N-queen backtracking in Python: how to return solutions instead of printing them?

def solve(n):
    #prepare a board
    board = [[0 for x in range(n)] for x in range(n)]
    #set initial positions
    place_queen(board, 0, 0)

def place_queen(board, row, column):
    """place a queen that satisfies all the conditions"""
    #base case
    if row > len(board)-1:
        print board
    #check every column of the current row if its safe to place a queen
    while column < len(board):
        if is_safe(board, row, column):
            #place a queen
            board[row][column] = 1
            #place the next queen with an updated board
            return place_queen(board, row+1, 0)
        else:
            column += 1
    #there is no column that satisfies the conditions. Backtrack
    for c in range(len(board)):
        if board[row-1][c] == 1:
            #remove this queen
            board[row-1][c] = 0
            #go back to the previous row and start from the last unchecked column
            return place_queen(board, row-1, c+1)

def is_safe(board, row, column):
    """ if no other queens threaten a queen at (row, queen) return True """
    queens = []
    for r in range(len(board)):
        for c in range(len(board)):
            if board[r][c] == 1:
                queen = (r,c)
                queens.append(queen)
    for queen in queens:
        qr, qc = queen
        #check if the pos is in the same column or row
        if row == qr or column == qc:
            return False
        #check diagonals
        if (row + column) == (qr+qc) or (column-row) == (qc-qr):
            return False
    return True

solve(4)

I wrote Python code for N-queen problem and it prints every possible solution whenever it's found. However, I would like to modify this code so that it returns a list of all the solutions(board configurations) instead of printing them. I tried modifying the code like following:

def solve(n):
    #prepare a board
    board = [[0 for x in range(n)] for x in range(n)]
    #set initial positions
    solutions = []
    place_queen(board, 0, 0, solutions)

def place_queen(board, row, column, solutions):
    """place a queen that satisfies all the conditions"""
    #base case
    if row > len(board)-1:
        solutions.append(board)
        return solutions
    #check every column of the current row if its safe to place a queen
    while column < len(board):
        if is_safe(board, row, column):
            #place a queen
            board[row][column] = 1
            #place the next queen with an updated board
            return place_queen(board, row+1, 0, solutions)
        else:
            column += 1
    #there is no column that satisfies the conditions. Backtrack
    for c in range(len(board)):
        if board[row-1][c] == 1:
            #remove this queen
            board[row-1][c] = 0
            #go back to the previous row and start from the last unchecked column
            return place_queen(board, row-1, c+1, solutions)

However, this returns as soon as the first solution is found, so solutions only consists of one possible board configuration. Since print vs. return has been confusing to me for backtracking algorithms, I would very much appreciate it if someone could show me how to modify the above code, and how to approach similar problems in future.

I assume using a global variable would work, but I learned from somewhere that using global variables for such problem is discouraged. Could someone explain this too?

EDIT:

def solve(n):
    #prepare a board
    board = [[0 for x in range(n)] for x in range(n)]
    #set initial positions
    solutions = list()
    place_queen(board, 0, 0, solutions)
    return solutions

def place_queen(board, row, column, solutions):
    """place a queen that satisfies all the conditions"""
    #base case
    if row > len(board)-1:
        #print board
        solutions.append(deepcopy(board)) #Q1
    #check every column of the current row if its safe to place a queen
    while column < len(board):
        if is_safe(board, row, column):
            #place a queen
            board[row][column] = 1
            #place the next queen with an updated board
            return place_queen(board, row+1, 0, solutions) #Q2
        else:
            column += 1
    #there is no column that satisfies the conditions. Backtrack
    for c in range(len(board)):
        if board[row-1][c] == 1:
            #remove this queen
            board[row-1][c] = 0
            #go back to the previous row and start from the last unchecked column
            return place_queen(board, row-1, c+1, solutions) #Q3

The above returns all the found solutions instead of printing them. I have a few more questions (related parts are marked Q1 and Q2 in above code)

1. Why do we need to solutions.append(deepcopy(board))? In other words, what exactly is happening when we do solutions.append(board) and why does this lead to appending the initial board which is [[0,0,0,0] ...]?
2. Why do we run into a problem when return place_queen(board, row+1, 0) is replaced by place_queen(board, row+1, 0)? We are not actually returning anything (or None), but without return the list goes out of index.