diff --git a/tool.py b/tool.py index b02fe22..19d8831 100644 --- a/tool.py +++ b/tool.py @@ -10,7 +10,7 @@ import http.server import socketserver import threading -from tqdm import tqdm +from tqdm import tqdm import shutil import math @@ -114,6 +114,8 @@ def josaa_rounds_year(): steps_completed = int(total * 0.1) display_progress_bar("STEP 1/10 ", steps_completed=steps_completed, total=total, duration=0.3) + applied_filters = {"Counseling Type": "JOSAA"} + josaa_round_year = None # initialize print(Fore.YELLOW + "Select JOSAA round year") print(Fore.GREEN + "1." + Fore.BLUE + "2022") @@ -131,10 +133,10 @@ def josaa_rounds_year(): else: print(Fore.RED + "Invalid input! Please select a number between 1 and 3." + Fore.RESET) - print(josaa_round_year) - josaa_rounds(josaa_round_year) + applied_filters["Year"] = josaa_round_year + josaa_rounds(josaa_round_year, applied_filters) -def josaa_rounds(josaa_round_year): +def josaa_rounds(josaa_round_year, applied_filters): os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) @@ -176,7 +178,8 @@ def josaa_rounds(josaa_round_year): else: print(Fore.RED + f"Invalid input! Please select a number between 1 and {max_option}." + Fore.RESET) - csv_files("josaa", selected_round, josaa_round_year) + applied_filters["Round"] = selected_round + csv_files("josaa", selected_round, josaa_round_year, applied_filters) def csab_rounds_year(): os.system("cls" if os.name == "nt" else "clear") @@ -186,7 +189,8 @@ def csab_rounds_year(): total = 100 steps_completed = int(total * 0.1) display_progress_bar("STEP 1/10 ", steps_completed=steps_completed, total=total, duration=0.3) - + + applied_filters = {"Counseling Type": "CSAB"} csab_round_year = None # initialize print(Fore.YELLOW + "Select CSAB round year") @@ -209,10 +213,10 @@ def csab_rounds_year(): else: print(Fore.RED + "Invalid input! Please select a number between 1 and 4." + Fore.RESET) - print(csab_round_year) - csab_rounds(csab_round_year) + applied_filters["Year"] = csab_round_year + csab_rounds(csab_round_year, applied_filters) -def csab_rounds(csab_round_year): +def csab_rounds(csab_round_year, applied_filters): os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) # progress bar for step-2 @@ -232,11 +236,11 @@ def csab_rounds(csab_round_year): else: print(Fore.RED + "Invalid input! Please select 1 or 2." + Fore.RESET) - csv_files("csab", csab_round, csab_round_year) + applied_filters["Round"] = csab_round + csv_files("csab", csab_round, csab_round_year, applied_filters) -# define the path of csv files for different types of colleges -def csv_files(type, round, year): +def csv_files(type, round, year, applied_filters): # Get path to the temporary folder created by PyInstaller if getattr(sys, 'frozen', False): # If the script is running in a PyInstaller bundle @@ -253,7 +257,7 @@ def csv_files(type, round, year): "NITs": os.path.join(cwd, "josaa", f"{year}", f"round_{josaa_rounds}", "ranks_nits.csv"), "GFTIs": os.path.join(cwd, "josaa", f"{year}", f"round_{josaa_rounds}", "ranks_gftis.csv") } - josaa_institute_types(CSV_FILES) + josaa_institute_types(CSV_FILES, applied_filters) elif type == "csab": csab_rounds = round csv_path = os.path.join( @@ -263,10 +267,9 @@ def csv_files(type, round, year): f"round_{csab_rounds}", "ranks.csv") df = pd.read_csv(csv_path) - csab_institute_types(df) + csab_institute_types(df, applied_filters) -def csab_institute_types(df): - # clear the screen +def csab_institute_types(df, applied_filters): os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) @@ -282,6 +285,7 @@ def csab_institute_types(df): print(Fore.GREEN + "4." + Fore.BLUE + "GFTIs") # loop until valid input option = None + institute_type_name = "" while option is None: user_input = input(Fore.RESET + "Select Option (1 to 4): ").strip() @@ -293,18 +297,22 @@ def csab_institute_types(df): # filter the dataframe based on the selected option if option == "1": df = df[~df['Institute'].str.contains('Indian Institute of Technology')] + institute_type_name = "ALL (IIITs, NITs, GFTIs)" elif option == "2": df = df[df['Institute'].str.contains('Indian Institute of Information Technology')] + institute_type_name = "IIITs" elif option == "3": df = df[df['Institute'].str.contains('National Institute of Technology')] + institute_type_name = "NITs" elif option == "4": df = df[~df['Institute'].str.contains('National Institute of Technology')] df = df[~df['Institute'].str.contains('Indian Institute of Information Technology')] + institute_type_name = "GFTIs" + + applied_filters["Institute Type"] = institute_type_name + main(df, applied_filters) - main(df) - - -def josaa_institute_types(CSV_FILES): +def josaa_institute_types(CSV_FILES, applied_filters): # clear the screen os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) @@ -341,6 +349,8 @@ def josaa_institute_types(CSV_FILES): else: print(Fore.RED + "Invalid option! Please select a number between 1 and 5." + Fore.RESET) + applied_filters["Institute Type"] = college_type + # read the csv file based on the selected college type csv_path = CSV_FILES[college_type] df = pd.read_csv(csv_path) @@ -348,17 +358,17 @@ def josaa_institute_types(CSV_FILES): if option == "1": # Remove all IITs occurrence if "ALL" option was chosen df = df[~df['Institute'].str.contains('Indian Institute of Technology')] - main(df) + main(df, applied_filters) elif option == "5": # fix ranks with strings in them df['Closing Rank'] = df['Closing Rank'].str.extract(r'(\d+)').astype(float) df['Opening Rank'] = df['Opening Rank'].str.extract(r'(\d+)').astype(int) - main(df) + main(df, applied_filters) else: - main(df) + main(df, applied_filters) -def filter_programs(institute_df): +def filter_programs(institute_df, current_filters): os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) #progress bar for step-4 @@ -386,7 +396,7 @@ def filter_programs(institute_df): print("") program_choices = { - 1: '', + 1: 'All', 2: 'Computer Science and Engineering', 3: 'Artificial Intelligence and Data Science', 4: 'Electronics and Communication Engineering', @@ -404,10 +414,24 @@ def filter_programs(institute_df): program_choices_list = program_input.split() filtered_df = institute_df + + selected_program_names = [] + + if '1' in program_choices_list: + selected_program_names.append("All") + else: + # Build a list of selected program names + for choice in program_choices_list: + if choice.isdigit() and int(choice) in program_choices: + selected_program_names.append(program_choices[int(choice)]) + + # Filter the dataframe + if selected_program_names: + filtered_df = institute_df[institute_df["Academic Program Name"].str.contains( + '|'.join(selected_program_names))] + + current_filters["Program"] = ", ".join(selected_program_names) - if '1' not in program_choices_list: - filtered_df = institute_df[institute_df["Academic Program Name"].str.contains( - '|'.join([program_choices.get(int(choice), '') for choice in program_choices_list]))] if len(filtered_df) == 0: print( @@ -416,6 +440,7 @@ def filter_programs(institute_df): Fore.RESET) return filtered_df + # This part for page 2 can be simplified or adjusted as needed if '13' in program_choices_list: os.system("cls" if os.name == "nt" else "clear") programs = filtered_df["Academic Program Name"].unique() @@ -425,14 +450,14 @@ def filter_programs(institute_df): if program_choice >= 14 and program_choice < 14 + len(programs): program = programs[program_choice - 14] filtered_df = filtered_df[filtered_df["Academic Program Name"] == program] + current_filters["Program"] = program # Update with the specific choice else: print(Fore.RED + "Invalid choice. Please try again." + Fore.RESET) return filtered_df return filtered_df - -def display_df_web(df, heading, subheading): +def display_df_web(df, heading, subheading, applied_filters=None): output_dir = 'output' if not os.path.exists(output_dir): os.makedirs(output_dir) @@ -443,6 +468,15 @@ def display_df_web(df, heading, subheading): # convert the DataFrame to an HTML table html_table = df.to_html(index=False, classes='table',table_id="tableID") + + # Prepare the filters section as HTML + filters_html = "" + if applied_filters: + filters_html += "
" + filters_html += "

Applied Filters:

" # Generate the complete HTML content with headings, CSS styles, and the # table @@ -667,7 +701,6 @@ def display_df_web(df, heading, subheading): }} - @@ -678,13 +711,11 @@ def display_df_web(df, heading, subheading): -

{ heading }

{ subheading }

-
Fork repo Icon @@ -706,8 +737,7 @@ def display_df_web(df, heading, subheading):
- - + {filters_html}
{ html_table }
@@ -750,13 +780,8 @@ def display_df_web(df, heading, subheading): ''' - - - - - # Save the HTML content to the file - with open(filename, "w") as file: + with open(filename, "w", encoding='utf-8') as file: file.write(html_content) #progress bar for step-10 total=100 @@ -797,15 +822,15 @@ def display_df_web(df, heading, subheading): else: subprocess.Popen(["xdg-open", filename], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) - -# main function to run the CLI tool -def main(df): +def main(df, applied_filters): while True: + current_run_filters = applied_filters.copy() institute_df = df os.system("cls" if os.name == "nt" else "clear") - filtered_df = filter_programs(institute_df) + filtered_df = filter_programs(institute_df, current_run_filters) - def filter_by_choices(df, column_name, steps): + # CHANGE: Restored pagination logic within this function + def filter_by_choices(df, column_name, steps, current_filters): unique_choices = list(df[column_name].unique()) os.system("cls" if os.name == "nt" else "clear") @@ -817,10 +842,7 @@ def filter_by_choices(df, column_name, steps): str_steps = f"STEP {steps_count}/10" display_progress_bar(str_steps, steps_completed=steps_completed, total=total, duration=0.3) - print(f"{Fore.YELLOW}Select {column_name}:") - print(Fore.GREEN + "1." + Fore.BLUE + " All") - - # ✅ If Institute list is very long → paginate + # CHANGE: Start of the conditional pagination logic if column_name == "Institute" and len(unique_choices) > 25: page_size = 25 total_pages = (len(unique_choices) + page_size - 1) // page_size @@ -838,7 +860,7 @@ def filter_by_choices(df, column_name, steps): for i, choice in enumerate(page_choices, start=2): print(f"{Fore.GREEN}{i}. {Fore.BLUE}{choice}{Fore.RESET}") - print("\nOptions: [N]ext Page | [P]rev Page | Enter Numbers | [Q]uit selection") + print("\nOptions: [N]ext Page | [P]rev Page | Enter Numbers (e.g., 2 3) | [Q]uit selection") user_input = input("Enter choice: ").strip().lower() if user_input == 'n' and current_page < total_pages: @@ -848,65 +870,86 @@ def filter_by_choices(df, column_name, steps): current_page -= 1 continue elif user_input == 'q': + # Defaulting to all if user quits selection + current_filters[column_name] = "All" return df else: try: - selected_choices = list(map(int, user_input.split())) - if 1 in selected_choices: + selected_choices_indices = list(map(int, user_input.split())) + if 1 in selected_choices_indices: + current_filters[column_name] = "All" return df else: - selected_choices = [idx - 2 for idx in selected_choices] - selected = [page_choices[i] for i in selected_choices if 0 <= i < len(page_choices)] + # Adjust indices for the current page + selected_indices = [idx - 2 for idx in selected_choices_indices] + selected = [page_choices[i] for i in selected_indices if 0 <= i < len(page_choices)] + + if not selected: # Handle invalid number entry + print(Fore.RED + "Invalid number(s). Please try again." + Fore.RESET) + time.sleep(1) + continue + + current_filters[column_name] = ", ".join(selected) return df[df[column_name].isin(selected)] - except: - print("Invalid input, try again.") + except ValueError: + print(Fore.RED + "Invalid input, please use numbers or navigation keys (n, p, q)." + Fore.RESET) time.sleep(1) continue - else: - # ✅ Normal flow for Quota, Seat Type, Gender + # CHANGE: This is the non-paginated flow for Quota, Gender, etc. + print(f"{Fore.YELLOW}Select {column_name}:") + print(Fore.GREEN + "1." + Fore.BLUE + " All") for i, choice in enumerate(unique_choices, start=2): print(f"{Fore.GREEN}{i}. {Fore.BLUE}{choice}{Fore.RESET}") print(f"{Fore.YELLOW}") print(f"You are Selecting {column_name}") choices_input = input("Choose Options ((space-separated, e.g., 2 3 4) & 1 for all choices) : ") - selected_choices = list(map(int, choices_input.split())) - - if 1 in selected_choices: + + try: + selected_choices_indices = list(map(int, choices_input.split())) + except ValueError: + print(Fore.RED + "Invalid input. Defaulting to 'All'." + Fore.RESET) + selected_choices_indices = [1] + time.sleep(1) + + if 1 in selected_choices_indices: + current_filters[column_name] = "All" return df else: - selected_choices = [choice - 2 for choice in selected_choices] - filtered_choices = [unique_choices[i] for i in selected_choices] - return df[df[column_name].isin(filtered_choices)] - - - filtered_df = filter_by_choices(institute_df, "Institute",0.5) + selected_indices = [idx - 2 for idx in selected_choices_indices] + filtered_choice_names = [unique_choices[i] for i in selected_indices if 0 <= i < len(unique_choices)] + current_filters[column_name] = ", ".join(filtered_choice_names) + return df[df[column_name].isin(filtered_choice_names)] - filtered_df = filter_by_choices(institute_df, "Quota",0.6) + filtered_df = filter_by_choices(filtered_df, "Institute", 0.5, current_run_filters) + filtered_df = filter_by_choices(filtered_df, "Quota", 0.6, current_run_filters) + filtered_df = filter_by_choices(filtered_df, "Seat Type", 0.7, current_run_filters) + filtered_df = filter_by_choices(filtered_df, "Gender", 0.8, current_run_filters) - filtered_df = filter_by_choices(institute_df, "Seat Type",0.7) - - filtered_df = filter_by_choices(institute_df, "Gender",0.8) - - - os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) display_progress_bar("STEP 9/10 ",steps_completed=90,total=100, duration=0.3) - rank = int(input(Fore.YELLOW + "Enter your rank: " + Fore.RESET)) - filtered_df["Closing Rank"] = filtered_df["Closing Rank"].astype( - str).str.extract(r"(\d+)").astype(int) - filtered_df = filtered_df[filtered_df["Closing Rank"] > rank].sort_values( - by=["Closing Rank"], ascending=True) + rank = 0 + while True: + try: + rank_input = input(Fore.YELLOW + "Enter your rank: " + Fore.RESET) + rank = int(rank_input) + break + except ValueError: + print(Fore.RED + "Invalid rank. Please enter a number." + Fore.RESET) + + current_run_filters["Your Rank (Show colleges with closing rank >)"] = rank + + filtered_df["Closing Rank"] = filtered_df["Closing Rank"].astype(str).str.extract(r"(\d+)").astype(int) + filtered_df = filtered_df[filtered_df["Closing Rank"] > rank].sort_values(by=["Closing Rank"], ascending=True) os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) - display_df_web(filtered_df, "JEE COUNSELLOR", "~By Ksauraj") - print( - Fore.GREEN + - "Congratulations! File successfully opened in browser. Please wait......" + - Fore.RESET) + + display_df_web(filtered_df, "JEE COUNSELLOR", "~By Ksauraj", applied_filters=current_run_filters) + + print(Fore.GREEN + "Congratulations! File successfully opened in browser. Please wait......" + Fore.RESET) time.sleep(3) os.system("cls" if os.name == "nt" else "clear") print(Fore.GREEN + ascii_art) @@ -920,6 +963,4 @@ def filter_by_choices(df, column_name, steps): elif choice == "3": break - -# run the main function pre_setup()