hitting 512 MB memory quota on heroku after just 2 API calls

# Bug Description
The [Heroku Standard 1x Dyno](https://www.heroku.com/pricing) has a [512 MB memory quota](https://devcenter.heroku.com/articles/dyno-types) and we have hit the limit after just
1. deployment
2. 2 API calls to the `/ask` endpoint

# Screenshots
screenshots


# Proposed solutions
## 1. switch to GCP and choose an appropriately sized virtual machine

* GCP may be more affordable for the club with student credits.
* we need a new [`.github/workflows/*.yml`](https://github.com/calpoly-csai/api/tree/dev/.github/workflows) to handle GCP deployment
* [Google offers example GitHub workflows for GCP](https://github.com/marketplace/actions/setup-gcloud-environment)

## 2. scale the heroku dyno to [standard-2x or something else](https://devcenter.heroku.com/articles/dyno-types)

This would get expensive, quickly...

## 3. identify memory usage & performance improvements for our code
### maybe avoid the use of `pandas` in `QA` and use `import csv` instead

##### only `read_csv` is imported
https://github.com/calpoly-csai/api/blob/48336b06f95e3676c5322d6760c34968b2d145d5/QA.py#L10

##### reference @zpdeng 's usage of `csv` module
https://github.com/calpoly-csai/api/blob/48336b06f95e3676c5322d6760c34968b2d145d5/database_wrapper.py#L426-L433

##### it may be a good idea to [actually test if `pandas` is truly hogging memory](https://stackoverflow.com/questions/552744/how-do-i-profile-memory-usage-in-python)

### maybe `spacy`?

### maybe `nltk`?

### maybe `SQLAlchemy`?

### maybe `Flask`?

### maybe `gcloud`?

### maybe `another_package_expected_to_be_large`?

### consider this output of [`python3 -m memory_profiler flask_api.py`](https://pypi.org/project/memory-profiler/)

memory profile

```
{'entity': 'Dr. Khosmood', 'tag': 'PROF', 'normalized entity': 'Khosmood', 'input question': "What is Dr. Khosmood's phone number?", 'normalized question': "What is [PROF]'s phone number?", 'question class': "What is [PROF]'s phone number?"}
Filename: /Users/mfekadu/GitHub/api/QA.py

Line # Mem usage Increment Line Contents
================================================
61 218.5 MiB 218.5 MiB @profile
62 def answer(self, extracted_vars):
63 218.5 MiB 0.0 MiB db_data = self._get_data_from_db(extracted_vars)
64 218.5 MiB 0.0 MiB return self._format_answer(extracted_vars, db_data)

Filename: /Users/mfekadu/GitHub/api/nimbus.py

Line # Mem usage Increment Line Contents
================================================
22 215.0 MiB 215.0 MiB @profile
23 def answer_question(self, question):
24 218.5 MiB 3.5 MiB ans_dict = NIMBUS_NLP.predict_question(question)
25 218.5 MiB 0.0 MiB print(ans_dict)
26 218.5 MiB 0.0 MiB try:
27 218.5 MiB 0.0 MiB qa = self.qa_dict[ans_dict["question class"]]
28 except KeyError:
29 return "I'm sorry, I don't understand. Please try another question."
30 else:
31 218.5 MiB 0.0 MiB answer = qa.answer(ans_dict)
32 218.5 MiB 0.0 MiB if answer is None:
33 return("I'm sorry, I understand your question but was unable to find an answer. "
34 "Please try another question.")
35 else:
36 218.5 MiB 0.0 MiB return answer

127.0.0.1 - - [02/Mar/2020 01:28:41] "POST /ask HTTP/1.1" 200 -
```

git diff

```diff
diff --git a/Pipfile b/Pipfile
index 6069200..0f8e7ef 100644
--- a/Pipfile
+++ b/Pipfile
@@ -22,7 +22,7 @@ pytest = "==5.3.4"
pyre-check = "==0.0.41"
## like the Unix `make` but better
invoke = "==1.4.1"
-
+memory-profiler = "*"

[packages]
# REST API
diff --git a/Pipfile.lock b/Pipfile.lock
index 6575e89..e55e8ff 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
{
"_meta": {
"hash": {
- "sha256": "fb30d39142d3cc83d8909d9f4f4648a60ac33d4ec3a5a94d8dac7b90ef727a24"
+ "sha256": "c1f663e58339a2e67ba7d26a44722711969699a9998316437dcaef26cbbe8b80"
},
"pipfile-spec": 6,
"requires": {
@@ -826,6 +826,13 @@
],
"version": "==0.6.1"
},
+ "memory-profiler": {
+ "hashes": [
+ "sha256:23b196f91ea9ac9996e30bfab1e82fecc30a4a1d24870e81d1e81625f786a2c3"
+ ],
+ "index": "pypi",
+ "version": "==0.57.0"
+ },
"more-itertools": {
"hashes": [
"sha256:5dd8bcf33e5f9513ffa06d5ad33d78f31e1931ac9a18f33d37e77a180d393a7c",
diff --git a/QA.py b/QA.py
index 250b065..06ecf0b 100644
--- a/QA.py
+++ b/QA.py
@@ -9,6 +9,8 @@ from Entity.Sections import Sections
from database_wrapper import NimbusMySQLAlchemy
from pandas import read_csv

+from memory_profiler import profile
+
Extracted_Vars = Dict[str, Any]
DB_Data = Dict[str, Any]
DB_Query = Callable[[Extracted_Vars], DB_Data]
@@ -33,6 +35,7 @@ class QA:
A class for wrapping functions used to answer a question.
"""

+ @profile
def __init__(self, q_format, db_query, format_answer):
"""
Args:
@@ -55,6 +58,7 @@ class QA:
def _format_answer(self, extracted_vars, db_data):
return self.format_answer(extracted_vars, db_data)

+ @profile
def answer(self, extracted_vars):
db_data = self._get_data_from_db(extracted_vars)
return self._format_answer(extracted_vars, db_data)
@@ -66,6 +70,7 @@ class QA:
return hash(self.q_format)

+@profile
def create_qa_mapping(qa_list):
"""
Creates a dictionary whose values are QA objects and keys are the question
@@ -186,6 +191,7 @@ def yes_no(a_format, pred=None):
return functools.partial(_yes_no, a_format, pred)

+@profile
def generate_fact_QA(csv):
df = read_csv(csv)
text_in_brackets = r'\[[^\[\]]*\]'
diff --git a/flask_api.py b/flask_api.py
index d6478c5..34fe17b 100755
--- a/flask_api.py
+++ b/flask_api.py
@@ -18,6 +18,8 @@ from modules.validators import WakeWordValidator, WakeWordValidatorError

from nimbus import Nimbus

+from memory_profiler import profile
+
BAD_REQUEST = 400
SUCCESS = 200

@@ -44,6 +46,7 @@ def generate_session_token() -> str:
return "SOME_NEW_TOKEN"

+@profile
@app.route('/ask', methods=['POST'])
def handle_question():
"""
diff --git a/nimbus.py b/nimbus.py
index 7d6bdfc..729cf62 100644
--- a/nimbus.py
+++ b/nimbus.py
@@ -9,14 +9,17 @@ from werkzeug.exceptions import BadRequestKeyError
from QA import create_qa_mapping, generate_fact_QA
from nimbus_nlp.NIMBUS_NLP import NIMBUS_NLP

+from memory_profiler import profile

class Nimbus:

+ @profile
def __init__(self):
self.qa_dict = create_qa_mapping(
generate_fact_QA("q_a_pairs.csv")
)

+ @profile
def answer_question(self, question):
ans_dict = NIMBUS_NLP.predict_question(question)
print(ans_dict)
(END)
```