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Time Stopper 2.0 Tutorial


Time Stopper 2.0 Tutorial

I've been playing Mega Man 2 for over 30 years and have finished it countless times so allow me to share my go-to boss order and strategies. This walkthrough follows the optimal order to face Mega Man 2's bosses so you can make the most of each stage with unlocked items and weapons as well as exploit every boss's weakness.

Although the exact order of which bosses to tackle next is often debated, there's no denying that defeating Metal Man first is the best way to go. To beat Metal Man, simply jump to avoid the blades that he throws while shooting like crazy. He'll sometimes leap to the other side so stay somewhat in the middle to avoid the most damage.

I recommend Heat Man after Crash Man so you can use the Crash Bomber weapon to create little shortcuts by destroying the weak wall segments. Also, Item-2 makes Heat Man's stage much easier so now that we have it, you can use it during the final disappearing blocks segment for an easy-breezy time. Specifically, deploy it on the ledge right before the lava river so you don't run out of energy.

As the blocks assemble 2 at a time, jump over them when needed then blast the assembled enemies with Bubble Lead which should defeat them in 1 shot each. The boss will be annihilated once most of the blocks are taken care of; specifically, after you destroy 14 enemies. Keep in mind that some of the enemies move more aggressively than others so stay on your toes.

When working your way through this next stage, ensure that your Crash Bomber ammo remains topped-up and avoid falling down the false floors; using the Items will help a lot with that. Anyway, this is the most annoying boss in the whole game. There are a couple of ways to take it down and I'll go over both with the first being easy yet time-consuming and the second being risky yet quick.

The tutorial demonstrates quick ways to freeze panes in Excel. You will learn how to quickly lock header row or/and the first column. You will also see how to freeze several panes at a time to make Excel always show certain rows or/and columns when you scroll down or right. These tips work in all modern versions of Excel 365, 2021, 2019, 2016, 2013, 2010 and 2007.

Typically, you would want to lock the first row to see the column headers when you scroll down the sheet. But sometimes your spreadsheet may contain important information in a few top rows and you may want to freeze them all. Below you will find the steps for both scenarios.

I am successfully able to freeze the top row. I do so and then save. However, each time I open the spreadsheet I have to manually re-freeze the top row. The save will not stick Is there any way to permanently freeze the top row so I do not have to do so each time I open the sheet Thanks in advance.

My problem, also. I have used excel since it came on the market and I switched from Lotus123, if I remember correctly. But every time I post this problem I get the same lecture on how to freeze rows like I was born yesterday. I have other spreadsheets with the top row frozen. But, even in those sheets the "freeze" icon is no longer highlighted. Also, the fonts are huge even though it is set on 8. The worksheets from previous years are the right font 11. If I have caused this problem on my Windows 10 will someone please tell me how to activate my freeze icon Clicking on "normal" view does nothing.

Quick Cup Fix Stopper Sets provide an easy solution to a big problem. Two and four-pack stopper sets are available to slow the spills. Once installed on the lid, stoppers are top rack dishwasher safe.

On the other hand, when you call .stop(), you first check that the Python timer is running. If it is, then you calculate the elapsed time as the difference between the current value of perf_counter() and the one that you stored in ._start_time. Finally, you reset ._start_time so that the timer can be restarted, and print the elapsed time.

First, see how you can customize the text used to report the time spent. In the previous code, the text f"Elapsed time: elapsed_time:0.4f seconds" is hard-coded into .stop(). You can add flexibility to classes using instance variables, whose values are normally passed as arguments to .__init__() and stored as self attributes. For convenience, you can also provide reasonable default values.

To add names to your Python timer, you need to make two more changes to First, Timer should accept name as a parameter. Second, the elapsed time should be added to .timers when a timer stops:

Lines 17 to 20: You can use the special .__post_init__() method for any initialization that you need to do apart from setting the instance attributes. Here, you use it to add named timers to .timers.

Context managers have been a part of Python for a long time. They were introduced by PEP 343 in 2005, and first implemented in Python 2.5. You can recognize context managers in code by the use of the with keyword:

In this example, open("") is an expression that returns a context manager. That context manager is bound to the name fp. The context manager is in effect during the execution of print(). This one-line code block executes in the context of fp.

Timer is now a context manager. The important part of the implementation is that .__enter__() calls .start() to start a Python timer when the context is entered, and .__exit__() uses .stop() to stop the Python timer when the code leaves the context. Try it out:

Based on the blueprint above, you only need to decide what to do before and after you call the decorated function. This is similar to the considerations about what to do when entering and exiting the context manager. You want to start a Python timer before calling the decorated function, and stop the Python timer after the call finishes. You can define a @timer decorator as follows:

However, the decorator still applies to the whole function. This means that your code is taking into account the time it takes to print the tutorial, in addition to the time it takes to download. Run the script one final time:

Consider time(). The main purpose of this function is to represent the actual time right now. It does this as the number of seconds since a given point in time, called the epoch. The number returned by time() is quite big, which means that there are fewer numbers available, and the resolution suffers. Specifically, time() is not able to measure nanosecond differences:

The challenges with representing time as a float are well known, so Python 3.7 introduced a new option. Each time measurement function now has a corresponding _ns function that returns the number of nanoseconds as an int instead of the number of seconds as a float. For instance, time() now has a nanosecond counterpart called time_ns():

There are two functions in time that do not measure the time spent sleeping. These are process_time() and thread_time(), which are useful in some settings. However, for Timer, you typically want to measure the full time spent. The final function in the list above is monotonic(). The name alludes to this function being a monotonic timer, which is a Python timer that can never move backward.

All these functions are monotonic except time(), which can go backward if the system time is adjusted. On some systems, monotonic() is the same function as perf_counter(), and you can use them interchangeably. However, this is not always the case. You can use time.get_clock_info() to get more information about a Python timer function:

timeit is excellent for benchmarking a particular snippet of code. However, it would be very cumbersome to use it to check all parts of your program and locate which sections take the most time. Instead, you can use a profiler.

This command runs with profiling turned on. You save the output from cProfile in, as specified by the -o option. The output data is in a binary format that needs a dedicated program to make sense of it. Again, Python has an option right in the standard library! Running the pstats module on your .prof file opens an interactive profile statistics browser:

The total time (tottime) column indicates how much time your code spent inside a function, excluding time in sub-functions. You can see that none of the functions above really spend any time doing this. To find where the code spent most of its time, issue another sort command:

You can use pstats to get some idea of where your code is spending most of its time and then try to optimize any bottlenecks you find. You can also use the tool to understand the structure of your code better. For instance, the commands callees and callers will show you which functions call and are called by a given function.

Note: You can also profile the memory consumption of your code. This falls outside the scope of this tutorial. However, you can check out memory-profiler if you need to monitor the memory consumption of your programs.

Before you run the profiler, you need to tell it which functions to profile. You do this by adding a @profile decorator inside your source code. For example, to profile Timer.stop(), you add the following inside

First, note that the time unit in this report is microseconds (1e-06 s). Usually, the most accessible number to look at is %Time, which tells you the percentage of the total time your code spends inside a function at each line. In this example, you can see that your code spends almost 70 percent of the time on line 47, which is the line that formats and prints the result of the timer.

Now you can add Python timer functions to your own code! Keeping track of how fast your program runs in your logs will help you monitor your scripts. Do you have ideas for other use cases where classes, context managers, and decorators play well together Leave a comment down below! 153554b96e


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