Once we have learned any programming language, the next task is to become familiar with the most common activities required to get our jobs done. Saving data to files is often an important part of any significant data processing activity. In this training opportunity, we will begin by discovering how to simply and quickly print what we have created to files on our local hard drive.
In this session we will review how to save data into several classic & ever-popular data formats.
Finally, we will leverage what we have learned so as to be able to tag & keep track of what has been stored in any data-file type. By the time the student has completed this training, the student will know what he or she will need to know in order to manage & track data without using any 3rd party database technology!
A quick review of the major mission & themes to be covered in Python 3000.
While the content of a file is usually what we are most interested in, knowing more about the file is also important. For example, learning more about file size, creation date, security information, as well as both common & platform-specific information is often just as important.
In this lesson, we will:
• Discover how to retrieve file meta-data
• Understand common & relivable cross-platform values
• Learn how platform-specific security attributes are used
• Practice how to manually represent year, month, and day information
• Discover how to convert time values to localized time displays
Like the content of any book, the content of a file can be categorized. Often referred to as "indexing," our ability to "tag" and keep track of important parts of a file is the heart & soul of modern file-management activities.
In this lesson we will:
• Learn the secret behind keeping track of file content
• Review how to track locations of binary data
• Discover real-world text indexing success stories
• Create a binary text-data writer, seeker, and reader
Much like the CSV Standard itself, when moving human-readable data between operating systems, we can see some curious problems!
In this lesson, we will document, demystify & correct the curious problems we often see when transferring our programming & other human-readable files between Unix-like systems (zOS, OS/X, Linux, etc.) and Microsoft Windows.
In this lesson we will:
• Discover the difference between “raw” and “cooked” data
• Apply what we have learned to manage variant-length text data
• Create a report using the tab-delimited format (TDF)
• Review a simple strategy to index official CSV files
• Create a newline-delimited record writer, seeker, and reader
Everyone is surprised upon learning how easy it is to append printable data to a file in Python. Even more surprising however can be to discover that Python has built-in support for saving data in popular data formats, as well.
In this lesson, we will:
• Lean how to open / truncate a file
• Discover how to use print() report to files
• Learn how to “quick print” a CSV file in Unix format
• Learn how to read + split CSV files
• Learn how to remove a file from the file system
• Dual-render a faceplate that can be used for calendar representation
While a very common standard, there are sight nuances to be found in the CSV standard. In this lesson, we will review the official support for generating CSV file for the two most popular formats.
• Discover how to enumerate supported textual csv formats
• Create a program that will format data in all supported formats
• Learn this difference between “excel” and “unix” CSV formats
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