Update GitHub links to https

piskvorky · Mar 13, 2023 · 27f27b1 · 27f27b1
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diff --git a/README.md b/README.md
@@ -173,6 +173,6 @@ BibTeX entry:
   [unsupervised document analysis]: https://en.wikipedia.org/wiki/Latent_semantic_indexing
   [NumPy and Scipy]: https://scipy.org/install/
   [ATLAS]: https://math-atlas.sourceforge.net/
-  [OpenBLAS]: http://xianyi.github.io/OpenBLAS/
+  [OpenBLAS]: https://xianyi.github.io/OpenBLAS/
   [source tar.gz]: https://pypi.org/project/gensim/
   [documentation]: https://radimrehurek.com/gensim/#install
diff --git a/gensim/nosy.py b/gensim/nosy.py
@@ -11,7 +11,7 @@
 https://pypi.org/project/rudolf/
 
 Originally by Jeff Winkler, http://jeffwinkler.net
-Forked from wkral http://github.com/wkral/Nosy
+Forked from wkral https://github.com/wkral/Nosy
 """
 
 import os

diff --git a/gensim/utils.py b/gensim/utils.py
@@ -1160,7 +1160,7 @@ def safe_unichr(intval):
 def decode_htmlentities(text):
     """Decode all HTML entities in text that are encoded as hex, decimal or named entities.
     Adapted from `python-twitter-ircbot/html_decode.py
-    <http://github.com/sku/python-twitter-ircbot/blob/321d94e0e40d0acc92f5bf57d126b57369da70de/html_decode.py>`_.
+    <https://github.com/sku/python-twitter-ircbot/blob/321d94e0e40d0acc92f5bf57d126b57369da70de/html_decode.py>`_.
 
     Parameters
     ----------

diff --git a/setup.py b/setup.py
@@ -202,7 +202,7 @@ def run(self):
 This software depends on `NumPy and Scipy <https://scipy.org/install/>`_, two Python packages for scientific computing.
 You must have them installed prior to installing `gensim`.
 
-It is also recommended you install a fast BLAS library before installing NumPy. This is optional, but using an optimized BLAS such as MKL, `ATLAS <https://math-atlas.sourceforge.net/>`_ or `OpenBLAS <http://xianyi.github.io/OpenBLAS/>`_ is known to improve performance by as much as an order of magnitude. On OSX, NumPy picks up its vecLib BLAS automatically, so you don't need to do anything special.
+It is also recommended you install a fast BLAS library before installing NumPy. This is optional, but using an optimized BLAS such as MKL, `ATLAS <https://math-atlas.sourceforge.net/>`_ or `OpenBLAS <https://xianyi.github.io/OpenBLAS/>`_ is known to improve performance by as much as an order of magnitude. On OSX, NumPy picks up its vecLib BLAS automatically, so you don't need to do anything special.
 
 Install the latest version of gensim::