Merge pull request #173 from AI-SDC/pre-commit-ci-update-config

[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -84,7 +84,7 @@ repos:
 
   # Check types with mypy
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.5.1
+    rev: v1.6.0
     hooks:
       - id: mypy
         args: ["--ignore-missing-imports", "--follow-imports", "skip", "--check-untyped-defs"]

notebooks/acro_demo.py

@@ -9,7 +9,7 @@
 import pandas as pd
 from scipy.io.arff import loadarff
 
-from acro import ACRO, add_constant, add_to_acro
+from acro import ACRO
 
 # Instantiate ACRO by making an acro object
 print(
@@ -21,10 +21,12 @@
 
 # Load test data
 # The dataset used in this notebook is the nursery dataset from OpenML.
-# - In this version, the data can be read directly from the local machine after it has been downloaded.
-# - The code below reads the data from a folder called "data" which we assume is at the same level as the folder where you are working.
+# - In this version, the data can be read directly from the local machine after
+#   it has been downloaded.
+# - The code below reads the data from a folder called "data" which we assume
+#   is at the same level as the folder where you are working.
 # - The path might need to be changed if the data has been downloaded and stored elsewhere.
-#  - for example use:
+#   - for example use:
 #     path = os.path.join("data", "nursery.arff")
 #     if the data is in a sub-folder of your work folder
 
@@ -39,7 +41,8 @@
 # Examples of producing tabular output
 # We rely on the industry-standard package **pandas** for tabulating data.
 # In the next few examples we show:
-# - first, how a researcher would normally make a call in pandas, saving the results in a variable that they can view on screen (or save to file?)
+# - first, how a researcher would normally make a call in pandas, saving the
+#   results in a variable that they can view on screen (or save to file?)
 # - then how the call is identical in SACRO, except that:
 #   - "pd" is replaced by "acro"
 #   - the researcher immediately sees a copy of what the TRE output checker will see.
@@ -69,9 +72,12 @@
 print(safe_table)
 
 # ACRO crosstab with suppression
-# - This is an example of crosstab with suppressing the cells that violate the disclosure tests.
-# - Note that you need to change the value of the suppress variable in the acro object to True. Then run the crosstab command.
-# - If you wish to continue the research while suppressing the outputs, leave the suppress variable as it is, otherwise turn it off.
+# - This is an example of crosstab with suppressing the cells that violate the
+#   disclosure tests.
+# - Note that you need to change the value of the suppress variable in the acro
+#   object to True. Then run the crosstab command.
+# - If you wish to continue the research while suppressing the outputs, leave
+#   the suppress variable as it is, otherwise turn it off.
 
 print("\nTurn on the suppression variable")
 acro.suppress = True
@@ -85,7 +91,8 @@
 # ACRO functionality to let users manage their outputs
 #
 # 1: List current ACRO outputs
-# This is an example of using the print_output function to list all the outputs created so far
+# This is an example of using the print_output function to list all the outputs
+# created so far
 
 print("\nNow illustrating how users can manage their outputs")
 print(
@@ -96,7 +103,8 @@
 
 # 2: Remove some ACRO outputs before finalising
 # This is an example of deleting some of the ACRO outputs.
-# The name of the output that needs to be removed should be passed to the function remove_output.
+# The name of the output that needs to be removed should be passed to the
+# function remove_output.
 # - The output name can be taken from the outputs listed by the print_outputs function,
 # - or by listing the results and choosing the specific output that needs to be removed
 
@@ -111,13 +119,15 @@
 
 # 4: Add a comment to output
 # This is an example to add a comment to outputs.
-# It can be used to provide a description or to pass additional information to the output checkers.
+# It can be used to provide a description or to pass additional information to
+# the output checkers.
 
 print("\nUsers can add comments which the output checkers will see.")
 acro.add_comments("cross_tabulation", "Please let me have this data.")
 
 # 5: (the big one) Finalise ACRO
-# This is an example of the function _finalise()_ which the users must call at the end of each session.
+# This is an example of the function _finalise()_ which the users must call at
+# the end of each session.
 # - It takes each output and saves it to a CSV file.
 # - It also saves the SDC analysis for each output to a json file or Excel file
 #   (depending on the extension of the name of the file provided as an input to the function)