Final Exam: Dynamic Data Handling with Python
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- Includes Assessment
- Earns a Badge
Final Exam: Dynamic Data Handling with Python will test your knowledge and application of the topics presented throughout the Dynamic Data Handling with Python track of the Skillsoft Aspire Pythonista to Python Master Journey.
WHAT YOU WILL LEARN
add a foreign key constraint between tablesanalyze the common and distinct values in two tables using various petl functionsautomate operations using triggerscalculate aggregate statistics for a field in a table using the aggregate functionconfigure an httpx.Cookies instance to send a collection of properties to a remote servercreate and invoke stored procedurescreate and use a SQL primary key constraint with autoincrementcreate a table and insert rows into itcreate a table in SQLite and read it into petl using SQLAlchemy and SQLite3create SQL indexes on tablescreate tables using object relational mappingdefine and submit a POST request containing JSON and binary datadownload a set of files sequentially using HTTPXdrop a table, recreate it, and insert rows into itexecute alter operations to add constraints and indices to tablesexplore different ways to use logical operators for querying dataget data from MS Excel and perform basic operations on the dataidentify the different options available to stream large volumes of data in an HTTP responseidentify when a redirect has taken place upon submitting an HTTP requestimplement an httpx.Cookies instance to send a collection of properties to a remote serverimplement check constraintsimplement insert and delete operationsimplement slicing, dicing, and merging operations on petl data tablesimplement specialized types of joins such as anti joins and cross joinsimplement split operations on data stored within petl tablesinsert and edit columns and rows in petl data tablesinsert and edit rows and columns in petl data tablesinsert data into viewsinsert rows into a tableinstall petl and create a basic petl data table out of toy data
install SQLAlchemy and connect to MySQLinstall SQLAlchemy and connect to MySQLinstall the latest available version of HTTPX on your systemlimit the amount of time your app spends waiting to get served a response to an HTTP request using timeoutsmake use of the rowreduce() function to reduce rows and compute aggregate statisticsmap fields in a petl table to transformation based on functionsperform insert and delete operationsperform joins based on overlapping intervals rather than absolute valuesperform SQL like equi-joins on petl data tablesperform various grouping operations on the data in a tableperform various import and export operations on CSV, TSV, and TXT files.perform various update and replace operations on petl data tables by defining functions to perform transformationsquery data using object relational mappingread in data from the serialized pickle and XML file formatsread JSON data, perform various operations, and export it to a persistent formatrecall the types of exceptions that can be encountered when sending and processing requests with HTTPXrecognize the messages conveyed in the different status codes sent in an HTTP responserecognize the types of exceptions that can be encountered when sending and processing requests with HTTPXrecognize when a redirect has taken place upon submitting an HTTP requestretrieve information about a remote resource using a HEAD requestsubmit data to a remote server using a POST request with HTTPXsubmit HTTP GET requests with one or more parameters using HTTPXuse an httpx.Cookies instance to send a collection of properties to a remote serveruse slicing, dicing, and merging operations on petl data tablesuse the aggregate function to calculate aggregate statistics for a field in a tableuse the facet petl function to define filters on specific fields in a tableuse the fetchmany() function to retrieve the output of a select queryuse the HTTPX AsynClient to download a set of files asynchronouslyuse triggers to automate operationswork with transaction aborts
IN THIS COURSE
1.Dynamic Data Handling with Python36sUP NEXT
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