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Function arguments suggestion/autocomplete in VSCode for Python

In RStudio, function variables, parameters or arguments are displayed by pressing tab.
While VSCode has a lot of features, I cannot find a similar one for Python.
I found a way for VSCode to show me the definition of the function while hovering in the function itself, but there are no autocompletion for the actual variables of that function (nor suggestions while writing). Besides, the tooltips close itself as soon as I start typing the variables.
Is there a way to get something more similar regarding autocompletion and suggestion of function variables in VSCode while using Python?
Thanks.

According to your description, it is recommended that you use the extension "Pylance", which provides outstanding language service functions.
Its 'Docstrings' and 'auto-completion' functions show us the function parameters and will not close the prompt when inputting:
Part of its function introduction:

Do I need to do type checking when preparing library for open source?

I have I small module that I use inside one of my projects. Now I decided to place it on github so now I am writing some docstrings and cleaning the code.
I have a composition of 2 classes so the initialization looks like this:
foo = Class_1()
bar = Class_2(param1=foo)
I know that the first argument to the Class_2 has to be an instance of Class_1 or the code won't work. But it may be clear only for me as I wrote code of Class_2, but when using module as API it may be unclear for a user that param1 has to be an instance of Class_1. If someone will use bar = Class_2(param1='foo'). The trackback will be bad and it will be impossible to understand what happened. So the question is: do I need to check in my __init__ that isinstance(param1, Class_1) and if no raise an excaption with an appropriate message, or writing good documentation is enough?

This is very opinion-based (not great for StackOverflow in particular) - but in my opinion, you should do both.
On the one hand, using isinstance() and exception-handling are both good defensive-coding practices.
On the other hand, inline documentation is nice. Per the Python developer guide:
The markup used for the Python documentation is reStructuredText, developed by the docutils project, amended by custom directives and using a toolset named Sphinx to post-process the HTML output.
Some IDEs, such as JetBrains PyCharm, are configured to automatically pick up well-formed reST docstrings and perform automated type-checking based on those conventions (which I've found to be really useful). See also: PEP 257 and What is the standard Python docstring format? for details.

How do I display function arguments in ipython qtconsole?

I'm using IPython qtconsole under windows 7, and when I first write a method name and type the bracket, a popup shows method parameters.
What is the way to display that popup explicitly, once it has disappeared? This is pretty common 'show method parameters' shortcut that I'm talking about, but I've failed to find the shortcut to it after an embarrassing amount of google searches.

In Spyder, try View - Panes - Object inspector. Then type the full name of the function.

I would highly recommend relying on the Python Library Reference rather than any in-IDE tools, at least for functions and classes that are in the standard library. For objects outside those libraries however... it looks like you can type object_name followed by a question mark, that is, object_name?, to get a list of informative details about the object. (Since everything is an object, this presumably includes functions.)
For your specific question, it looks, from the iPython docs, like the TAB key is what you're looking for, but somehow I doubt you haven't already tried that.

Use user provided python code during runtime

I'm developing a system that operates on (arbitrary) data from databases. The data may need some preprocessing before the system can work with it. To allow the user the specify possibly complex rules I though of giving the user the possibility to input Python code which is used to do this task. The system is pure Python.
My plan is to introduce the tables and columns as variables and let the user to anything Python can do (including access to the standard libs). Now to my problem:
How do I take a string (the user entered), compile it to Python (after adding code to provide the input data) and get the output. I think the easiest way would be to use the user-entered data a the body of a method and take the return value of that function a my new data.
Is this possible? If yes, how? It's unimportant that the user may enter malicious code since the worst thing that could happen is, that he screws up his own system, which is thankfully not my problem ;)

Python provides an exec() statement which should do what you want. You will want to pass in the variables that you want available as the second and/or third arguments to the function (globals and locals respectively) as those control the environment that the exec is run in.
For example:
env = {'somevar': 'somevalue'}
exec(code, env)
Alternatively, execfile() can be used in a similar way, if the code that you want executed is stored in its own file.
If you only have a single expression that you want to execute, you can also use eval.

Is this possible?
If it doesn't involve time travel, anti-gravity or perpetual motion the answer to this question is always "YES". You don't need to ask that.
The right way to proceed is as follows.
You build a framework with some handy libraries and packages.
You build a few sample applications that implement this requirement: "The data may need some preprocessing before the system can work with it."
You write documentation about how that application imports and uses modules from your framework.
You turn the framework, the sample applications and the documentation over to users to let them build these applications.
Don't waste time on "take a string (the user entered), compile it to Python (after adding code to provide the input data) and get the output".
The user should write applications like this.
from your_framework import the_file_loop
def their_function( one_line_as_dict ):
one_line_as_dict['field']= some stuff
the_file_loop( their_function )
That can actually be the entire program.
You'll have to write the_file_loop, which will look something like this.
def the_file_loop( some_function ):
with open('input') as source:
with open('output') as target:
for some_line in source:
the_data = make_a_dictionary( some_line )
some_function( the_data )
target.write( make_a_line( the_data ) )
By creating a framework, and allowing users to write their own programs, you'll be a lot happier with the results. Less magic.

2 choices:
You take his input and put it in a file, then you execute it.
You use exec()

If you just want to set some local values and then provide a python shell, check out the code module.
You can start an instance of a shell that is similar to the python shell, as well as initialize it with whatever local variables you want. This would assume that whatever functionality you want to use the resulting values is built into the classes you are passing in as locals.
Example:
shell = code.InteractiveConsole({'foo': myVar1, 'bar': myVar2})

What you actually want is exec, since eval is limited to taking an expression and returning a value. With exec, you can have code blocks (statements) and work on arbitrarily complex data, passed in as the globals and locals of the code.
The result is then returned by the code via some convention (like binding it to result).

well, you're describing compile()
But... I think I'd still implement this using regular python source files. Add a special location to the path, say '~/.myapp/plugins', and just __import__ everything there. Probably you'll want to provide some convenient base classes that expose the interface you're trying to offer, so that your users can inherit from them.

How to document and test interfaces required of formal parameters in Python 2?

To ask my very specific question I find I need quite a long introduction to motivate and explain it -- I promise there's a proper question at the end!
While reading part of a large Python codebase, sometimes one comes across code where the interface required of an argument is not obvious from "nearby" code in the same module or package. As an example:
def make_factory(schema):
entity = schema.get_entity()
...
There might be many "schemas" and "factories" that the code deals with, and "def get_entity()" might be quite common too (or perhaps the function doesn't call any methods on schema, but just passes it to another function). So a quick grep isn't always helpful to find out more about what "schema" is (and the same goes for the return type). Though "duck typing" is a nice feature of Python, sometimes the uncertainty in a reader's mind about the interface of arguments passed in as the "schema" gets in the way of quickly understanding the code (and the same goes for uncertainty about typical concrete classes that implement the interface). Looking at the automated tests can help, but explicit documentation can be better because it's quicker to read. Any such documentation is best when it can itself be tested so that it doesn't get out of date.
Doctests are one possible approach to solving this problem, but that's not what this question is about.
Python 3 has a "parameter annotations" feature (part of the function annotations feature, defined in PEP 3107). The uses to which that feature might be put aren't defined by the language, but it can be used for this purpose. That might look like this:
def make_factory(schema: "xml_schema"):
...
Here, "xml_schema" identifies a Python interface that the argument passed to this function should support. Elsewhere there would be code that defines that interface in terms of attributes, methods & their argument signatures, etc. and code that allows introspection to verify whether particular objects provide an interface (perhaps implemented using something like zope.interface / zope.schema). Note that this doesn't necessarily mean that the interface gets checked every time an argument is passed, nor that static analysis is done. Rather, the motivation of defining the interface is to provide ways to write automated tests that verify that this documentation isn't out of date (they might be fairly generic tests so that you don't have to write a new test for each function that uses the parameters, or you might turn on run-time interface checking but only when you run your unit tests). You can go further and annotate the interface of the return value, which I won't illustrate.
So, the question:
I want to do exactly that, but using Python 2 instead of Python 3. Python 2 doesn't have the function annotations feature. What's the "closest thing" in Python 2? Clearly there is more than one way to do it, but I suspect there is one (relatively) obvious way to do it.
For extra points: name a library that implements the one obvious way.

Take a look at plac that uses annotations to define a command-line interface for a script. On Python 2.x it uses plac.annotations() decorator.

The closest thing is, I believe, an annotation library called PyAnno.
From the project webpage:
"The Pyanno annotations have two functions:
Provide a structured way to document Python code
Perform limited run-time checking "