eccentricorange / npbc Goto Github PK

This app calculates your monthly newspaper bill, given the cost of each paper per weekday.

License: MIT License

Python 97.84% Dockerfile 2.16%

command-line-tool hacktoberfest python sqlite

npbc's Introduction

👋 Hi, I'm a college student that loves robotics, and is currently studying Electrical Engineering at the Bachelor's level. Almost all projects uploaded here are something I've needed in real life.

Check out my personal blog: https://eccentricorange.netlify.app/ [repo]

I work with: Python, C++ (Arduino, ESP32), LabVIEW (myRIO FPGA, Desktop), KiCAD (PCB designing), physical electronics
Currently exploring: STM32 and ESP32 embedded C dev, RTOS, ROS2, PCB Designing
Learning about: core electrical/electronics, control systems, power electronics, kinematics, localization
Want to learn: core CS (architectures, OS, DSA, scaling, virtualization), the wizard-like skills old electrical engineers have
Other random skills: Git, Docker, Linux, CI+CD, Raspberry Pi, soldering, PCB designing, technical documentation
Random interests: articulately-written science-fiction, music production, OS-level vulnerabilities, intersection of quantum mechanics and astrophysics, table tennis, cool algorithms

npbc's People

Contributors

Stargazers

Watchers

Forkers

sickofgooglesshit

npbc's Issues

Better testing

Add better testing for the entire program.

Test creation of database if it does not exist.
Test the CLI.

Builds run unnecessarily

npbc/.github/workflows/test-build-release.yml

Lines 21 to 115 in 518364d

 # build executable for linux 

 build-linux: 

 name: build for linux 

 runs-on: ubuntu-latest 

 needs: test 

 steps: 

 # setup 

 - uses: actions/checkout@v2 

 - uses: actions/setup-python@v2 

 - run: | 

  pip install pyinstaller 

  mkdir bin 

  mkdir build 

  # build 

 - run: | 

  pyinstaller --distpath bin --clean --onefile --name npbc_updater-linux-x64 npbc_updater.py 

  pip install -r requirements.txt 

  pyinstaller --distpath bin --clean --add-data "data/schema.sql:." --onefile --name npbc_cli-linux-x64 npbc_cli.py 

  # upload artifacts 

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_cli-linux-x64  

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_updater-linux-x64 

 # build executable for windows 

 build-windows: 

 name: build for windows 

 runs-on: windows-latest 

 needs: test 

 steps: 

 # setup 

 - uses: actions/checkout@v2 

 - uses: actions/setup-python@v2 

 - run: | 

  pip install pyinstaller 

  mkdir bin 

  mkdir build 

  # build 

 - run: | 

  pyinstaller --distpath bin --clean --onefile --name npbc_updater-windows-x64 npbc_updater.py 

  pip install -r requirements.txt 

  pyinstaller --distpath bin --clean --add-data "data/schema.sql;." --onefile --name npbc_cli-windows-x64 npbc_cli.py 

  # upload artifacts 

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_cli-windows-x64  

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_updater-windows-x64 

 # build executable for macos 

 build-macos: 

 name: build for macos 

 runs-on: macos-latest 

 needs: test 

 steps: 

 # setup 

 - uses: actions/checkout@v2 

 - uses: actions/setup-python@v2 

 - run: | 

  pip install pyinstaller 

  mkdir bin 

  mkdir build 

  # build 

 - run: | 

  pyinstaller --distpath bin --clean --onefile --name npbc_updater-macos-x64 npbc_updater.py 

  pip install -r requirements.txt 

  pyinstaller --distpath bin --clean --add-data "data/schema.sql:." --onefile --name npbc_cli-macos-x64 npbc_cli.py 

  # upload artifacts 

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_cli-macos-x64  

 - uses: actions/upload-artifact@v2 

 with: 

 path: bin 

 name: npbc_updater-macos-x64

Figure out a better alternative or method for the "installation"

Python applications are typically not distributed like EXEs (as an app written in C or something might be). They're typically distributed as source and an environment (or specifications thereof).

My hacky PyInstaller system is likely inefficient and not as portable.

Log row shown only if both fields present

The get_logged_data() function does not return some entries. It appears that it's showing only the entries for which an undelivered date and a cost both exist.

npbc/npbc_core.py

Lines 694 to 759 in 49dcf6e

 def get_logged_data( 

 paper_id: int | None = None, 

 log_id: int | None = None, 

 month: int | None = None, 

 year: int | None = None, 

 timestamp: date_type | None = None 

 ): 

 """get logged data 

  - the user may specify as parameters many as they want 

  - available parameters: paper_id, log_id, month, year, timestamp 

  - returns: a list of tuples containing the following fields: 

  log_id, paper_id, month, year, timestamp, date, cost.""" 

 global DATABASE_PATH 

 # initialize parameters for the WHERE clause of the SQL query 

 data = [] 

 parameters = [] 

 values = () 

 # check each parameter and add it to the WHERE clause if it is given 

 if paper_id: 

 parameters.append("paper_id") 

 values += (paper_id,) 

 if log_id: 

 parameters.append("log_id") 

 values += (log_id,) 

 if month: 

 parameters.append("month") 

 values += (month,) 

 if year: 

 parameters.append("year") 

 values += (year,) 

 if timestamp: 

 parameters.append("timestamp") 

 values += (timestamp.strftime(r'%d/%m/%Y %I:%M:%S %p'),) 

 # generate the SQL query 

 columns_only_query = """ 

  SELECT logs.log_id, logs.paper_id, logs.month, logs.year, logs.timestamp, undelivered_dates_logs.date_not_delivered, cost_logs.cost 

  FROM logs 

  INNER JOIN undelivered_dates_logs ON logs.log_id = undelivered_dates_logs.log_id 

  INNER JOIN cost_logs ON logs.log_id = cost_logs.log_id""" 

 if parameters: 

 conditions = ' AND '.join( 

 f"logs.{parameter} = ?" 

 for parameter in parameters 

 ) 

 final_query = f"{columns_only_query} WHERE {conditions};" 

 else: 

 final_query = f"{columns_only_query};" 

 # execute the query 

 with connect(DATABASE_PATH) as connection: 

 data = connection.execute(final_query, values).fetchall() 

 connection.close() 

 return data

Redundancy in DB table `paper_day_id`

Consider the following section of the schema:

npbc/data/schema.sql

Lines 7 to 24 in 9d6eafb

 CREATE TABLE IF NOT EXISTS papers_days ( 

 paper_day_id INTEGER PRIMARY KEY AUTOINCREMENT, 

 paper_id INTEGER NOT NULL REFERENCES papers(paper_id), 

 day_id INTEGER NOT NULL, 

 CONSTRAINT unique_paper_day UNIQUE (paper_id, day_id) 

 ); 

 CREATE TABLE IF NOT EXISTS papers_days_delivered ( 

 papers_days_delivered_id INTEGER PRIMARY KEY AUTOINCREMENT, 

 paper_day_id INTEGER NOT NULL REFERENCES papers_days(paper_day_id), 

 delivered INTEGER NOT NULL CHECK (delivered IN (0, 1)) 

 ); 

 CREATE TABLE IF NOT EXISTS papers_days_cost ( 

 papers_days_cost_id INTEGER PRIMARY KEY AUTOINCREMENT, 

 paper_day_id INTEGER NOT NULL REFERENCES papers_days(paper_day_id), 

 cost REAL 

 );

In practice

papers_days_delivered.papers_days_delivered is always equal to papers_days_delivered.paper_day_id
papers_days_cost.papers_days_cist_id is always equal to papers_days_cost.paper_day_id

In effect, this makes the primary key column redundant. More over, the data from the three tables mentioned here can be combined in to one effectively, without the kind of repetition prohibited by NF1.

Incorporate CRSE feedback 2

I had posted the code up to commit 041a949 to the Code Review Stack Exchange (abbreviated CRSE). Good feedback has been received, and will be acted up on.

Post 1 of 3, Core: https://codereview.stackexchange.com/q/276927/257004
Post 2 of 3, CLI: https://codereview.stackexchange.com/q/276928/257004
Post 3 of 3, Database: https://codereview.stackexchange.com/q/276929/257004

Each comment tackles one file/aspect of the upgrades. The pull request immedeatly following a comment will have a summary of the changes and decisions made, with respect to the issue comment.

Incorporate CRSE and Reddit feedback

I had posted the code up to commit 6020a4f to the Code Review Stack Exchange (abbreviated CRSE). Good feedback has been received, and will be acted up on.

Post 1 of 3, Core: https://codereview.stackexchange.com/q/276225/257004
Post 2 of 3, CLI: https://codereview.stackexchange.com/q/276227/257004
Post 3 of 3, Database: https://codereview.stackexchange.com/q/276229/257004

I had also posted up to commit 3250a1a to r/learnpython on Reddit, and got some good feedback there too.

Each comment tackles one file/aspect of the upgrades. The pull request immedeatly following a comment will have a summary of the changes and decisions made, with respect to the issue comment.

eccentricorange / npbc Goto Github PK

npbc's Introduction

npbc's People

Contributors

Stargazers

Watchers

Forkers

npbc's Issues

Better testing

Builds run unnecessarily

Figure out a better alternative or method for the "installation"

Log row shown only if both fields present

Redundancy in DB table `paper_day_id`

Incorporate CRSE feedback 2

Incorporate CRSE and Reddit feedback

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	# build executable for linux
	build-linux:
	name: build for linux
	runs-on: ubuntu-latest
	needs: test

	steps:

	# setup
	- uses: actions/checkout@v2
	- uses: actions/setup-python@v2
	- run: \|
	pip install pyinstaller
	mkdir bin
	mkdir build

	# build
	- run: \|
	pyinstaller --distpath bin --clean --onefile --name npbc_updater-linux-x64 npbc_updater.py
	pip install -r requirements.txt
	pyinstaller --distpath bin --clean --add-data "data/schema.sql:." --onefile --name npbc_cli-linux-x64 npbc_cli.py

	# upload artifacts
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_cli-linux-x64
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_updater-linux-x64

	# build executable for windows
	build-windows:
	name: build for windows
	runs-on: windows-latest
	needs: test

	steps:

	# setup
	- uses: actions/checkout@v2
	- uses: actions/setup-python@v2
	- run: \|
	pip install pyinstaller
	mkdir bin
	mkdir build

	# build
	- run: \|
	pyinstaller --distpath bin --clean --onefile --name npbc_updater-windows-x64 npbc_updater.py
	pip install -r requirements.txt
	pyinstaller --distpath bin --clean --add-data "data/schema.sql;." --onefile --name npbc_cli-windows-x64 npbc_cli.py

	# upload artifacts
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_cli-windows-x64
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_updater-windows-x64

	# build executable for macos
	build-macos:
	name: build for macos
	runs-on: macos-latest
	needs: test

	steps:

	# setup
	- uses: actions/checkout@v2
	- uses: actions/setup-python@v2
	- run: \|
	pip install pyinstaller
	mkdir bin
	mkdir build

	# build
	- run: \|
	pyinstaller --distpath bin --clean --onefile --name npbc_updater-macos-x64 npbc_updater.py
	pip install -r requirements.txt
	pyinstaller --distpath bin --clean --add-data "data/schema.sql:." --onefile --name npbc_cli-macos-x64 npbc_cli.py

	# upload artifacts
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_cli-macos-x64
	- uses: actions/upload-artifact@v2
	with:
	path: bin
	name: npbc_updater-macos-x64

	def get_logged_data(
	paper_id: int \| None = None,
	log_id: int \| None = None,
	month: int \| None = None,
	year: int \| None = None,
	timestamp: date_type \| None = None
	):
	"""get logged data
	- the user may specify as parameters many as they want
	- available parameters: paper_id, log_id, month, year, timestamp
	- returns: a list of tuples containing the following fields:
	log_id, paper_id, month, year, timestamp, date, cost."""

	global DATABASE_PATH

	# initialize parameters for the WHERE clause of the SQL query
	data = []
	parameters = []
	values = ()

	# check each parameter and add it to the WHERE clause if it is given
	if paper_id:
	parameters.append("paper_id")
	values += (paper_id,)

	if log_id:
	parameters.append("log_id")
	values += (log_id,)

	if month:
	parameters.append("month")
	values += (month,)

	if year:
	parameters.append("year")
	values += (year,)

	if timestamp:
	parameters.append("timestamp")
	values += (timestamp.strftime(r'%d/%m/%Y %I:%M:%S %p'),)

	# generate the SQL query
	columns_only_query = """
	SELECT logs.log_id, logs.paper_id, logs.month, logs.year, logs.timestamp, undelivered_dates_logs.date_not_delivered, cost_logs.cost
	FROM logs
	INNER JOIN undelivered_dates_logs ON logs.log_id = undelivered_dates_logs.log_id
	INNER JOIN cost_logs ON logs.log_id = cost_logs.log_id"""

	if parameters:
	conditions = ' AND '.join(
	f"logs.{parameter} = ?"
	for parameter in parameters
	)

	final_query = f"{columns_only_query} WHERE {conditions};"

	else:
	final_query = f"{columns_only_query};"

	# execute the query
	with connect(DATABASE_PATH) as connection:
	data = connection.execute(final_query, values).fetchall()

	connection.close()

	return data

	CREATE TABLE IF NOT EXISTS papers_days (
	paper_day_id INTEGER PRIMARY KEY AUTOINCREMENT,
	paper_id INTEGER NOT NULL REFERENCES papers(paper_id),
	day_id INTEGER NOT NULL,
	CONSTRAINT unique_paper_day UNIQUE (paper_id, day_id)
	);

	CREATE TABLE IF NOT EXISTS papers_days_delivered (
	papers_days_delivered_id INTEGER PRIMARY KEY AUTOINCREMENT,
	paper_day_id INTEGER NOT NULL REFERENCES papers_days(paper_day_id),
	delivered INTEGER NOT NULL CHECK (delivered IN (0, 1))
	);

	CREATE TABLE IF NOT EXISTS papers_days_cost (
	papers_days_cost_id INTEGER PRIMARY KEY AUTOINCREMENT,
	paper_day_id INTEGER NOT NULL REFERENCES papers_days(paper_day_id),
	cost REAL
	);