print(f"Table size is {table.height} x {table.width}")
print(f"Table row 1 height is {table.row_height(0)}")
table.row_height(0, 40)
print(f"Table row 1 height is now {table.row_height(0)}")
print(f"Table column A width is {table.col_width(0)}")
table.col_width(0, 200)
print(f"Table column A width is {table.col_width(0)}")
When new tables are created, numbers-parser
follows the Numbers convention of creating a table with one row header and one column header. You can change the number of headers by modifying the appopriate property:
doc = Document("sheet.numbers")
table = doc.sheets[0].tables[0]
table.num_header_rows = 2
table.num_header_cols = 0
doc.save("saved.numbers")
A zero header count will remove the headers from the table. Attempting to set a negative number of headers, or using more headers that rows or columns in the table will raise a ValueError
exception.
By default, new tables are positioned at a fixed offset below the last table vertically in a sheet and on the left side of the sheet. Large table headers and captions may result in new tables overlapping existing ones. The add_table
method takes optional coordinates for positioning a table. A table's height and coordinates can also be queried to help aligning new tables:
(x, y) = sheet.table[0].coordinates
y += sheet.table[0].height + 200.0
new_table = sheet.add_table("Offset Table", x, y)
When installed from PyPI, a command-like script cat-numbers
is installed in Python's scripts folder. This script dumps Numbers spreadsheets into Excel-compatible CSV format, iterating through all the spreadsheets passed on the command-line.
usage: cat-numbers [-h] [-T | -S | -b] [-V] [--debug] [--formulas]
[--formatting] [-s SHEET] [-t TABLE] [document ...]
Export data from Apple Numbers spreadsheet tables
positional arguments:
document Document(s) to export
optional arguments:
-h, --help show this help message and exit
-T, --list-tables List the names of tables and exit
-S, --list-sheets List the names of sheets and exit
-b, --brief Don't prefix data rows with name of sheet/table (default: false)
-V, --version
--debug Enable debug output
--formulas Dump formulas instead of formula results
--formatting Dump formatted cells (durations) as they appear in Numbers
-s SHEET, --sheet SHEET Names of sheet(s) to include in export
-t TABLE, --table TABLE Names of table(s) to include in export
Note: --formatting
will return different capitalisation for 12-hour times due to differences between Numbers' representation of these dates and datetime.strftime
. Numbers in English locales displays 12-hour times with 'am' and 'pm', but datetime.strftime
on macOS at least cannot return lower-case versions of AM/PM.
Numbers uses a proprietary, compressed binary format to store its tables.
This format is comprised of a zip file containing images, as well as
Snappy-compressed
Protobuf .iwa
files containing
metadata, text, and all other definitions used in the spreadsheet.
As numbers-parser
includes private Protobuf definitions extracted from a copy of Numbers, new versions of Numbers will inevitably create .numbers
files that cannot be read by numbers-parser
. As new versions of Numbers are released, running make bootstrap
will perform all the steps necessary to recreate the protobuf files used numbers-parser
to read Numbers spreadsheets.
On Apple Silicon Macs, the default protobuf package installation does not include the C++ optimised version which is required by the bootstrapping scripts to extract protobufs. You will receive the following error during build if this is the case:
This script requires the Protobuf installation to use the C++ implementation. Please reinstall Protobuf with C++ support.
To include the C++ support, download a released version of Google protobuf from github. Build instructions are in the src/README.md
in the distribution but for macOS with Homebrew the two steps are, firstly to install the native protobuf libraries, which must be on your LD_LIBRARY_PATH
:
brew install autoconf automake libtool
./autogen.sh
./configure --prefix=/usr/local
make check -j`sysctl -n hw.ncpu`
sudo make install
And then to install the Python libraries with C++ support. If you already have protobuf install via Homebrew, you will need to brew unlink
the installation.
cd python
python3 setup.py build --cpp_implementation
python3 setup.py test --cpp_implementation
python3 setup.py install --cpp_implementation
This will install protobuf in a folder above the source installation which can then be used by make bootstrap
in the numbers-parser
source tree.
numbers-parser
was built by Jon Connell but relies heavily on from prior work by Peter Sobot to read the IWA format archives used by Apple's iWork family of applications, and to regenerate the mapping files required for Python. Both modules are derived from previous work by Sean Patrick O'Brien.
Decoding the data structures inside Numbers files was helped greatly by Stingray-Reader by Steven Lott.
Formula tests were adapted from JavaScript tests used in fast-formula-parser.
Decimal128 conversion to and from byte storage was adapted from work done by the SheetsJS project. SheetJS also helped greatly with some of the steps required to successfully save a Numbers spreadsheet.
All code in this repository is licensed under the MIT License