load_working_file() method

Loads a working file from the Working data area to make the file available for Python/HCL scripting. The loaded file is a copy, not the original.

Syntax

hcl.load_working_file(name = "working_file_name")

Parameters

Returns

For success, the return code 202. For failure, an error message.

Examples

CSV examples

hcl.load_working_file(name = "Invoices_Q1_2022.csv")

# Import the Pandas library 
import pandas as pd

# Load a CSV file from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.csv") 

# Read the CSV file to a Pandas dataframe 
invoices_q1_2022_pd_df = pd.read_csv("Invoices_Q1_2022.csv") 

# Display the Pandas dataframe
invoices_q1_2022_pd_df

# Load a CSV file from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.csv")

# Read the CSV file to an HCL dataframe
invoices_q1_2022_hcl_df = hcl.read_csv("Invoices_Q1_2022.csv")

# Display the HCL dataframe
invoices_q1_2022_hcl_df

# Convert an HCL dataframe to a Pandas dataframe
invoices_q1_2022_pd_df = invoices_q1_2022_hcl_df.to_pandas()

# Display the Pandas dataframe
invoices_q1_2022_pd_df

# Import the Pandas library 
import pandas as pd

# Load a compressed CSV file (*.csv.gz) from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.csv.gz")

# Read the compressed CSV file to a Pandas dataframe
invoices_q1_2022_pd_df = pd.read_csv("Invoices_Q1_2022.csv.gz", compression="gzip", header=0)

# Display the Pandas dataframe
invoices_q1_2022_pd_df

Excel examples

# Import the Pandas library 
import pandas as pd

# Load an Excel file (*.xlsx) from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.xlsx") 

# Read the Excel file to a Pandas dataframe 
invoices_q1_2022_pd_df = pd.read_excel("Invoices_Q1_2022.xlsx") 

# Display the Pandas dataframe
invoices_q1_2022_pd_df

pip install xlrd

# Import the Pandas library 
import pandas as pd

# Load an Excel file (*.xls) from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.xls") 

# Read the Excel file to a Pandas dataframe 
invoices_q1_2022_pd_df = pd.read_excel("Invoices_Q1_2022.xls") 

# Display the Pandas dataframe
invoices_q1_2022_pd_df

pip install pyexcel

pip install pyexcel-xlsx

# Import the pyexcel library
import pyexcel as pe

# Import the get_data method from the pyexcel-xlsx library
from pyexcel_xlsx import get_data

# Load an Excel file from the Working data area
hcl.load_working_file(name = "Invoices_Q1_2022.xlsx")

# Copy the Excel data to a pyexcel sheet
sheet = pe.get_sheet(file_name="Invoices_Q1_2022.xlsx")

# Delete two rows of unwanted header information from the top of the worksheet
del sheet.row[0, 1]

# Name the columns using the name values in what is now the first row in the worksheet
sheet.name_columns_by_row(0)

# Delete three unwanted columns from the worksheet
del sheet.column['Prodno', 'Quantity', 'Unit_Cost']

# Save the pyexcel sheet to a new Excel file
sheet.save_as("Invoices_Q1_2022_prepared.xlsx")

# Save the new Excel file to the Working data area
hcl.save_working_file(name = "Invoices_Q1_2022_prepared.xlsx")

Remarks

Working data area

The Working data area in a robot is accessible in two different locations in the Robots user interface:

• The Working data tab

• The Working data panel in the script editor

Both locations provide access to the same central data storage area in a robot. Actions you perform in one location are automatically synchronized in the other location.

Automatic generation of load_working_file() method

As a labor-saving feature, the Working data panel in the script editor automatically generates a copy of the load_working_file() method with a specific file name prefilled:

• Copy snippet button In the Working data panel, each row contains the Copy snippet button . Select the button to copy a snippet with the load_working_file() method prefilled with the name of the file in the row. You can paste the snippet in any script editor cell.

• Auto-creation of script editor cell When you upload a file to the Working data panel in the script editor, a cell containing the load_working_file() method prefilled with the name of the file is automatically created at the top of the script. You can use the cell as a starting point, or copy the method to another location in the script and then delete the cell.

File loading behavior

When you load a file from the Working data area into the Python runtime environment you are loading a copy, not the original file. If a file with the same name, and identical file name casing, already exists in the runtime environment, it is automatically overwritten.

Casing of file names

When you specify working_file_name it is not case sensitive. When you run a script interactively in the script editor, whatever casing you use for working_file_name is replicated in the Session files panel. If you load the same file twice, and use different casing for the file name each time, the result is two identical session files with differently cased names. The behavior is the same when you use a task to run a script.

Once a file is loaded into the Python environment, however, file names are case sensitive. So after loading a working file, any subsequent code needs to replicate the casing that you used when you loaded the file.

To avoid simple script errors caused by mismatched file name casing, the best practice when loading a working file is to replicate the casing of the file name in the Working data area.

Script error message

Any of these situations produce the script error message shown below:

• the specified file does not exist in the Working data area in the robot containing the script

• the file name is misspelled

• the file extension is missing

Script error message:

Exception: File not found in the Working section