my new nada program submission

nohup.out

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+ℹ️ cluster id is 9e68173f-9c23-4acc-ba81-4f079b639964
+ℹ️ using 256 bit prime
+ℹ️ storing state in /tmp/.tmp1xYehT (79.99Gbs available)
+🏃 starting nilchain node in: /tmp/.tmp1xYehT/nillion-chain
+⛓  nilchain JSON RPC available at http://127.0.0.1:48102
+⛓  nilchain REST API available at http://localhost:26650
+⛓  nilchain gRPC available at localhost:26649
+🏃 starting node 12D3KooWMvw1hEqm7EWSDEyqTb6pNetUVkepahKY6hixuAuMZfJS
+⏳ waiting until bootnode is up...
+🏃 starting node 12D3KooWAiwGZUwSUaT2bYVxGS8jmfMrfsanZYkHwH3uL7WJPsFq
+🏃 starting node 12D3KooWM3hsAswc7ZT6VpwQ1TCZU4GCYY55nLhcsxCcfjuixW57
+👛 funding nilchain keys
+📝 nillion CLI configuration written to /root/.config/nillion/nillion-cli.yaml
+🌄 environment file written to /root/.config/nillion/nillion-devnet.env
+ℹ️ cluster id is 9e68173f-9c23-4acc-ba81-4f079b639964
+ℹ️ using 256 bit prime
+ℹ️ storing state in /tmp/.tmpgsHTsP (79.99Gbs available)
+🏃 starting nilchain node in: /tmp/.tmpgsHTsP/nillion-chain
+⛓  nilchain JSON RPC available at http://127.0.0.1:48102
+⛓  nilchain REST API available at http://localhost:26650
+⛓  nilchain gRPC available at localhost:26649
+🏃 starting node 12D3KooWMvw1hEqm7EWSDEyqTb6pNetUVkepahKY6hixuAuMZfJS
+⏳ waiting until bootnode is up...
+🏃 starting node 12D3KooWAiwGZUwSUaT2bYVxGS8jmfMrfsanZYkHwH3uL7WJPsFq
+🏃 starting node 12D3KooWM3hsAswc7ZT6VpwQ1TCZU4GCYY55nLhcsxCcfjuixW57
+👛 funding nilchain keys
+📝 nillion CLI configuration written to /root/.config/nillion/nillion-cli.yaml
+🌄 environment file written to /root/.config/nillion/nillion-devnet.env

quickstart/client_code/=0.9.2

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+Requirement already satisfied: cosmpy in /usr/local/lib/python3.10/dist-packages (0.9.2)
+Requirement already satisfied: bech32 in /usr/local/lib/python3.10/dist-packages (from cosmpy) (1.2.0)
+Requirement already satisfied: ecdsa in /usr/local/lib/python3.10/dist-packages (from cosmpy) (0.19.0)
+Requirement already satisfied: googleapis-common-protos in /usr/local/lib/python3.10/dist-packages (from cosmpy) (1.63.2)
+Requirement already satisfied: grpcio in /usr/local/lib/python3.10/dist-packages (from cosmpy) (1.64.1)
+Requirement already satisfied: jsonschema<5,>=3.2.0 in /usr/local/lib/python3.10/dist-packages (from cosmpy) (4.19.2)
+Requirement already satisfied: protobuf<5.0dev,>=4.21.6 in /usr/local/lib/python3.10/dist-packages (from cosmpy) (4.25.3)
+Requirement already satisfied: pycryptodome<4.0.0,>=3.18.0 in /usr/local/lib/python3.10/dist-packages (from cosmpy) (3.20.0)
+Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from cosmpy) (2.8.2)
+Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from cosmpy) (2.31.0)
+Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5,>=3.2.0->cosmpy) (23.2.0)
+Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5,>=3.2.0->cosmpy) (2023.12.1)
+Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5,>=3.2.0->cosmpy) (0.35.1)
+Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5,>=3.2.0->cosmpy) (0.18.1)
+Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from ecdsa->cosmpy) (1.16.0)
+Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->cosmpy) (3.3.2)
+Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->cosmpy) (3.7)
+Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->cosmpy) (2.0.7)
+Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->cosmpy) (2024.6.2)

quickstart/client_code/run_my_first_program.py

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+from nada_dsl import *
+
+def initialize_managers(nr_managers):
+    """
+    Initialize managers with unique identifiers.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+
+    Returns:
+    - managers (list): List of Party objects representing managers.
+    """
+    managers = []
+    for i in range(nr_managers):
+        managers.append(Party(name="Manager" + str(i)))
+
+    return managers
+
+def inputs_initialization(nr_managers, nr_employees, managers):
+    """
+    Initialize inputs for performance scores per employee.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+
+    Returns:
+    - scores_per_employee (list): List of lists representing scores per employee.
+    """
+    scores_per_employee = []
+    for e in range(nr_employees):
+        scores_per_employee.append([])
+        for m in range(nr_managers):
+            scores_per_employee[e].append(
+                SecretUnsignedInteger(
+                    Input(name="m" + str(m) + "_e" + str(e), party=managers[m])
+                )
+            )
+
+    return scores_per_employee
+
+def compute_average_scores(nr_managers, nr_employees, scores_per_employee, outparty):
+    """
+    Compute the average scores for each employee.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+    - scores_per_employee (list): List of lists representing scores per employee.
+
+    Returns:
+    - avg_scores (list): List of Output objects representing average scores for each employee.
+    """
+    avg_scores = []
+    for e in range(nr_employees):
+        total_score = scores_per_employee[e][0]
+        for m in range(1, nr_managers):
+            total_score += scores_per_employee[e][m]
+        average_score = total_score / UnsignedInteger(nr_managers)
+        avg_scores.append(Output(average_score, "avg_score_e" + str(e), outparty))
+
+    return avg_scores
+
+def verify_scores(nr_managers, nr_employees, scores_per_employee, max_score, outparty):
+    """
+    Check if any score exceeds the allowed maximum score.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+    - scores_per_employee (list): List of lists representing scores per employee.
+
+    Returns:
+    - score_checks (list): List of Output objects representing score checks for each employee.
+    - if_cheat_open (list): List of Output objects representing revealed scores of cheating managers.
+    """
+    score_checks = []
+    if_cheat_open = []
+    for e in range(nr_employees):
+        for m in range(nr_managers):
+            score = scores_per_employee[e][m]
+            check = score <= UnsignedInteger(max_score)
+            score_checks.append(Output(check, "check_score_m" + str(m) + "_e" + str(e), outparty))
+            reveal_cheat = check.if_else(UnsignedInteger(0), score)
+            if_cheat_open.append(Output(reveal_cheat, "if_cheat_open_m" + str(m) + "_e" + str(e), outparty))
+
+    return score_checks, if_cheat_open
+
+def nada_main():
+    # Compiled-time constants
+    nr_managers = 3
+    nr_employees = 2
+    max_score = 10  # Example maximum score allowed
+
+    # Parties initialization
+    managers = initialize_managers(nr_managers)
+    outparty = Party(name="OutParty")
+
+    # Inputs initialization
+    scores_per_employee = inputs_initialization(nr_managers, nr_employees, managers)
+
+    # Computation
+    # Compute average scores
+    avg_scores = compute_average_scores(nr_managers, nr_employees, scores_per_employee, outparty)
+    # Check score validity
+    score_checks, if_cheat_open = verify_scores(nr_managers, nr_employees, scores_per_employee, max_score, outparty)
+
+    # Output
+    results = avg_scores + score_checks + if_cheat_open
+    return results
+
+# Run the main function
+nada_main()

quickstart/nada_quickstart_programs/nada-project.toml

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+name = "nada_quickstart_programs"
+version = "0.1.0"
+authors = [""]
+
+[[programs]]
+path = "src/main.py"
+prime_size = 128

quickstart/nada_quickstart_programs/src/main.py

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+from nada_dsl import *
+
+def initialize_managers(nr_managers):
+    """
+    Initialize managers with unique identifiers.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+
+    Returns:
+    - managers (list): List of Party objects representing managers.
+    """
+    managers = []
+    for i in range(nr_managers):
+        managers.append(Party(name="Manager" + str(i)))
+
+    return managers
+
+def inputs_initialization(nr_managers, nr_employees, managers):
+    """
+    Initialize inputs for performance scores per employee.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+
+    Returns:
+    - scores_per_employee (list): List of lists representing scores per employee.
+    """
+    scores_per_employee = []
+    for e in range(nr_employees):
+        scores_per_employee.append([])
+        for m in range(nr_managers):
+            scores_per_employee[e].append(
+                SecretUnsignedInteger(
+                    Input(name="m" + str(m) + "_e" + str(e), party=managers[m])
+                )
+            )
+
+    return scores_per_employee
+
+def compute_average_scores(nr_managers, nr_employees, scores_per_employee, outparty):
+    """
+    Compute the average scores for each employee.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+    - scores_per_employee (list): List of lists representing scores per employee.
+
+    Returns:
+    - avg_scores (list): List of Output objects representing average scores for each employee.
+    """
+    avg_scores = []
+    for e in range(nr_employees):
+        total_score = scores_per_employee[e][0]
+        for m in range(1, nr_managers):
+            total_score += scores_per_employee[e][m]
+        average_score = total_score / UnsignedInteger(nr_managers)
+        avg_scores.append(Output(average_score, "avg_score_e" + str(e), outparty))
+
+    return avg_scores
+
+def verify_scores(nr_managers, nr_employees, scores_per_employee, max_score, outparty):
+    """
+    Check if any score exceeds the allowed maximum score.
+
+    Parameters:
+    - nr_managers (int): Number of managers.
+    - nr_employees (int): Number of employees.
+    - scores_per_employee (list): List of lists representing scores per employee.
+
+    Returns:
+    - score_checks (list): List of Output objects representing score checks for each employee.
+    - if_cheat_open (list): List of Output objects representing revealed scores of cheating managers.
+    """
+    score_checks = []
+    if_cheat_open = []
+    for e in range(nr_employees):
+        for m in range(nr_managers):
+            score = scores_per_employee[e][m]
+            check = score <= UnsignedInteger(max_score)
+            score_checks.append(Output(check, "check_score_m" + str(m) + "_e" + str(e), outparty))
+            reveal_cheat = check.if_else(UnsignedInteger(0), score)
+            if_cheat_open.append(Output(reveal_cheat, "if_cheat_open_m" + str(m) + "_e" + str(e), outparty))
+
+    return score_checks, if_cheat_open
+
+def nada_main():
+    # Compiled-time constants
+    nr_managers = 3
+    nr_employees = 2
+    max_score = 10  # Example maximum score allowed
+
+    # Parties initialization
+    managers = initialize_managers(nr_managers)
+    outparty = Party(name="OutParty")
+
+    # Inputs initialization
+    scores_per_employee = inputs_initialization(nr_managers, nr_employees, managers)
+
+    # Computation
+    # Compute average scores
+    avg_scores = compute_average_scores(nr_managers, nr_employees, scores_per_employee, outparty)
+    # Check score validity
+    score_checks, if_cheat_open = verify_scores(nr_managers, nr_employees, scores_per_employee, max_score, outparty)
+
+    # Output
+    results = avg_scores + score_checks + if_cheat_open
+    return results
+
+# Run the main function
+nada_main()

quickstart_complete/nada_quickstart_programs/src/main.py

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+from nada_dsl import *
+from math import gcd 
+
+def nada_main():
+    party1 = Party(name="Party1")
+
+    my_int1 = SecretInteger(Input(name="my_int1", party=party1))
+    my_int2 = SecretInteger(Input(name="my_int2", party=party1))
+
+    sum_int = my_int1 + my_int2
+
+    difference_int = my_int1 - my_int2
+
+    product_int = my_int1 * my_int2
+
+    quotient_int = my_int1 // my_int2
+
+    gcd_int = gcd(my_int1, my_int2)
+
+    is_multiple = (my_int1 % my_int2) == 0
+    multiple_message = is_multiple.if_else("Yes", "No")
+
+    return [
+        Output(sum_int, "sum_output", party=party1),
+        Output(difference_int, "difference_output", party=party1),
+        Output(product_int, "product_output", party=party1),
+        Output(quotient_int, "quotient_output", party=party1),
+        Output(gcd_int, "gcd_output", party=party1),
+        Output(multiple_message, "multiple_output", party=party1)
+    ]

quickstart_complete/nada_quickstart_programs/src/secret_addition_complete.py

@@ -1,12 +1,11 @@
 from nada_dsl import *
-def nada_main():
 
-    party1 = Party(name="Party1")
 
+def nada_main():
+    party1 = Party(name="Party1")
     my_int1 = SecretInteger(Input(name="my_int1", party=party1))
+    my_int3 = PublicInteger(Input(name="my_int3", party=party1))
 
-    my_int2 = SecretInteger(Input(name="my_int2", party=party1))
-
-    new_int = my_int1 + my_int2
+    new_int = my_int1 / my_int3
 
     return [Output(new_int, "my_output", party1)]