add card printing data scripts

scripts/card_print_1.js

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+
+
+function main(workbook: ExcelScript.Workbook) {
+    let selectedCell = workbook.getActiveCell();
+    let selectedSheet = workbook.getActiveWorksheet();
+
+    // Set fill colour to yellow for the selected cell.
+    selectedCell.getFormat().getFill().setColor("yellow");
+
+    // Get the hyperlink of the active cell.
+    let hyperlink = selectedCell.getHyperlink();
+
+    // Print the hyperlink in the console.
+    // console.log("Hyperlink: " + JSON.stringify(hyperlink.address));
+
+    // Check if there is a selected cell.
+    if (selectedCell) {
+        // Get the column index of the selected cell.
+        let selectedColumnIndex = selectedCell.getColumnIndex();
+
+        // Get the active sheet.
+        let selectedSheet = workbook.getActiveWorksheet();
+
+        // Get the number of rows in the sheet.
+        let rowCount = 10932;
+
+        // Iterate through each row and copy the value from the selected column to a new column.
+        for (let rowIndex = 0; rowIndex < rowCount; rowIndex++) {
+            // Get the value from the selected column.
+            let cellValue = selectedSheet.getCell(rowIndex, selectedColumnIndex).getHyperlink()?.address;
+
+            // Assume the new column is next to the selected column. You can adjust the index as needed.
+            let newColumnIndex = selectedColumnIndex + 1;
+
+            // Set the value in the new column.
+            selectedSheet.getCell(rowIndex, newColumnIndex).setValue(cellValue);
+        }
+
+        console.log("New column created with values from the selected column.");
+    } else {
+        console.log("No cell selected.");
+    }
+}

scripts/card_print_data_2.py

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+import pandas as pd
+import os
+import numpy as np
+import xlsxwriter
+
+curdir = os.getcwd()
+path_delim = '/'
+df1 = pd.read_excel(curdir + path_delim + "data/users_16_12_2023_18_31.xlsx", sheet_name="Sheet1")
+df2 = pd.read_excel(curdir + path_delim + "data/16Dec23-GIPCI Card Printing-2.xlsx", sheet_name="Data for Submission-GIPCI 16Dec")
+
+df = df2.merge(df1, on="_id", how="inner")
+print(df.columns)
+
+# df = df[["_id", "name_x", "abhaId", "aadharId", "Age", "gender", "category", "maritalStatus", "house", "district", "state", "pinCode", "phoneNumber", "classificationResult", "bloodGroup", "testTime", "caste", "registrationCenterName"]]
+# print(df)
+
+df["Block/Ward"] = ""
+df["Village/Town/City"] = df["city"]
+df["Test Type"] = "HPOS"
+df["Photograph"] = df['_id'].apply(lambda x: f'images\{x}.jpg') #f"external:{row['Image URL']}"
+
+df.rename(columns={'_id': "Sample ID", "aadharId": "AADHAAR ID", "ABHA ID": "ABHA Number", "careOf": "Father's Name / Husband's Name", "Test Result": "Test report"}, inplace = True)
+
+df = df.reindex(["Sample ID", "ABHA Number", "Name", "AADHAAR ID", "Age", "Gender", "Father's Name / Husband's Name", "District", "Block/Ward", "Village/Town/City", "Address", "Pincode", "Test report", "Test Type", "Blood Group", "bloodGroup", "Photograph"], axis=1)
+
+writer = pd.ExcelWriter(curdir + path_delim + "data/CardPrint4.xlsx", engine = 'xlsxwriter')
+df.to_excel(writer, sheet_name = 'op', index=False)
+
+# Get the xlsxwriter workbook and worksheet objects
+workbook = writer.book
+worksheet = writer.sheets['op']
+
+# Add hyperlinks to the 'Photograph' column
+for row_num, link in enumerate(df['Photograph'], start=1):
+    worksheet.write_url(row_num, df.columns.get_loc('Photograph'), string=link, url=link, cell_format=None)
+
+writer.close()

scripts/card_print_data_3.py

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+import pandas as pd
+import os
+
+curdir = os.getcwd()
+path_delim = '/'
+df1 = pd.read_excel(curdir + path_delim + "data/users_12_01_2024_23_25.xlsx", sheet_name="Sheet1")
+df2 = pd.read_excel(curdir + path_delim + "data/12jan-printing-input.xlsx", sheet_name="Sheet1")
+
+# Define a function to find the _id for each row in df2
+def find_id(row):
+    match = df1[(df1['abhaId'] == row['abhaId'])]
+    if not match.empty:
+        return match.iloc[0]['_id']
+    else:
+        match = df1[(df1['name'] == row['name'])]
+        if not match.empty:
+            return match.iloc[0]['_id']
+        match = df1[(df1['house'] == row['address'])]
+        if not match.empty:
+            return match.iloc[0]['_id']
+        return None
+
+def find_aadharId(row):
+    match = df1[(df1['abhaId'] == row['abhaId'])]
+    if not match.empty:
+        return match.iloc[0]['aadharId']
+    else:
+        match = df1[(df1['name'] == row['name'])]
+        if not match.empty:
+            return match.iloc[0]['aadharId']
+        match = df1[(df1['house'] == row['address'])]
+        if not match.empty:
+            return match.iloc[0]['aadharId']
+        return None
+
+def find_abhaId(row):
+    match = df1[(df1['name'] == row['name'])]
+    if not match.empty:
+        return match.iloc[0]['abhaId']
+    else:
+        match = df1[(df1['house'] == row['address'])]
+        if not match.empty:
+            return match.iloc[0]['abhaId']
+        return None
+
+# Apply the function to create a new '_id' column in df2
+df2['_id'] = df2["Photograph"].get_url()
+df2['aadharId'] = df2.apply(find_aadharId, axis=1)
+df2['abhaId2'] = df2.apply(find_abhaId, axis=1)
+
+# Continue with the rest of your code...
+
+# Add the rest of your code (e.g., renaming columns, creating new columns, etc.)
+df2["Block/Ward"] = ""
+# df2["Village/Town/City"] = df2["city"]
+df2["Test Type"] = "HPOS"
+df2["Photograph"] = df2['_id'].apply(lambda x: f'images\{x}.jpg') 
+
+df2.rename(columns={'_id': "Sample ID", "name": "Name", "aadharId": "AADHAAR ID", "ABHA ID": "ABHA Number", "careOf": "Father's Name / Husband's Name", "Test Result": "Test report"}, inplace=True)
+
+# Continue with the rest of your code...
+
+# Save the resulting DataFrame to Excel
+writer = pd.ExcelWriter(curdir + path_delim + "data/CardPrint10.xlsx", engine='xlsxwriter')
+df2.to_excel(writer, sheet_name='op', index=False)
+
+# Get the xlsxwriter workbook and worksheet objects
+workbook = writer.book
+worksheet = writer.sheets['op']
+
+# Add hyperlinks to the 'Photograph' column
+for row_num, link in enumerate(df2['Photograph'], start=1):
+    worksheet.write_url(row_num, df2.columns.get_loc('Photograph'), string=link, url=link, cell_format=None)
+
+writer.close()

scripts/card_print_data_4.py

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+import pandas as pd
+import os
+import re
+
+curdir = os.getcwd()
+path_delim = '/'
+df = pd.read_excel(curdir + path_delim + "data/12jan-printing-input.xlsx", sheet_name="Sheet1")
+
+
+pattern = re.compile(r'/([^/]+)\.[a-z]+$', re.IGNORECASE)
+
+# Function to apply to each row of the DataFrame
+def extract_filename(file_path):
+    match = pattern.search(file_path)
+    return match.group(1) if match else None
+
+# Apply the function to the 'file_path' column
+df['_id'] = df['Url'].apply(extract_filename)
+
+print(df)
+print(df.columns)
+
+writer = pd.ExcelWriter(curdir + path_delim + "data/CardPrint11.xlsx", engine='xlsxwriter')
+df.to_excel(writer, sheet_name='op', index=False)
+
+writer.close()

scripts/card_print_data_5.py

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+import os
+import re
+
+file_path = "../../../../Downloads/images/352405884025RAVGMC.jpg"
+
+# Using regular expression to extract the filename without extension
+pattern = re.compile(r'/([^/]+)\.[a-z]+$', re.IGNORECASE)
+match = pattern.search(file_path)
+
+if match:
+    extracted_file_name = match.group(1)
+    print(extracted_file_name)
+else:
+    print("Unable to extract filename from the given path.")

scripts/card_print_data_6.py

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+import pandas as pd
+import os
+
+curdir = os.getcwd()
+path_delim = '/'
+df1 = pd.read_excel(curdir + path_delim + "data/users_12_01_2024_23_25.xlsx", sheet_name="Sheet1")
+df2 = pd.read_excel(curdir + path_delim + "data/CardPrint11.xlsx", sheet_name="op")
+
+df = df2.merge(df1, on="_id", how="left")
+print(df.columns)
+
+# df = df[["_id", "name_x", "abhaId", "aadharId", "Age", "gender", "category", "maritalStatus", "house", "district", "state", "pinCode", "phoneNumber", "classificationResult", "bloodGroup", "testTime", "caste", "registrationCenterName"]]
+# print(df)
+
+df["Block/Ward"] = ""
+df["Village/Town/City"] = df["city"]
+df["Test Type"] = "HPOS"
+df["Photograph"] = df['_id'].apply(lambda x: f'images\{x}.jpg') #f"external:{row['Image URL']}"
+
+df.rename(columns={'_id': "Sample ID", "aadharId": "AADHAAR ID", "ABHA ID": "ABHA Number", "careOf": "Father's Name / Husband's Name", "Test Result": "Test report"}, inplace = True)
+
+# df = df.reindex(["Sample ID", "ABHA Number", "Name", "AADHAAR ID", "Age", "Gender", "Father's Name / Husband's Name", "District", "Block/Ward", "Village/Town/City", "Address", "Pincode", "Test report", "Test Type", "Blood Group", "bloodGroup", "Photograph"], axis=1)
+
+writer = pd.ExcelWriter(curdir + path_delim + "data/CardPrint12.xlsx", engine = 'xlsxwriter')
+df.to_excel(writer, sheet_name = 'op', index=False)
+
+# Get the xlsxwriter workbook and worksheet objects
+workbook = writer.book
+worksheet = writer.sheets['op']
+
+# Add hyperlinks to the 'Photograph' column
+for row_num, link in enumerate(df['Photograph'], start=1):
+    worksheet.write_url(row_num, df.columns.get_loc('Photograph'), string=link, url=link, cell_format=None)
+
+writer.close()