ENH: Enable Execution, GitHub Actions, update config.yml (#4)

mmcky · web-flow · commit 48204872c183 · 2021-05-07T13:04:21.000+10:00
* amss lecture literalinclude -> code-cell * opt_tax_recur lecture literalinclude -> code-cell * amss2 lecture literalinclude -> code-cell * amss3 lecture literalinclude -> code-cell * chang_credible lecture literalinclude -> code-cell * chang_ramsey lecture literalinclude -> code-cell * classical_filtering lecture literalinclude -> code-cell * lu_tricks lecture literalinclude -> code-cell * rob_markov_perf lecture literalinclude -> code-cell * install myst_nb from branch for testing * install mysb_nb from branch for testing * switch on execution * myst_nb now supports code-cell from file * add in upgrade for tornado while fixing environment * specify priority for notebook outputs * [TEST] see if ipython display shows the image for html * change :file: to :load: * migrate file: to load: for multi-argument output * add execution status page * [medium term] this shows what the output should look like and leaves mybinder for the interactive plot at the end * add note about ipywidgets and html * fix timeout from 60s to 600s (10min) per lecture * enable run times per lecture of up to 20 minutes * harmonise _config.yml with lecture-python.myst * install quantecon-book-theme from main on github * removing output so that failed javascript objects don't get added * remove output from other uses of @interact * add notes about interactive plots on website * move to using quantecon-book-theme from pip * [TEST] demote javascript and jupyter widgets for html builder * Revert "[TEST] demote javascript and jupyter widgets for html builder" This reverts commit a881d8f. * [TEST] build using quantecon-book-theme@refactor as test for upcoming quantecon-book-theme=0.2.0 * Revert "Merge branch 'fix-ipywidgets' into fix-codefromfile" This reverts commit 37a63a3, reversing changes made to caf175a. * Revert "Merge branch 'fix-ipywidgets' into fix-codefromfile" This reverts commit caf175a, reversing changes made to 4a4f625. * [TEST] install from master to test upcoming 0.2.0 * remove tornado update in favour of updated environmnent.yml * check output_scroll tag * Revert "check output_scroll tag" This reverts commit bb51afd. * remove testing for interact and open in different PR
diff --git a/environment.yml b/environment.yml
@@ -8,7 +8,7 @@ dependencies:
   - pip:
     - jupyter-book
     - sphinx-multitoc-numbering
-    - quantecon-book-theme
+    - git+https://github.com/QuantEcon/quantecon-book-theme
     - sphinx-tojupyter
     - sphinxext-rediraffe
     - sphinx-exercise
diff --git a/lectures/_config.yml b/lectures/_config.yml
@@ -1,23 +1,74 @@
 title: Advanced Quantitative Economics with Python
 author: Thomas J. Sargent & John Stachurski
 logo: _static/qe-logo-large.png
+description: This website presents a set of lectures on advanced quantitative economic modeling, designed and written by Thomas J. Sargent and John Stachurski.
 
 execute:
-  execute_notebooks: "off"
-  timeout: 60
-#   run_in_temp: true
+  execute_notebooks: "cache"
+  timeout: 1200
 
 bibtex_bibfiles:
    - _static/quant-econ.bib
 
+html:
+  baseurl: https://python-advanced.quantecon.org/
+
 sphinx:
-  extra_extensions: [sphinx_multitoc_numbering]
+  extra_extensions: [sphinx_multitoc_numbering, sphinxext.rediraffe, sphinx_tojupyter]
   config:
+    nb_render_priority:
+      html:
+      - "application/vnd.jupyter.widget-view+json"
+      - "application/javascript"
+      - "text/html"
+      - "text/latex"
+      - "image/svg+xml"
+      - "image/png"
+      - "image/jpeg"
+      - "text/markdown"
+      - "text/plain"
+      jupyter:
+      - "application/vnd.jupyter.widget-view+json"
+      - "application/javascript"
+      - "text/html"
+      - "text/latex"
+      - "image/svg+xml"
+      - "image/png"
+      - "image/jpeg"
+      - "text/markdown"
+      - "text/plain"
+    html_favicon: _static/lectures-favicon.ico
     html_theme: quantecon_book_theme
     html_static_path: ['_static']
+    html_theme_options:
+      header_organisation_url: https://quantecon.org
+      header_organisation: QuantEcon
+      repository_url: https://github.com/QuantEcon/lecture-python-advanced.myst
+      nb_repository_url: https://github.com/QuantEcon/lecture-python-advanced.notebooks
+      twitter: quantecon
+      twitter_logo_url: https://assets.quantecon.org/img/qe-twitter-logo.png
+      og_logo_url: https://assets.quantecon.org/img/qe-og-logo.png
+      description: This website presents a set of lectures on advanced quantitative economic modeling, designed and written by Thomas J. Sargent and John Stachurski.
+      keywords: Python, QuantEcon, Quantitative Economics, Economics, Sloan, Alfred P. Sloan Foundation, Tom J. Sargent, John Stachurski
+      google_analytics_id: UA-54984338-11
     mathjax_config:
       TeX:
         Macros:
           "argmax" : "arg\\,max"
           "argmin" : "arg\\,min"
     mathjax_path: https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
+    rediraffe_redirects:
+      index_toc.md: intro.md
+    tojupyter_static_file_path: ["source/_static", "_static"]
+    tojupyter_target_html: true
+    tojupyter_urlpath: "https://python-advanced.quantecon.org/"
+    tojupyter_image_urlpath: "https://python-advanced.quantecon.org/_static/"
+    tojupyter_lang_synonyms: ["ipython", "ipython3", "python"]
+    tojupyter_kernels:
+      python3:
+        kernelspec:
+          display_name: "Python"
+          language: python3
+          name: python3
+        file_extension: ".py"
+    tojupyter_images_markdown: true
diff --git a/lectures/amss.md b/lectures/amss.md
@@ -400,8 +400,9 @@ in a Lucas-Stokey economy with state-contingent government debt.
 We need some code from  {doc}`an earlier lecture <opt_tax_recur>`
 on optimal taxation with state-contingent debt  sequential allocation implementation:
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/sequential_allocation.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/opt_tax_recur/sequential_allocation.py
 tags: [output_scroll]
 ---
 ```
@@ -672,7 +673,8 @@ assets, returning any excess revenues to the household as non-negative lump-sum
 
 The recursive formulation is implemented as follows
 
-```{literalinclude} _static/lecture_specific/amss/recursive_allocation.py
+```{code-cell} python3
+:load: _static/lecture_specific/amss/recursive_allocation.py
 ```
 
 ## Examples
@@ -681,7 +683,8 @@ We now turn to some examples.
 
 We will first build some useful functions for solving the model
 
-```{literalinclude} _static/lecture_specific/amss/utilities.py
+```{code-cell} python3
+:load: _static/lecture_specific/amss/utilities.py
 ```
 
 ### Anticipated One-Period War
@@ -742,7 +745,8 @@ We assume the same utility parameters as in the {doc}`Lucas-Stokey economy <opt_
 
 This utility function is implemented in the following class.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/crra_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/crra_utility.py
 ```
 
 The following figure plots  Ramsey plans under complete and incomplete
@@ -866,7 +870,8 @@ $$
 
 In accordance, we will re-define our utility function.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/log_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/log_utility.py
 ```
 
 With these preferences, Ramsey tax rates will vary even in the Lucas-Stokey
diff --git a/lectures/amss2.md b/lectures/amss2.md
@@ -245,7 +245,8 @@ In equation {eq}`amss2_TS_barg10`, it is understood that $c$ and $g$ are each fu
 
 The CRRA utility function is represented in the following class.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/crra_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/crra_utility.py
 ```
 
 ## Example Economy
@@ -275,20 +276,23 @@ Here are several classes that do most of the work for us.
 The code is  mostly taken or adapted from the earlier lectures {doc}`optimal taxation without state-contingent debt <amss>` and
 {doc}`optimal taxation with state-contingent debt <opt_tax_recur>`.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/sequential_allocation.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/opt_tax_recur/sequential_allocation.py
 tags: [output_scroll]
 ---
 ```
 
-```{literalinclude} _static/lecture_specific/amss/recursive_allocation.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/amss/recursive_allocation.py
 tags: [output_scroll]
 ---
 ```
 
-```{literalinclude} _static/lecture_specific/amss/utilities.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/amss/utilities.py
 tags: [output_scroll]
 ---
 ```
diff --git a/lectures/amss3.md b/lectures/amss3.md
@@ -116,7 +116,8 @@ $$
 
 The following Python code sets up the economy
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/crra_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/crra_utility.py
 ```
 
 ### First and Second Moments
@@ -148,20 +149,23 @@ We begin by showing the code that we used in earlier lectures on the AMSS model.
 
 Here it is
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/sequential_allocation.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/opt_tax_recur/sequential_allocation.py
 tags: [output_scroll]
 ---
 ```
 
-```{literalinclude} _static/lecture_specific/amss/recursive_allocation.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/amss/recursive_allocation.py
 tags: [output_scroll]
 ---
 ```
 
-```{literalinclude} _static/lecture_specific/amss/utilities.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/amss/utilities.py
 tags: [output_scroll]
 ---
 ```
diff --git a/lectures/chang_credible.md b/lectures/chang_credible.md
@@ -809,8 +809,9 @@ code for now. We can increase accuracy by increasing the number of subgradients)
 
 The following code computes sustainable plans
 
-```{literalinclude} _static/lecture_specific/chang_credible/changecon.py
+```{code-cell} python3
 ---
+load: _static/lecture_specific/chang_credible/changecon.py
 tags: [output_scroll]
 ---
 ```
diff --git a/lectures/chang_ramsey.md b/lectures/chang_ramsey.md
@@ -882,7 +882,8 @@ $\beta = 0.8$.
 (Here we have set the number of subgradients to 10 in order to speed up the
 code for now - we can increase accuracy by increasing the number of subgradients)
 
-```{literalinclude} _static/lecture_specific/chang_credible/changecon.py
+```{code-cell} python3
+:load: _static/lecture_specific/chang_credible/changecon.py
 ```
 
 ```{code-cell} python3
diff --git a/lectures/classical_filtering.md b/lectures/classical_filtering.md
@@ -225,7 +225,8 @@ $$
 
 Here's the code that computes solutions to LQ control and filtering problems using the methods described here and in {doc}`Classical Control with Linear Algebra <lu_tricks>`.
 
-```{literalinclude} _static/lecture_specific/lu_tricks/control_and_filter.py
+```{code-cell} python3
+:load: _static/lecture_specific/lu_tricks/control_and_filter.py
 ```
 
 Let's use this code to tackle two interesting examples.
diff --git a/lectures/lu_tricks.md b/lectures/lu_tricks.md
@@ -892,7 +892,8 @@ solving a related undiscounted problem.
 Here's the code that computes solutions to the LQ problem using the methods described
 above.
 
-```{literalinclude} _static/lecture_specific/lu_tricks/control_and_filter.py
+```{code-cell} python3
+:load: _static/lecture_specific/lu_tricks/control_and_filter.py
 ```
 
 ### Example
diff --git a/lectures/opt_tax_recur.md b/lectures/opt_tax_recur.md
@@ -719,7 +719,8 @@ $$
 
 The above steps are implemented in a class called SequentialAllocation
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/sequential_allocation.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/sequential_allocation.py
 ```
 
 ## Recursive Formulation of the Ramsey Problem
@@ -1020,7 +1021,8 @@ through them, the value of initial government debt $b_0$.
 
 The above steps are implemented in a class called `RecursiveAllocation`.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/recursive_allocation.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/recursive_allocation.py
 ```
 
 ## Examples
@@ -1073,7 +1075,8 @@ utility as a function of $n$ rather than leisure $l$.
 
 This utility function is implemented in the class `CRRAutility`.
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/crra_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/crra_utility.py
 ```
 
 We set initial government debt $b_0 = 1$.
@@ -1351,7 +1354,8 @@ $$
 
 We will create a new class LogUtility to represent this utility function
 
-```{literalinclude} _static/lecture_specific/opt_tax_recur/log_utility.py
+```{code-cell} python3
+:load: _static/lecture_specific/opt_tax_recur/log_utility.py
 ```
 
 Also, suppose that $g_t$ follows a two-state IID process with equal
diff --git a/lectures/rob_markov_perf.md b/lectures/rob_markov_perf.md
@@ -454,7 +454,8 @@ Consider the  duopoly model with parameter values of:
 
 From these, we computed the infinite horizon MPE without robustness using the code
 
-```{literalinclude} _static/lecture_specific/markov_perf/duopoly_mpe.py
+```{code-cell} python3
+:load: _static/lecture_specific/markov_perf/duopoly_mpe.py
 ```
 
 #### Markov Perfect Equilibrium with Robustness
diff --git a/lectures/status.md b/lectures/status.md
@@ -9,17 +9,12 @@ kernelspec:
   name: python3
 ---
 
-(status)=
-# Lecture Status
+# Execution Statistics
 
-```{raw} html
-<style type="text/css">.lecture-options{display:none;}</style>
-<p>The badges below show which lectures are currently passing their execution test (i.e., executing without errors).</p>
-<p>The lecture code checker was last run: <strong id="last_test_time">N/A</strong></p>
-<div class="status-table-container">
-    <table id="status_table" class="status-table"></table>
-</div>
-<p>The code checker is run on a <code class="docutils literal notranslate"><span class="pre">t2.small</span></code> Amazon EC2 instance. This is an instance with a single CPU and 2 GiB of Memory.</p>
-<p>You should achieve faster run times on many common laptops and desktops.</p>
+This table contains the latest execution statistics.
+
+```{nb-exec-table}
 ```
 
+These lectures are built on `linux` instances through `github actions` so are
+executed using the following [hardware specifications](https://docs.github.com/en/actions/reference/specifications-for-github-hosted-runners#supported-runners-and-hardware-resources)
