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Minor fixes to IfcCSV documentation
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@@ -1,8 +1,9 @@
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IfcCSV
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======
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IfcCSV lets you view and edit IFC data using spreadsheets or tabular datasets,
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such as CSV, ODS, XLSX, Pandas DataFrames, and regular Python lists.
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IfcCSV lets you view and edit IFC data using spreadsheets or tabular datasets.
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IfcCSV supports CSV (Comma Separated Values), ODS (Open Document Spreadsheet),
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XLSX (Microsoft Excel), Pandas DataFrames, and regular Python lists.
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IfcCSV lets you select rooted elements using the IFC selection queries. These
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elements may be physical elements (walls, doors, windows, etc), construction
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@@ -13,13 +14,13 @@ Once you have selected a list of elements, you may specify attributes,
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properties, quantities, or relationships to extract and use as columns in your
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table.
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For example, you might use a selection query of ``.IfcDoor``, for all doors in
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For example, you might use a selection query of ``IfcDoor``, for all doors in
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your project. You may then specify a ``class`` attribute, a ``Name`` attribute,
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a ``type.Name`` relationship, and a ``type.Description`` relationship. This
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will produce a table as shown:
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a ``type.Name`` relationship, and a ``type.Description`` relationship. You can
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then produce a spreadsheet like this:
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+------------------------+---------+------+-----------+------------------------------------+
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| GlobalId | class | Name | type.Name | type.Description |
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| GlobalId | Class | Name | Type Name | Type Description |
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+========================+=========+======+===========+====================================+
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| 3AjGVS9EjBeBrDA5_tAcwQ | IfcDoor | 01 | DT-A | Single swing steel frame door |
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+------------------------+---------+------+-----------+------------------------------------+
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@@ -32,8 +33,8 @@ will produce a table as shown:
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.. note::
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IfcCSV automatically inserts the GlobalId column at the beginning, in order
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to uniquely identify the element.
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By default, IfcCSV automatically inserts the GlobalId column at the
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beginning, in order to uniquely identify the element.
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This tabular data may then be exported in your desired format.
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@@ -42,8 +43,8 @@ you make in the spreadsheet or table will also be made in the IFC.
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There are different methods of installation, depending on your situation.
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1. **Source installation** is recommended for users wanting to use the latest
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code as a library or a CLI utility.
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1. **Source installation** is recommended for developers wanting to use the
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latest code as a library or a CLI utility.
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2. **Using the BlenderBIM Add-on** is recommended for non-developers wanting a
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graphical interface.
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@@ -54,11 +55,12 @@ Source installation
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2. `Clone the source code <https://github.com/IfcOpenShell/IfcOpenShell/tree/v0.7.0/src/ifccsv>`_.
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3. ``cd /path/to/IfcOpenShell/src/ifccsv``
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Depending on which formats you want to edit, you will need to install more dependencies:
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Depending on which formats you want to edit, you will need to install more
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dependencies:
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- ``pip install odfpy`` for ODS support
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- ``pip install xlsxwriter`` for XLSX support
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- ``pip install pandas`` for Pandas DataFrame support
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- ``pip install openpyxl`` for XLSX support
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- ``pip install pandas`` for ODS, XLSX, and Pandas DataFrame support
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Here is a minimal example of how to use IfcDiff as a Python module or CLI
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utility:
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@@ -100,7 +102,7 @@ utility:
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Choose the sort order from ASC or DESC for each sorted attribute.
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--export Export from IFC to the desired format.
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--import Import from the autodetected format to IFC.
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$ python -m ifccsv -i model.ifc -s out.csv -f csv -q .IfcProduct -a "Name" "Description" --export
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$ python -m ifccsv -i model.ifc -s out.csv -f csv -q IfcProduct -a "Name" "Description" --export
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$ cat out.csv
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Here is a minimal example of how to use IfcCSV as a library:
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@@ -159,7 +161,7 @@ interface to access the IfcOpenShell utilities.
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3. Browse to your IFC file.
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4. Type in a filter query, such as ``.IfcDoor``.
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4. Type in a filter query, such as ``IfcDoor``.
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5. Optionally add attributes you'd like to export.
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