Can I copy or download a Google Doc if I have only its 'Publish to the web' link?

Question

If a Google Doc has been published to the Web, the published version is not a Google document but an HTML webpage.

To copy or download the document I can save it as a webpage or PDF, but that screws up the layout and formatting relative to the published document.

Is there a way to copy or download the source Google document to my Drive using information contained in the web-published link?

I would be fine with any document format that maintained the original document layout and format (Google Doc, Acrobat PDF, MS Word Doc, etc.).

Example web-published Doc link:

 https://docs.google.com/document/d/e/2PACX-1vTka35LEjmhp_0Fa8hUkWJazZSkGG5tO0phXt9lKrFdeh0nbPv-YyVjhsZGgGmdWWXELA9yl-ZXCesU/pub

Answer 1

Unfortunately a Google document's 'Publish to the web' URL can't be used to copy or download the corresponding document.

You would need view or edit permission for the source document.

Perhaps if you contact the document owner they might be willing to share it with you.

Resources

• Publish a document, spreadsheet, presentation, or drawing - Google Docs editors Help

Answer 2

the code below can help reading the information in the link below into a excel file, maybe others will find it useful as well:

URL: https://docs.google.com/spreadsheets/d/1G8FQNlitoRr1oK2-LZEloeg0_VBP-E0J_WoSXqAhxNo/pubhtml#

import pandas as pd

# Step 1: Read data from the Google Sheets URL
url = 'https://docs.google.com/spreadsheets/d/1G8FQNlitoRr1oK2-LZEloeg0_VBP-E0J_WoSXqAhxNo/pubhtml'

# Read all tables from the HTML page
tables = pd.read_html(url)

# Assuming the first table is 'orals' and the second is 'posters'
df_orals = tables[0]
df_posters = tables[1]

# Step 2: Clean the DataFrames by removing columns with many NaNs and rows with any NaNs
def clean_dataframe(df, threshold=0.5):
    # Calculate the percentage of NaNs in each column
    nan_percent = df.isna().mean()
    
    # Keep columns where the percentage of NaNs is less than the threshold
    cols_to_keep = nan_percent[nan_percent < threshold].index
    df_clean = df[cols_to_keep]
    
    # Drop rows with any NaNs
    df_clean = df_clean.dropna()
    
    # Reset the index
    df_clean.reset_index(drop=True, inplace=True)
    
    return df_clean

# Apply cleaning to both DataFrames
df_orals_clean = clean_dataframe(df_orals)
df_posters_clean = clean_dataframe(df_posters)

# Step 3: Remove the first column and replace column headers with the first row
def modify_dataframe(df):
    # Remove the first column
    df_modified = df.iloc[:, 1:]
    
    # Replace column headers with the first row
    df_modified.columns = df_modified.iloc[0]
    
    # Remove the first row since it's now the header
    df_modified = df_modified.iloc[1:]
    
    # Reset the index
    df_modified.reset_index(drop=True, inplace=True)
    
    return df_modified

# Modify both DataFrames
df_orals_modified = modify_dataframe(df_orals_clean)
df_posters_modified = modify_dataframe(df_posters_clean)

# Step 4: Save the modified DataFrames to an Excel file with two sheets
output_filename = 'orals_and_posters.xlsx'

# Use ExcelWriter to write multiple DataFrames to different sheets
with pd.ExcelWriter(output_filename, engine='openpyxl') as writer:
    # Write each DataFrame to a specific sheet
    df_orals_modified.to_excel(writer, sheet_name='Orals', index=False)
    df_posters_modified.to_excel(writer, sheet_name='Posters', index=False)

print(f"DataFrames saved to '{output_filename}' with two sheets: 'Orals' and 'Posters'")

Answer 3

You can download the document as a PDF by printing it, and then choose "download as PDF". If you want to fix the formatting issues (for example, on my saved PDF version the text was all centered really narrow in the middle and I wanted it to extend to the left and right of the page), you can edit the html to take the padding off the main div before you do this.