PyCharm Professional: Python Development for Flask

Russell Bateman
February 2022
last update:

I downloaded PyCharm Professional for a 30-day trial. My purchase price will be $89 if I decide to continue. Right now, I'm most interested in Flask development because I might be using it at the office.

Links

Notes on set-up

  1. My PyCharm subscription is valid until 3 March 2022.
  2. I have long used PyCharm Community Edition, however, Flask support comes only in the Professional version.
  3. Even though Python 3.8.10 came natually installed on my Linux Mint distribution, by default, PyCharm only offered the Python 2.7 interpreter. Adding a Python interpreter was the first thing I tackled—offended by the "old" mindset.
  4. python3 on my host is at /usr/bin/python3; this is what I set up as my Python interpreter. Fortunately, that appeared to be enough.
  5. PyCharm will assist in downloading and installing a Python interpreter, especially if there is no suitable Python on the host. I did not try this.
  6. PyCharm sets up everything needed to develop for Flask—no need to squint at pip3 command lines, especially no need to convert from Python 2 to Python 3 pip commands as other tutorials I saw require (because "everyone" doing Flask is still running on Python 2). For example, commands like (these are Python 2). In times past, I have followed instructions written for Python 2, but needed in Python 3 and there were some gotchas (more than just adding '3' to the commands), but I don't remember specifics. Anyway, I didn't have to do any of this:
  7. A virtual environment may be set up and shared for use by other projects. This appears to make set-up easier (and the same) for other projects.

First project: flask

  1. The project I created is flask and it's on path /home/russ/dev/flask.
  2. The newly created Flask application, app.py, can be run by
  3. Running gets me this: 
    FLASK_APP = app.py
FLASK_ENV = development
FLASK_DEBUG = 0
In folder /home/russ/dev/flask
/home/russ/dev/flask/venv/bin/python -m flask run
 * Serving Flask app 'app.py' (lazy loading)
 * Environment: development
 * Debug mode: off
 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
  4. Though the tutorial didn't say to do it, I loaded the URL in my browser to see: 
    Hello World!
  5. A note says if Flask support has been enabled in the PyCharm project, the Python Console (reached along the bottom edge of the IDE as installed on my host) begins acting as a Flask console. The Flask console accepts Flask-specific commands (after >>>).
  6. The Flask console implements an "IntelliSense"-style interface, i.e.: offers suggestions as soon as you begin typing a command. This is especially convenient when you don't know what you're doing.

That was the whole tutorial.

Next, I moved on to "Creating Web Applications with Flask." The featured application, MeteoMaster (obviously written by a speaker of French some other language that uses meteo- for "weather," processes weather data stored in a database and presents it in scatter- or line charts.

Second project meteomaster...

  1. It's very important not to forget to click on Flask down the left-hand side of the New Project. Failing to do that results in some confusion and back-tracking. We're using the existing virtual environment—we can because we enabled that in our first project above. We don't have to re-enable it this time.
  2. Apparently, kicking off a new project always results in app.py's "Hello World!" code. Why not?
  3. This exercise teaches how to use requirements.txt in PyCharm. You right-click the project root (that is, the bold-faced name of the project and not the title bar Project), choose New → File, and see requirements.txt added to the project's files just under app.py. Edit that to add requirements in the format 
    requirement-name==version
    I guess this is Python's answer to Maven.
  4. The requirement must be installed. If you lose track of the IDE link to do that, just close the requirements.txt edit window and, if not installed, you'll see a control to click for that.
  5. Disaster: Installing requirements can take considerable time. Installing for this weather project took 5 mintues and, ultimately, failed. JetBrains deflects criticism for this saying, "the problem is out of IDE control."
  6. Pressing JetBrains on this for an answer, they tol me that a (very slightly) different requirements list was needed for Python 3.8.10 as the tutorial was written for Python 3.7. (Okay, this is just another reason to prefer a world-class development language like Java or C/C++ to Python, but saying it doesn't help.) I modified requirements.txt and it worked:
    Click==7.0
cycler==0.10.0
Flask==1.0.2
Jinja2==2.10
kiwisolver
MarkupSafe==1.1.0
matplotlib
numpy
pyparsing==2.3.0
python-dateutil==2.7.5
six==1.11.0
SQLAlchemy==1.2.14
Werkzeug==0.14.1

Setting up a database...

  1. Using this database: https://github.com/allaredko/flask-tutorial-demo/blob/master/user_database. This must be saved to the root of the project and (it's already) named user_database. Once you've saved it there, click the Reload All from Disk button in the IDE (it's two spinning arrows).
  2. Install the SQLite driver. Confusingly, there wasn't an identifiable "warning" message, but there was, toward the right side, a hyper link entitled, Download ver. 3.34.0. Then I clicked OK.
  3. It doesn't go identically to what's in the tutorial. I clicked the user_database's hamburger menu (⋮) to do some playing around to see what the tutorial was showing. Ultimately, however, you just need to click the right-angle icon at the left of user_database. It does look a little different that what's shown in the tutorial.

  4. There's no right-clicking user_database to get a Properties context menu; it isn't there. Instead, there is a "wrench" icon button in the Database toolbar leading to Data Source Properties. In the dialog that appears, there is a Test Connection hyperlink near the bottom. I got a notice that my connection was good.
  5. Now we create the first, real Python-code workhorse, user_database.py as suggested by the tutorial. This is done by right-clicking on the root and choosing New → File, then naming it user_database.py. (Now, meteomaster is what I called my project, but I think the tutorial called theirs flask-tutorial-demo. Keep this in mind.)

    6. Notice that, based on the filename extension, PyCharm "decorates" the new file by changing its icon from that of a simple file to a Python file icon.

  6. We copy and paste the contents for this new Python file from the tutorial to the new .py file we created (at the root). There are many errors. If I click on (the first) line with red underlining, I then do Alt+Enter and can choose to Import alchemy-MetaData(SchemaItem) by just pressing Enter. I go on to do the others like this too...
  7. ...however, be careful about how you do Column, Integer and String as they must come in from SQLAlchemy (and from nowhere else that happens to offer versions of these identifiers). To get these, you'll do as above, but choose Import this name, press Enter, but then you'll have to choose (very carefully) the symbol prefixed with "sqlalchemy." If you don't, things will get real confusing real fast.

    8. If life gets too ugly, you can cheat by sneaking a peak at allaredko/flask-tutorial-demo to get better oriented.

Plotting the scatter chart...

  1. New file charts.py gets created in the project root. You already know now how to create a new file. Just copy the contents from the tutorial, paste into your new file, then fix the errors as before.

    2. It's harder to fix the red-underlined errors this time because their solution is to create new symbols or functions in user_database.py. (When was the tutorial going to tell us this?) See allaredko/flask-tutorial-demo/user_database.py starting after class Meteo() and add lines 30 through 49 to user_database.py. The errors in the pasted code of charts.py will disappear.

  2. Stop and rerun meteomaster using Shift+F10 to preview the advertised graph.

    3. No, I couldn't find the preview graph either. This is the problem with tutorials being written by authors who already know where they want this to go and fail to imagine themselves as a developer who needs the tutorial (or wants to follow it) and doesn't have all the answers.

    Bug filed.

  3. It turns out that just running charts.py in the debugger was enough.
    1. In the Project pane, right-click charts.py.
    2. Choose Run 'charts.py'.

(More to come...)