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Develop a password security check module. The password will be considered strong enough if its length is greater than or equal to 10 symbols, it has at least one number, as well as containing one uppercase letter and one lowercase letter in it. def checkio(data): 'Return True if password strong and False if not' num = False upper = False lower = False for i in range(len(data)): num = num or data[i].isnumeric() upper = upper or data[i].isupper() lower = lower or data[i].islower() return num and upper and lower and len(data)>=10

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Teach Coding in the Classroom: Resources from ISTE '14 I was super excited to attend Hack Education (originally called “EdubloggerCon”), an all-day unconference held the Friday before the formal start of ISTE 2014. This interactive day of learning, now in its eighth year, was touted to me as the event to attend in Atlanta, and it did not disappoint. The informal, small-group conversations were inclusive and welcoming. The "rule of two feet" meant that if you needed to move, you were encouraged. And session topics were diverse -- on the schedule were discussions about maker education, augmented reality, design thinking, game-based learning, coding in the classroom, digital storytelling, and many, many more!

How to work with large JSON datasets using Python and Pandas Working with large JSON datasets can be a pain, particularly when they are too large to fit into memory. In cases like this, a combination of command line tools and Python can make for an efficient way to explore and analyze the data. In this post, we’ll look at how to leverage tools like Pandas to explore and map out police activity in Montgomery County, Maryland. We’ll start with a look at the JSON data, then segue into exploration and analysis. When data is stored in SQL databases, it tends to follow a rigid structure that looks like a table. Here’s an example from a SQLite database:

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