Added HTTP URLs to HTTPS URLs finder & converter Python scripts, and processed HTTP-->HTTPS URL changes by mstfbl · Pull Request #346 · microsoft/NimbusML

This repository was archived by the owner on Nov 16, 2023. It is now read-only.

src/DotNetBridge/MessageValidator.cs

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -195,7 +195,7 @@ public sealed class MessageValidator
  
                    {

                        return "Failed to initialize CUDA runtime. Possible reasons:" + "\n" +

                                @"1. The machine does not have CUDA-capable card. Supported devices have compute capability 2.0 and higher." + "\n" +

                                @"2. Outdated graphics drivers. Please install the latest drivers from http://www.nvidia.com/Drivers ." + "\n" +

                                @"2. Outdated graphics drivers. Please install the latest drivers from https://www.nvidia.com/Download/index.aspx?lang=en-us ." + "\n" +

                                @"3. CUDA runtime DLLs are missing, please see the GPU acceleration help for the installation instructions.";

                    }

                )

src/NativeBridge/DataViewInterop.h

-Original file line number
+Diff line change
@@ Expand Up @@
     // REVIEW: boost_python is not updated at the same speed as swig or pybind11.
     // Both have a larger audience now, see about pybind11 https://github.com/davisking/dlib/issues/293
-    // It handles csr_matrix: http://pybind11-rtdtest.readthedocs.io/en/stable/advanced.html#transparent-conversion-of-dense-and-sparse-eigen-data-types.
+    // It handles csr_matrix: https://pybind11-rtdtest.readthedocs.io/en/stable/advanced.html#transparent-conversion-of-dense-and-sparse-eigen-data-types.
     using namespace boost::python;
     // The data source wrapper used for managed interop. Some of the fields of this are visible to managed code.
@@ Expand Down @@

src/python/docs/docstrings/AveragedPerceptronBinaryClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -45,10 +45,10 @@
  
                <https://en.wikipedia.org/wiki/Perceptron>`_

                `Large Margin Classification Using the Perceptron Algorithm

                <http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8200>`_

                <https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8200>`_

                `Discriminative Training Methods for Hidden Markov Models

                <http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.6725>`_

                <https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.6725>`_

        :param loss: The default is :py:class:`'hinge' <nimbusml.loss.Hinge>`. Other

src/python/docs/docstrings/FactorizationMachineBinaryClassifier.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -22,7 +22,7 @@ @@
                 `Field Aware Factorization Machines
                 <https://www.csie.ntu.edu.tw/~r01922136/slides/ffm.pdf>`_,
                 `Field-aware Factorization Machines for CTR Prediction
-                <http://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf>`_,
+                <https://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf>`_,
                 `Adaptive Subgradient Methods for Online Learning and Stochastic
                 Optimization
                 <http://jmlr.org/papers/volume12/duchi11a/duchi11a.pdf>`_
@@ Expand Down @@

src/python/docs/docstrings/FastForestBinaryClassifier.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -33,7 +33,7 @@ @@
             **Reference**
                 `Wikipedia: Random forest
-                <http://en.wikipedia.org/wiki/Random_forest>`_
+                <https://en.wikipedia.org/wiki/Random_forest>`_
                 `Quantile regression forest
                 <http://jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf>`_
@@ Expand Down @@

src/python/docs/docstrings/FastForestRegressor.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -43,7 +43,7 @@ @@
             **Reference**
                 `Wikipedia: Random forest
-                <http://en.wikipedia.org/wiki/Random_forest>`_
+                <https://en.wikipedia.org/wiki/Random_forest>`_
                 `Quantile regression forest
                 <http://jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf>`_
@@ Expand Down @@

src/python/docs/docstrings/FastLinearBinaryClassifier.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -58,8 +58,7 @@ @@
                 content/uploads/2016/06/main-3.pdf>`_
                 `Stochastic Dual Coordinate Ascent Methods for Regularized Loss
-                Minimization <http://www.jmlr.org/papers/volume14/shalev-
-                shwartz13a/shalev-shwartz13a.pdf>`_
+                Minimization <http://www.jmlr.org/papers/volume14/shalev-shwartz13a/shalev-shwartz13a.pdf>`_
         :param loss: The default is :py:class:`'log' <nimbusml.loss.Log>`. Other
@@ Expand Down @@

src/python/docs/docstrings/FastLinearClassifier.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -56,8 +56,7 @@ @@
                 content/uploads/2016/06/main-3.pdf>`_
                 `Stochastic Dual Coordinate Ascent Methods for Regularized Loss
-                Minimization <http://www.jmlr.org/papers/volume14/shalev-
-                shwartz13a/shalev-shwartz13a.pdf>`_
+                Minimization <http://www.jmlr.org/papers/volume14/shalev-shwartz13a/shalev-shwartz13a.pdf>`_
         :param feature: see `Columns </nimbusml/concepts/columns>`_.
@@ Expand Down @@

src/python/docs/docstrings/FastLinearRegressor.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -56,8 +56,7 @@ @@
                 content/uploads/2016/06/main-3.pdf>`_
                 `Stochastic Dual Coordinate Ascent Methods for Regularized Loss
-                Minimization <http://www.jmlr.org/papers/volume14/shalev-
-                shwartz13a/shalev-shwartz13a.pdf>`_
+                Minimization <http://www.jmlr.org/papers/volume14/shalev-shwartz13a/shalev-shwartz13a.pdf>`_
         :param loss: The only supported loss is :py:class:`'squared'
@@ Expand Down @@

src/python/docs/docstrings/FastTreesBinaryClassifier.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -57,7 +57,7 @@ @@
                 <https://en.wikipedia.org/wiki/Gradient_boosting#Gradient_tree_boosting>`_
                 `Greedy function approximation: A gradient boosting machine.
-                <http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
+                <https://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
         :param optimizer: Default is ``sgd``.
@@ Expand Down @@

src/python/docs/docstrings/FastTreesRegressor.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -62,7 +62,7 @@ @@
                 <https://en.wikipedia.org/wiki/Gradient_boosting#Gradient_tree_boosting>`_
                 `Greedy function approximation: A gradient boosting machine.
-                <http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
+                <https://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
         :param optimizer: Default is ``sgd``.
@@ Expand Down @@

src/python/docs/docstrings/FastTreesTweedieRegressor.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -14,7 +14,7 @@ @@
                 <https://en.wikipedia.org/wiki/Gradient_boosting#Gradient_tree_boosting>`_
                 `Greedy function approximation: A gradient boosting machine.
-                <http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
+                <https://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1013203451>`_
         :param optimizer: Default is ``sgd``.
@@ Expand Down @@

src/python/docs/docstrings/GamBinaryClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -21,7 +21,7 @@
  
            functions learned will step between the discretization boundaries.

            This implementation is based on the this `paper

            <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_,

            <https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_,

            but diverges from it in several important respects: most

            significantly,

            in each round of boosting, rather than do one feature at a time, it

    @@ -57,7 +57,7 @@
  
                `Generalized additive models

                <https://en.wikipedia.org/wiki/Generalized_additive_model>`_,

                `Intelligible Models for Classification and Regression

                <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_

                <https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_

        :param normalize: Specifies the type of automatic normalization used:

src/python/docs/docstrings/GamRegressor.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -21,7 +21,7 @@
  
            functions learned will step between the discretization boundaries.

            This implementation is based on the this `paper

            <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_,

            <https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_,

            but diverges from it in several important respects: most

            significantly,

            in each round of boosting, rather than do one feature at a time, it

    @@ -57,7 +57,7 @@
  
                `Generalized additive models

                <https://en.wikipedia.org/wiki/Generalized_additive_model>`_,

                `Intelligible Models for Classification and Regression

                <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_

                <https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.7619>`_

        :param normalize: Specifies the type of automatic normalization used:

src/python/docs/docstrings/LightLda.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -10,7 +10,7 @@
  
            topical vectors. LightLDA is an extremely

            efficient implementation of LDA developed in MSR-Asia that

            incorporates a number of optimization techniques

            `(http://arxiv.org/abs/1412.1576) <http://arxiv.org/abs/1412.1576>`_.

            `(https://arxiv.org/abs/1412.1576) <https://arxiv.org/abs/1412.1576>`_.

            With the LDA transform, we can

            train a topic model to produce 1 million topics with 1 million

            vocabulary on a 1-billion-token document set one

src/python/docs/docstrings/LocalDeepSvmBinaryClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -39,14 +39,14 @@
  
            More details about LD-SVM can be found in this paper `Local deep

            kernel

            learning for efficient non-linear SVM prediction

            <http://research.microsoft.com/en-

            <https://research.microsoft.com/en-

            us/um/people/manik/pubs/Jose13.pdf>`_.

            **Reference**

                `Local deep kernel learning for efficient non-linear SVM prediction

                <http://research.microsoft.com/en-

                <https://research.microsoft.com/en-

                us/um/people/manik/pubs/Jose13.pdf>`_

src/python/docs/docstrings/LogisticRegressionBinaryClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -69,14 +69,14 @@
  
            **Reference**

                `Wikipedia: L-BFGS <http://en.wikipedia.org/wiki/L-BFGS>`_

                `Wikipedia: L-BFGS <https://en.wikipedia.org/wiki/L-BFGS>`_

                `Wikipedia: Logistic

                regression <http://en.wikipedia.org/wiki/Logistic_regression>`_

                regression <https://en.wikipedia.org/wiki/Logistic_regression>`_

                `Scalable

                Training of L1-Regularized Log-Linear Models

                <http://research.microsoft.com/apps/pubs/default.aspx?id=78900>`_

                <https://research.microsoft.com/apps/pubs/default.aspx?id=78900>`_

                `Test Run - L1

                and L2 Regularization for Machine Learning

src/python/docs/docstrings/LogisticRegressionClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -70,14 +70,14 @@
  
            **Reference**

                `Wikipedia: L-BFGS <http://en.wikipedia.org/wiki/L-BFGS>`_

                `Wikipedia: L-BFGS <https://en.wikipedia.org/wiki/L-BFGS>`_

                `Wikipedia: Logistic

                regression <http://en.wikipedia.org/wiki/Logistic_regression>`_

                regression <https://en.wikipedia.org/wiki/Logistic_regression>`_

                `Scalable

                Training of L1-Regularized Log-Linear Models

                <http://research.microsoft.com/apps/pubs/default.aspx?id=78900>`_

                <https://research.microsoft.com/apps/pubs/default.aspx?id=78900>`_

                `Test Run - L1

                and L2 Regularization for Machine Learning

src/python/docs/docstrings/OneClassSVMAnomalyDetector.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -29,10 +29,10 @@
  
                us/library/azure/dn913103.aspx>`_

                `Estimating the Support of a High-Dimensional Distribution

                <http://research.microsoft.com/pubs/69731/tr-99-87.pdf>`_

                <https://research.microsoft.com/pubs/69731/tr-99-87.pdf>`_

                `New Support Vector Algorithms

                <http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf>`_

                <https://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf>`_

                `LIBSVM: A Library for Support Vector Machines

                <https://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf>`_

src/python/docs/docstrings/PcaAnomalyDetector.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -36,13 +36,12 @@ @@
                 `Randomized Methods for Computing the Singular Value Decomposition
                 (SVD) of very large matrices
-                <http://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf>`_
+                <https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf>`_
                 `A randomized algorithm for principal component analysis
                 <https://arxiv.org/abs/0809.2274>`_,
                 `Finding Structure with Randomness: Probabilistic Algorithms for
                 Constructing Approximate Matrix Decompositions
-                <http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-
-                SIREV.pdf>`_
+                <http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf>`_
         :param feature: see `Columns </nimbusml/concepts/columns>`_.
@@ Expand Down @@

src/python/docs/docstrings/SgdBinaryClassifier.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -13,14 +13,14 @@
  
            associated optimization problem is sparse, then Hogwild SGD achieves

            a

            nearly optimal rate of convergence. For a detailed reference, please

            refer to `http://arxiv.org/pdf/1106.5730v2.pdf

            <http://arxiv.org/pdf/1106.5730v2.pdf>`_.

            refer to `https://arxiv.org/pdf/1106.5730v2.pdf

            <https://arxiv.org/pdf/1106.5730v2.pdf>`_.

            **Reference**

                `http://arxiv.org/pdf/1106.5730v2.pdf

                <http://arxiv.org/pdf/1106.5730v2.pdf>`_

                `https://arxiv.org/pdf/1106.5730v2.pdf

                <https://arxiv.org/pdf/1106.5730v2.pdf>`_

        :param normalize: Specifies the type of automatic normalization used:

src/python/docs/docstrings/SigmoidKernel.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -3,8 +3,7 @@ @@
         Apply sigmoid function. tanh(gamma*<x,y>+c).
         .. remarks::
-            `SigmoidKernel <http://www2.spsc.tugraz.at/www-
-            archive/AdvancedSignalProcessing/WS05-Mistral/advances.pdf>`_ is a
+            `SigmoidKernel <https://www2.spsc.tugraz.at/www-archive/AdvancedSignalProcessing/WS05-Mistral/advances.pdf>`_ is a
             kernel function
             that computes the similarity between two features.
@@ Expand Down @@

src/python/docs/docstrings/SsaForecaster.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -11,7 +11,7 @@ @@
             input time-series where each component in the spectrum corresponds to a
             trend, seasonal or noise component in the time-series. For details of the
             Singular Spectrum Analysis (SSA), refer to `this document
-            <http://arxiv.org/pdf/1206.6910.pdf>`_.
+            <https://arxiv.org/pdf/1206.6910.pdf>`_.
         .. seealso::
             :py:func:`IIDChangePointDetector
@@ Expand Down @@

src/python/docs/docstrings/SsweEmbedding.txt

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -7,12 +7,12 @@
  
        versions of `GloVe Models

        <https://nlp.stanford.edu/projects/glove/>`_, `FastText

        <https://en.wikipedia.org/wiki/FastText>`_, and `Sswe

        <http://anthology.aclweb.org/P/P14/P14-1146.pdf>`_.

        <https://anthology.aclweb.org/P/P14/P14-1146.pdf>`_.

        .. remarks::

            Sentiment-specific word embedding (SSWE) is a DNN featurizer

            developed

            by MSRA (`paper <http://anthology.aclweb.org/P/P14/P14-1146.pdf>`_).

            by MSRA (`paper <https://anthology.aclweb.org/P/P14/P14-1146.pdf>`_).

            It

            incorporates sentiment information into the neural network to learn

            sentiment specific word embedding. It proves to be useful in various

src/python/docs/docstrings/SupervisedBinner.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -24,7 +24,7 @@ @@
             the default is to normalize features before training.
             ``SupervisedBinner`` implements the `Entropy-Based Discretization
-            <http://www.aaai.org/Papers/KDD/1996/KDD96-019.pdf>`_.
+            <https://www.aaai.org/Papers/KDD/1996/KDD96-019.pdf>`_.
             Partition of the data is performed recursively to select the split
             with highest entropy gain with respect to the label.
             Therefore, the final binned features will have high correlation with
@@ Expand Down @@

src/python/docs/docstrings/WordEmbedding.txt

-Original file line number
+Diff line change
@@ Expand Up / @@ -10,7 +10,7 @@ @@
             available options are various versions of `GloVe Models
             <https://nlp.stanford.edu/projects/glove/>`_, `FastText
             <https://en.wikipedia.org/wiki/FastText>`_, and `Sswe
-            <http://anthology.aclweb.org/P/P14/P14-1146.pdf>`_.
+            <https://anthology.aclweb.org/P/P14/P14-1146.pdf>`_.
         :param model_kind: Pre-trained model used to create the vocabulary.
@@ Expand Down @@

src/python/docs/sphinx/ci_script/_static/mystyle.css

-Original file line number
+Diff line change
@@ Expand Up / @@ -8432,7 +8432,7 @@ label { @@
       padding: 0px;
     }
     /* Flexible box model classes */
-    /* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
+    /* Taken from Alex Russell https://infrequently.org/2009/08/css-3-progress/ */
     /* This file is a compatability layer.  It allows the usage of flexible box
     model layouts accross multiple browsers, including older browsers.  The newest,
     universal implementation of the flexible box model is used when available (see
@@ Expand Down @@

src/python/docs/sphinx/ci_script/conf.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -128,8 +128,8 @@
  
        'relative': True,

        'reference_url': {

            'nimbusml': None,

            'matplotlib': 'http://matplotlib.org',

            'numpy': 'http://www.numpy.org/',

            'matplotlib': 'https://matplotlib.org',

            'numpy': 'https://www.numpy.org/',

            'scipy': 'https://www.scipy.org/'},

    }

src/python/docs/sphinx/conf.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -145,8 +145,8 @@ def install_and_import(package):
  
        'relative': True,

        'reference_url': {

            'nimbusml': None,

            'matplotlib': 'http://matplotlib.org',

            'numpy': 'http://www.numpy.org/',

            'matplotlib': 'https://matplotlib.org',

            'numpy': 'https://www.numpy.org/',

            'scipy': 'https://www.scipy.org/'},

    }

src/python/nimbusml.pyproj

-Original file line number
+Diff line change
@@ Expand Up / @@ -792,11 +792,13 @@ @@
         <Compile Include="tests_extended\test_docs_notebooks.py" />
         <Compile Include="tests\test_pyproj.py" />
         <Compile Include="tests_extended\test_docs_example.py" />
+        <Compile Include="tools\changeHttpURLsToHttps.py" />
         <Compile Include="tools\codegen_checker.py" />
         <Compile Include="tools\code_fixer.py" />
         <Compile Include="tools\compiler_utils.py" />
         <Compile Include="tools\doc_builder.py" />
         <Compile Include="tools\entrypoint_compiler.py" />
+        <Compile Include="tools\findHttpURLs.py" />
         <Compile Include="tools\fix_line_widths.py" />
         <Compile Include="tools\loss_processor.py" />
         <Compile Include="tools\manifest_diff_parser.py" />
@@ Expand Down @@

src/python/nimbusml/decomposition/factorizationmachinebinaryclassifier.py

-Original file line number
+Diff line change
@@ Expand Up / @@ -44,7 +44,7 @@ class FactorizationMachineBinaryClassifier( @@
                 `Field Aware Factorization Machines
                 <https://www.csie.ntu.edu.tw/~r01922136/slides/ffm.pdf>`_,
                 `Field-aware Factorization Machines for CTR Prediction
-                <http://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf>`_,
+                <https://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf>`_,
                 `Adaptive Subgradient Methods for Online Learning and Stochastic
                 Optimization
                 <http://jmlr.org/papers/volume12/duchi11a/duchi11a.pdf>`_
@@ Expand Down @@

src/python/nimbusml/decomposition/pcaanomalydetector.py

-Original file line number
+Diff line change
@@ Expand Up @@
                 `Randomized Methods for Computing the Singular Value Decomposition
                 (SVD) of very large matrices
-                <http://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf>`_
+                <https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf>`_
                 `A randomized algorithm for principal component analysis
                 <https://arxiv.org/abs/0809.2274>`_,
                 `Finding Structure with Randomness: Probabilistic Algorithms for
                 Constructing Approximate Matrix Decompositions
-                <http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-
-                SIREV.pdf>`_
+                <http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf>`_
         :param feature: see `Columns </nimbusml/concepts/columns>`_.
@@ Expand Down @@

src/python/nimbusml/ensemble/fastforestbinaryclassifier.py

-Original file line number
+Diff line change
@@ Expand Up / @@ -55,7 +55,7 @@ class FastForestBinaryClassifier( @@
             **Reference**
                 `Wikipedia: Random forest
-                <http://en.wikipedia.org/wiki/Random_forest>`_
+                <https://en.wikipedia.org/wiki/Random_forest>`_
                 `Quantile regression forest
                 <http://jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf>`_
@@ Expand Down @@

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Added HTTP URLs to HTTPS URLs finder & converter Python scripts, and processed HTTP-->HTTPS URL changes #346

Uh oh!

Diff view

Diff view

There are no files selected for viewing

Uh oh!