How to use process_output method in autotest

Best Python code snippet using autotest_python

do-svnsync.py

Source:do-svnsync.py

...40        return "Can't find svnlook binary at {}".format(svnlook_bin)41    if not os.path.isdir(local_repo_directory):42        return "Can't find local repository directory at {}".format(local_repo_directory)43    return None44def process_output(file):45    output = file.read().split()46    for x in range(0, len(output)):47        output[x] = output[x].decode()48    return output49def append_to_list(original_list, list_to_append):50    for i in list_to_append:51        original_list.append(i)52def get_remote_dir_names():53    p = Popen([ssh_bin,54               '{}@{}'.format(55                   ssh_user_name,56                   server_name57               ),58               'find',59               '/var/lib/scm/repositories/svn/',60               '-maxdepth', '1',61               '-type', 'd',62               '-exec', 'basename {} \;'], stdout=PIPE, stderr=PIPE)63    output = []64    error = []65    while p.poll() is None:66        sleep(1)67        append_to_list(output, process_output(p.stdout))68        append_to_list(error, process_output(p.stderr))69    append_to_list(output, process_output(p.stdout))70    append_to_list(error, process_output(p.stderr))71    if not p.returncode == 0:72        print("Failed to list remote directories with return code {}".format(p.returncode), file=sys.stderr)73        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)74        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)75        return None76    elif __verbose:77        print(' '.join(output))78    return output79def sync_repo(path):80    # Sync existing mirror with new changes81    p = Popen([svnsync_bin,82               'sync',83               '--username',84               user_name,85               '--password',86               pass_word,87               '--config-option=servers:global:http-library={}'.format(svn_http_client),88               'file://{}'.format(path)], stdout=PIPE, stderr=PIPE)89    output = []90    error = []91    while p.poll() is None:92        sleep(1)93        append_to_list(output, process_output(p.stdout))94        append_to_list(error, process_output(p.stderr))95    append_to_list(output, process_output(p.stdout))96    append_to_list(error, process_output(p.stderr))97    if not p.returncode == 0:98        print("Svnsync sync failed with return code {}".format(p.returncode), file=sys.stderr)99        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)100        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)101        return False102    elif __verbose:103        print(' '.join(output))104    return True105def create_sync_repo(path, url):106    # Create new repository107    p = Popen([svnadmin_bin,108               'create',109               path], stdout=PIPE, stderr=PIPE)110    output = []111    error = []112    while p.poll() is None:113        sleep(1)114        append_to_list(output, process_output(p.stdout))115        append_to_list(error, process_output(p.stderr))116    append_to_list(output, process_output(p.stdout))117    append_to_list(error, process_output(p.stderr))118    if not p.returncode == 0:119        print("Svnadmin create failed with return code {}".format(p.returncode), file=sys.stderr)120        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)121        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)122        return False123    if __verbose:124        print(' '.join(output))125    revprop_path = None126    # Prep for svnsync127    try:128        # Make sure pre-revprop-change has content129        revprop_path = "{}/hooks/pre-revprop-change".format(path)130        with open(revprop_path, 'w') as out:131            out.write("#!/bin/sh")132        p = Popen(['chmod',133                   '755',134                   revprop_path], stdout=PIPE, stderr=PIPE)135        # Safely process the output136        output = []137        error = []138        while p.poll() is None:139            sleep(1)140            append_to_list(output, process_output(p.stdout))141            append_to_list(error, process_output(p.stderr))142        append_to_list(output, process_output(p.stdout))143        append_to_list(error, process_output(p.stderr))144        if not p.returncode == 0:145            print("chmod 755 failed with return code {}".format(p.returncode), file=sys.stderr)146            print("Process Output: {}".format(' '.join(output)), file=sys.stderr)147            print("Error Output: {}".format(' '.join(error)), file=sys.stderr)148            return False149        elif __verbose:150            print(' '.join(output))151    except IOError as err:152        print("An error occurred while writing to {} with error code {}: {}".format(153            revprop_path, err.errno, err.output), file=sys.stderr)154        return False155    # Now we're ready for svnsync init156    p = Popen([svnsync_bin,157               'init',158               '--username',159               user_name,160               '--password',161               pass_word,162               'file://{}'.format(path),163               url], stdout=PIPE, stderr=PIPE)164    # Safely process the output165    output = []166    error = []167    while p.poll() is None:168        sleep(1)169        append_to_list(output, process_output(p.stdout))170        append_to_list(error, process_output(p.stderr))171    append_to_list(output, process_output(p.stdout))172    append_to_list(error, process_output(p.stderr))173    if not (p.returncode == 0 or p.returncode == 1):174        print("Svnsync init failed with return code {}".format(p.returncode), file=sys.stderr)175        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)176        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)177        return False178    elif __verbose:179        print(p.stdout.readlines())180    p = Popen([svnlook_bin,181               'pg',182               '--revprop',183               '-r0',184               path,185               r'svn:sync-from-uuid'], stdout=PIPE, stderr=PIPE)186    # Safely process the output187    output = []188    error = []189    while p.poll() is None:190        sleep(1)191        append_to_list(output, process_output(p.stdout))192        append_to_list(error, process_output(p.stderr))193    append_to_list(output, process_output(p.stdout))194    append_to_list(error, process_output(p.stderr))195    if not p.returncode == 0:196        print("Svnlook pg failed with return code {}".format(p.returncode), file=sys.stderr)197        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)198        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)199        return False200    # Don't worry about displaying the output of svnlook pg, only contains a uuid if it succeeds201    # Speaking of which, set uuid to the output202    uuid = ''.join(output)203    p = Popen([svnadmin_bin,204               'setuuid',205               path,206               uuid], stdout=PIPE, stderr=PIPE)207    # Safely process the output208    output = []209    error = []210    while p.poll() is None:211        sleep(1)212        append_to_list(output, process_output(p.stdout))213        append_to_list(error, process_output(p.stderr))214    append_to_list(output, process_output(p.stdout))215    append_to_list(error, process_output(p.stderr))216    if not p.returncode == 0:217        print("Svnadmin setuuid failed with return code {}".format(p.returncode), file=sys.stderr)218        print("Process Output: {}".format(' '.join(output)), file=sys.stderr)219        print("Error Output: {}".format(' '.join(error)), file=sys.stderr)220        return False221    elif __verbose:222        print(' '.join(output))223    return True224# Main Function225def main():226    print("Enumerating directories from {}".format(server_name))227    names = get_remote_dir_names()228    if names is None:229        sys.exit(-2)...

backend_kalman_filter.py

Source:backend_kalman_filter.py

1import numpy as np2import streamlit as st3import plotly.express as px4import plotly.graph_objects as go5from pandas import DataFrame as df6class FrontEndUtils:7    def filter_plot(self, process_output):8        plot_df = df(process_output)9        output_fig = px.line(10            plot_df,11            x="Time",12            y=[13                "Error Estimation",14                "Angle Estimation",15                "Zero Order Sensor",16                "Gyroscope Angle",17            ],18        )19        gain_fig = px.line(plot_df, x="Iteration", y=["Kalman Gain 1", "Kalman Gain 2"])20        st.markdown("### Comparing Output")21        st.plotly_chart(output_fig, use_container_width=True)22        st.markdown("### Gain Update")23        st.plotly_chart(gain_fig, use_container_width=True)24    def plot_best_kalman(self, best_kalman):25        z = best_kalman["RMSE"]26        best_kalman_df = df({"n": best_kalman["n"], "e": best_kalman["e"]})27        fig = go.Figure(28            data=[go.Surface(z=z, x=best_kalman_df["n"], y=best_kalman_df["e"])]29        )30        fig.update_layout(xaxis_title="n", yaxis_title="e")31        st.plotly_chart(fig, use_container_width=True)32class BackEndUtils:33    def padding(self, x):34        log = np.log2(len(x))35        return np.pad(36            x, (0, int(2 ** ((log - log % 1) + 1) - len(x))), mode="constant"37        ).flatten()38    def FFT(self, x):39        if np.log2(len(x)) % 1 > 0:40            x = self.padding(x)41        x = np.asarray(x, dtype=float)42        N = x.shape[0]43        N_min = min(N, 2)44        # DFT on all length-N_min sub-problems at once45        n = np.arange(N_min)46        k = n[:, None]47        W = np.exp(-2j * np.pi * n * k / N_min)48        X = np.dot(W, x.reshape((N_min, -1)))49        # Recursive calculation all at once50        while X.shape[0] < N:51            X_even = X[:, : int(X.shape[1] / 2)]52            X_odd = X[:, int(X.shape[1] / 2) :]53            factor = np.exp(-1j * np.pi * np.arange(X.shape[0]) / X.shape[0])[:, None]54            factor.shape, factor55            X = np.vstack([X_even + factor * X_odd, X_even - factor * X_odd])56        return X.flatten()57    @st.cache58    def load_data(self):59        raw_data = np.loadtxt("trial1.dat")60        data = {}61        data["Time"] = raw_data[:, 0].flatten()62        data["Zero Order Sensor"] = raw_data[:, 1].flatten()63        data["Gyroscope"] = raw_data[:, 3].flatten()64        data["Tilt Sensor"] = raw_data[:, 4].flatten()65        return data66    def rmse(self, y_true, y_pred):67        return np.sqrt(np.mean((y_true - y_pred) ** 2))68class KalmanFilter(BackEndUtils):69    def __init__(self):70        self.data = self.load_data()71        self.dtm = self.data["Gyroscope"] - self.data["Tilt Sensor"]72    def fast_process(self, kalman_filter_state):73        A = np.array([[1, 1], [0, 1]])74        B = np.array([[1], [1]])75        n = kalman_filter_state["n"]76        e = kalman_filter_state["e"]77        post_error_covar = np.zeros((2, 2))78        kalman_gain = np.zeros((2, len(self.dtm)))79        d_theta_b_h_min = np.zeros((2, len(self.dtm) + 1))80        d_theta_b_h = np.zeros((2, len(self.dtm)))81        for i in np.arange(len(self.dtm)):82            # Priory Covar Calculation83            priori_error_covar = np.dot(A, np.dot(post_error_covar, A.T)) + B * B.T * e84            # Kalman Gain Calculation85            kalman_gain[:, i] = priori_error_covar[:, 0] / (86                priori_error_covar[0, 0] + n87            )88            # Kalman Filtering (Estimation)89            v = self.dtm[i] - d_theta_b_h_min[0, i]90            d_theta_b_h[:, i] = d_theta_b_h_min[:, i] + kalman_gain[:, i] * v91            # Post Covar Update92            post_copy = post_error_covar.copy()93            post_error_covar[0, :] = post_copy[0, :] * np.array([1, -kalman_gain[0, i]])94            post_error_covar[1, :] = np.dot(95                np.array([-kalman_gain[1, i], 1]), post_copy96            )97            # Prediction98            d_theta_b_h_min[:, i + 1] = np.dot(99                np.array([[1, 1], [0, 1]]), d_theta_b_h[:, i].reshape(-1, 1)100            ).flatten()101        return {102            "RMSE": self.rmse(103                self.data["Zero Order Sensor"],104                self.data["Gyroscope"] - d_theta_b_h[0, :],105            )106        }107    def process(self, kalman_filter_state):108        process_output = {}109        theta = self.data["Gyroscope"]110        # Input Difference111        dtm = self.data["Gyroscope"] - self.data["Tilt Sensor"]112        filter_output = self.kalman_filter(dtm, kalman_filter_state)113        process_output = filter_output114        process_output["Angle Estimation"] = theta - filter_output["Error Estimation"]115        process_output["Zero Order Sensor"] = self.data["Zero Order Sensor"]116        process_output["Gyroscope Angle"] = self.data["Gyroscope"]117        process_output["Tilt Sensor"] = self.data["Tilt Sensor"]118        process_output["RMSE"] = self.rmse(119            process_output["Zero Order Sensor"], process_output["Angle Estimation"]120        )121        return process_output122    def kalman_filter(self, input_filter, kalman_filter_state):123        # Initialize124        dtm = input_filter125        A = np.array([[1, 1], [0, 1]])126        B = np.array([[1], [1]])127        n = kalman_filter_state["n"]128        e = kalman_filter_state["e"]129        post_error_covar = np.zeros((2, 2))130        kalman_gain = np.zeros((2, len(dtm)))131        d_theta_b_h_min = np.zeros((2, len(dtm) + 1))132        d_theta_b_h = np.zeros((2, len(dtm)))133        for i in np.arange(len(dtm)):134            # Priory Covar Calculation135            priori_error_covar = np.dot(A, np.dot(post_error_covar, A.T)) + B * B.T * e136            # Kalman Gain Calculation137            kalman_gain[:, i] = priori_error_covar[:, 0] / (138                priori_error_covar[0, 0] + n139            )140            # Kalman Filtering (Estimation)141            v = dtm[i] - d_theta_b_h_min[0, i]142            d_theta_b_h[:, i] = d_theta_b_h_min[:, i] + kalman_gain[:, i] * v143            # Post Covar Update144            post_copy = post_error_covar.copy()145            post_error_covar[0, :] = post_copy[0, :] * np.array([1, -kalman_gain[0, i]])146            post_error_covar[1, :] = np.dot(147                np.array([-kalman_gain[1, i], 1]), post_copy148            )149            # Prediction150            d_theta_b_h_min[:, i + 1] = np.dot(151                np.array([[1, 1], [0, 1]]), d_theta_b_h[:, i].reshape(-1, 1)152            ).flatten()153        filter_output = {}154        filter_output["Kalman Gain 1"] = kalman_gain[0, :]155        filter_output["Kalman Gain 2"] = kalman_gain[1, :]156        filter_output["Error Estimation"] = d_theta_b_h[0, :]157        filter_output["Prediction"] = d_theta_b_h_min[0, :-1]158        filter_output["Time"] = self.data["Time"]159        filter_output["Iteration"] = np.arange(len(dtm))160        return filter_output161    def best_kalman_parameter_search(self, best_parameter_state):162        range_n_start = best_parameter_state["N Start"]163        range_n_end = best_parameter_state["N End"]164        range_e_start = best_parameter_state["E Start"]165        range_e_end = best_parameter_state["E End"]166        data_amount = best_parameter_state["Data Amount"]167        z_output = np.zeros((data_amount, data_amount))168        n = np.linspace(range_n_start, range_n_end, data_amount)169        e = np.linspace(range_e_start, range_e_end, data_amount)170        progress_bar = st.progress(0.0)171        amount = 0.0172        for i in range(data_amount):173            for j in range(data_amount):174                process_output = self.fast_process({"n": n[i], "e": e[j]})175                z_output[i, j] = process_output["RMSE"]176                amount += 1177                progress_bar.progress((amount) / (data_amount ** 2))178        # st.write(z_output)...

exec_command.py

Source:exec_command.py

...161            raise Exception(msg)162    return error_code163################################################################################164#165def print_process_output(166    process_output,167    suppress_success_output = False,168):169    if suppress_success_output:170        if "code" in process_output.keys():171            if process_output["code"] == 0:172                return173    if "stdout" in process_output.keys():174        # Use stderr to print stdout of the command.175        # If stdout results were captured,176        # they are not meant to be on stdout by default.177        logging.info(process_output["stdout"])178    if "stderr" in process_output.keys():179        logging.info(process_output["stderr"])...

views.py

Source:views.py

1from rest_framework.decorators import api_view2from rest_framework import status3from rest_framework.response import Response4from mvp_cd.deploy_app.models import (BuildInfo, ServerBuildInfo, ServerType)5import subprocess6from django.shortcuts import render_to_response7import json8from django.shortcuts import get_object_or_4049ALLOWED_BRANCHES = ['staging', 'production']10@api_view(['POST'])11def deploy_view(request):12    if request.data['payload']['outcome'] == 'success':13        if request.data['payload']['branch'] not in ALLOWED_BRANCHES:14            return Response(status=status.HTTP_204_NO_CONTENT)15        vcs_revision = request.data['payload']['vcs_revision']16        build_info_obj = BuildInfo(17            circleci_json=request.data,18            branch=request.data['payload']['branch'],19            commiter=request.data['payload']['author_name'],20            circleci_url=request.data['payload']['build_url'],21            vcs_revision=vcs_revision)22        build_info_obj.save()23        with open('deploy_config.json') as data_file:24            deploy_config = json.load(data_file)25            pem_path = deploy_config['pem_path']26            deployment_path = deploy_config['deployment_path']27        if request.data['payload']['branch'] == 'staging':28            for ip in deploy_config['staging_celery_ips']:29                deploy_celery_staging(30                    request, ip, pem_path, deployment_path,31                    build_info_obj, vcs_revision)32            for ip in deploy_config['staging_app_server_ips']:33                deploy_app_staging(34                    request, ip, pem_path, deployment_path,35                    build_info_obj, vcs_revision)36            return Response(status=status.HTTP_204_NO_CONTENT)37        elif request.data['payload']['branch'] == 'production':38            for ip in deploy_config['production_celery_ips']:39                deploy_celery_production(40                    request, ip, pem_path, deployment_path,41                    build_info_obj, vcs_revision)42            for ip in deploy_config['production_app_server_ips']:43                deploy_app_production(44                    request, ip, pem_path, deployment_path,45                    build_info_obj, vcs_revision)46            return Response(status=status.HTTP_204_NO_CONTENT)47    return Response(status=status.HTTP_400_BAD_REQUEST)48def build_list_view(request):49    build_info = BuildInfo.objects.all().order_by('-id')[:10]50    return render_to_response(51        'build_list.html', {'build_list': build_info})52def build_detail_view(request, id):53    build_info = get_object_or_404(BuildInfo, id=id)54    serverbuildinfo_list = build_info.serverbuildinfo_set.all().order_by('-id')55    return render_to_response(56        'build_info.html',57        {'build_info_item': build_info,58         'serverbuildinfo_list': serverbuildinfo_list})59def deploy_celery_staging(60        request, ip, pem_path, deployment_path,61        build_info_obj, vcs_revision):62    try:63        process_output = subprocess.check_output(64            ['bash', 'deploy_worker.sh', pem_path,65             ip, deployment_path, vcs_revision, 'mvpserver.settings.staging'],66            stdin=subprocess.PIPE)67        process_status(68            request, process_output, 0, ip,69            ServerType.WORKER, build_info_obj)70    except subprocess.CalledProcessError as e:71        process_status(72            request, e.output, 1, ip,73            ServerType.WORKER, build_info_obj)74def deploy_celery_production(75        request, ip, pem_path, deployment_path,76        build_info_obj, vcs_revision):77    try:78        process_output = subprocess.check_output(79            ['bash', 'deploy_worker.sh', pem_path, ip, deployment_path,80             vcs_revision, 'mvpserver.settings.production'],81            stdin=subprocess.PIPE)82        process_status(83            request, process_output, 0, ip,84            ServerType.WORKER, build_info_obj)85    except subprocess.CalledProcessError as e:86        process_status(87            request, e.output, 1, ip,88            ServerType.WORKER, build_info_obj)89def deploy_app_staging(90        request, ip, pem_path, deployment_path,91        build_info_obj, vcs_revision):92    try:93        process_output = subprocess.check_output(94            ['bash', 'deploy_app.sh', pem_path, ip, deployment_path,95             vcs_revision, 'mvpserver.settings.staging'],96            stdin=subprocess.PIPE)97        process_status(98            request, process_output, 0, ip,99            ServerType.APP_SERVER, build_info_obj)100    except subprocess.CalledProcessError as e:101        process_status(102            request, e.output, 1, ip,103            ServerType.APP_SERVER, build_info_obj)104def deploy_app_production(105        request, ip, pem_path, deployment_path,106        build_info_obj, vcs_revision):107    try:108        process_output = subprocess.check_output(109            ['bash', 'deploy_app.sh', pem_path, ip, deployment_path,110             vcs_revision, 'mvpserver.settings.production'],111            stdin=subprocess.PIPE)112        process_status(113            request, process_output, 0, ip,114            ServerType.APP_SERVER, build_info_obj)115    except subprocess.CalledProcessError as e:116        process_status(117            request, e.output, 1, ip,118            ServerType.APP_SERVER, build_info_obj)119def process_status(120        request, process_output, process_status,121        ip, server_type, build_info_obj):122    print(process_output)123    if process_status == 0:124        build_info_item = ServerBuildInfo(125            is_success=True,126            console_output=process_output,127            ip=ip,128            server_type=server_type,129            build_info=build_info_obj)130        build_info_obj.deployment_status = True131        build_info_obj.save()132        build_info_item.save()133    else:134        build_info_item = ServerBuildInfo(135            is_success=False,136            console_output=process_output,137            ip=ip,138            server_type=server_type,139            build_info=build_info_obj)140        build_info_obj.deployment_status = False141        build_info_obj.save()...

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