Change to https. (#7277)

* Change to https.

* Revert the py_tf file.

fractals/julia_sets.py

@@ -12,7 +12,7 @@ The examples presented here are:
 https://en.wikipedia.org/wiki/File:Julia_z2%2B0,25.png
 - Other examples from https://en.wikipedia.org/wiki/Julia_set
 - An exponential map Julia set, ambiantly homeomorphic to the examples in
-http://www.math.univ-toulouse.fr/~cheritat/GalII/galery.html
+https://www.math.univ-toulouse.fr/~cheritat/GalII/galery.html
  and
 https://ddd.uab.cat/pub/pubmat/02141493v43n1/02141493v43n1p27.pdf
 

fractals/sierpinski_triangle.py

@@ -24,7 +24,7 @@ Usage:
   - $python sierpinski_triangle.py <int:depth_for_fractal>
 
 Credits: This code was written by editing the code from
-http://www.riannetrujillo.com/blog/python-fractal/
+https://www.riannetrujillo.com/blog/python-fractal/
 
 """
 import sys

machine_learning/lstm/lstm_prediction.py

@@ -1,7 +1,7 @@
 """
     Create a Long Short Term Memory (LSTM) network model
     An LSTM is a type of Recurrent Neural Network (RNN) as discussed at:
-    * http://colah.github.io/posts/2015-08-Understanding-LSTMs
+    * https://colah.github.io/posts/2015-08-Understanding-LSTMs
     * https://en.wikipedia.org/wiki/Long_short-term_memory
 """
 import numpy as np

machine_learning/sequential_minimum_optimization.py

@@ -28,7 +28,7 @@ Usage:
 Reference:
     https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/smo-book.pdf
     https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-98-14.pdf
-    http://web.cs.iastate.edu/~honavar/smo-svm.pdf
+    https://web.cs.iastate.edu/~honavar/smo-svm.pdf
 """
 
 
@@ -43,7 +43,7 @@ from sklearn.datasets import make_blobs, make_circles
 from sklearn.preprocessing import StandardScaler
 
 CANCER_DATASET_URL = (
-    "http://archive.ics.uci.edu/ml/machine-learning-databases/"
+    "https://archive.ics.uci.edu/ml/machine-learning-databases/"
     "breast-cancer-wisconsin/wdbc.data"
 )
 

maths/matrix_exponentiation.py

@@ -5,7 +5,7 @@ import timeit
 """
 Matrix Exponentiation is a technique to solve linear recurrences in logarithmic time.
 You read more about it here:
-http://zobayer.blogspot.com/2010/11/matrix-exponentiation.html
+https://zobayer.blogspot.com/2010/11/matrix-exponentiation.html
 https://www.hackerearth.com/practice/notes/matrix-exponentiation-1/
 """
 

maths/test_prime_check.py

@@ -1,6 +1,6 @@
 """
 Minimalist file that allows pytest to find and run the Test unittest.  For details, see:
-http://doc.pytest.org/en/latest/goodpractices.html#conventions-for-python-test-discovery
+https://doc.pytest.org/en/latest/goodpractices.html#conventions-for-python-test-discovery
 """
 
 from .prime_check import Test

physics/n_body_simulation.py

@@ -8,7 +8,7 @@ velocity and position brought about by these forces. Softening is used to preven
 numerical divergences when a particle comes too close to another (and the force
 goes to infinity).
 (Description adapted from https://en.wikipedia.org/wiki/N-body_simulation )
-(See also http://www.shodor.org/refdesk/Resources/Algorithms/EulersMethod/ )
+(See also https://www.shodor.org/refdesk/Resources/Algorithms/EulersMethod/ )
 """
 
 
@@ -258,7 +258,7 @@ def example_1() -> BodySystem:
     Example 1: figure-8 solution to the 3-body-problem
     This example can be seen as a test of the implementation: given the right
     initial conditions, the bodies should move in a figure-8.
-    (initial conditions taken from http://www.artcompsci.org/vol_1/v1_web/node56.html)
+    (initial conditions taken from https://www.artcompsci.org/vol_1/v1_web/node56.html)
     >>> body_system = example_1()
     >>> len(body_system)
     3

strings/frequency_finder.py

@@ -2,7 +2,7 @@
 
 import string
 
-# frequency taken from http://en.wikipedia.org/wiki/Letter_frequency
+# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
 english_letter_freq = {
     "E": 12.70,
     "T": 9.06,

web_programming/crawl_google_results.py

@@ -21,4 +21,4 @@ if __name__ == "__main__":
         if link.text == "Maps":
             webbrowser.open(link.get("href"))
         else:
-            webbrowser.open(f"http://google.com{link.get('href')}")
+            webbrowser.open(f"https://google.com{link.get('href')}")

web_programming/crawl_google_scholar_citation.py

@@ -29,4 +29,4 @@ if __name__ == "__main__":
         "year": 2018,
         "hl": "en",
     }
-    print(get_citation("http://scholar.google.com/scholar_lookup", params=params))
+    print(get_citation("https://scholar.google.com/scholar_lookup", params=params))

web_programming/current_weather.py

@@ -1,7 +1,7 @@
 import requests
 
 APPID = ""  # <-- Put your OpenWeatherMap appid here!
-URL_BASE = "http://api.openweathermap.org/data/2.5/"
+URL_BASE = "https://api.openweathermap.org/data/2.5/"
 
 
 def current_weather(q: str = "Chicago", appid: str = APPID) -> dict:

web_programming/giphy.py

@@ -10,7 +10,7 @@ def get_gifs(query: str, api_key: str = giphy_api_key) -> list:
     Get a list of URLs of GIFs based on a given query..
     """
     formatted_query = "+".join(query.split())
-    url = f"http://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}"
+    url = f"https://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}"
     gifs = requests.get(url).json()["data"]
     return [gif["url"] for gif in gifs]