text stringlengths 1 81 | start float64 0 10.1k | duration float64 0 24.9 |
|---|---|---|
change our approach for instance like | 3,600.24 | 4.26 |
one Paradigm that is not uncommon is to | 3,602.16 | 5.28 |
use something a little more | 3,604.5 | 5.52 |
a little less common like a vertical bar | 3,607.44 | 4.679 |
so I could go in and change all of my | 3,610.02 | 4.44 |
commas to Vertical bars that too could | 3,612.119 | 4.021 |
eventually come back to bite Us in that | 3,614.46 | 3.599 |
if my file eventually has vertical bar | 3,616.14 | 3.9 |
somewhere it might still break so maybe | 3,618.059 | 3.901 |
that's not the best approach I could | 3,620.04 | 3.6 |
maybe do something like this I could | 3,621.96 | 3.78 |
escape the data as I've done in the past | 3,623.64 | 5.28 |
and maybe I could put quotes around any | 3,625.74 | 6.18 |
English string that itself contains the | 3,628.92 | 5.1 |
comma and that's fine I could do that | 3,631.92 | 5.22 |
but then my code students.pi is going to | 3,634.02 | 5.039 |
have to change too because I can't just | 3,637.14 | 4.74 |
naively split on a comma Now I'm going | 3,639.059 | 4.981 |
to have to be smarter about it I'm going | 3,641.88 | 4.14 |
to have to take into account split only | 3,644.04 | 4.38 |
on the commas that are not inside of | 3,646.02 | 4.559 |
quotes and oh it's getting complicated | 3,648.42 | 4.32 |
fast and at this point you need to take | 3,650.579 | 3.661 |
a step back and consider you know what | 3,652.74 | 3.66 |
if we're having this problem odds are | 3,654.24 | 4.5 |
many other people before us have had the | 3,656.4 | 5.04 |
same problem it is incredibly common to | 3,658.74 | 4.74 |
store data in files it is incredibly | 3,661.44 | 5.28 |
common to use CSV files specifically and | 3,663.48 | 5.579 |
so you know what why don't we see if | 3,666.72 | 4.74 |
there's a library in Python that exists | 3,669.059 | 6.121 |
to read and or write CSV files rather | 3,671.46 | 5.82 |
than reinvent a wheel so to speak let's | 3,675.18 | 3.78 |
see if we can write better code by | 3,677.28 | 3.36 |
standing on the shoulders of others who | 3,678.96 | 3.599 |
have come before us programmers passed | 3,680.64 | 4.08 |
and actually use their code to do the | 3,682.559 | 4.26 |
reading and writing of csvs so we can | 3,684.72 | 4.32 |
focus on the part of our problem that | 3,686.819 | 4.381 |
you and I care about so let's propose | 3,689.04 | 4.74 |
that we go back to our code here and see | 3,691.2 | 5.159 |
how we might use the CSV Library indeed | 3,693.78 | 5.519 |
within python there is a module called | 3,696.359 | 6 |
CSV the documentation for it is at this | 3,699.299 | 4.681 |
URL here in Python's official | 3,702.359 | 3.181 |
documentation but there's a few | 3,703.98 | 3.66 |
functions that are pretty readily | 3,705.54 | 4.799 |
accessible if we just Dive Right In and | 3,707.64 | 4.86 |
let me propose that we do this let me go | 3,710.339 | 4.681 |
back to my code here and instead of | 3,712.5 | 4.859 |
Reinventing this wheel and reading the | 3,715.02 | 4.319 |
file line by line and splitting on | 3,717.359 | 4.2 |
commas and dealing now with quotes and | 3,719.339 | 4.681 |
privet drives and so forth let's do this | 3,721.559 | 5.461 |
instead at the start of my program let | 3,724.02 | 6.48 |
me go up and import the CSV module let's | 3,727.02 | 5.64 |
use this library that someone else has | 3,730.5 | 4.079 |
written that's dealing with all of these | 3,732.66 | 4.139 |
Corner cases if you will I'm still going | 3,734.579 | 4.621 |
to give myself a list initially empty in | 3,736.799 | 4.201 |
which to store all these students but | 3,739.2 | 3.599 |
I'm going to change my Approach here now | 3,741 | 4.74 |
just a little bit when I open this file | 3,742.799 | 6.121 |
with with let me go in here and change | 3,745.74 | 5.28 |
this a little bit I'm going to go in | 3,748.92 | 4.52 |
here now and say this | 3,751.02 | 6.539 |
reader equals CSV dot reader passing in | 3,753.44 | 6.46 |
file as input so it turns out if you | 3,757.559 | 4.081 |
read the documentation for the CSV | 3,759.9 | 4.02 |
module it comes with a function called | 3,761.64 | 4.679 |
reader whose purpose in life is to read | 3,763.92 | 5.52 |
a CSV file for you and figure out where | 3,766.319 | 4.681 |
are the commas where are the quotes | 3,769.44 | 3.78 |
where are all the the potential Corner | 3,771 | 4.14 |
cases and just deal with them for you | 3,773.22 | 3.899 |
you can override certain defaults or | 3,775.14 | 3.54 |
assumptions in case you're using not a | 3,777.119 | 3.48 |
comma but a pipe or something else but | 3,778.68 | 3.659 |
by default I think it's just going to | 3,780.599 | 4.74 |
work now how do I iterate over a reader | 3,782.339 | 5.161 |
and not the raw file itself it's almost | 3,785.339 | 4.26 |
the same the library allows you still to | 3,787.5 | 6.059 |
do this for each row in the reader so | 3,789.599 | 5.401 |
you're not iterating over the file | 3,793.559 | 3.54 |
directly now you're iterating over the | 3,795 | 3.72 |
reader which is again going to handle | 3,797.099 | 4.02 |
all of the parsing of commas and new | 3,798.72 | 4.619 |
lines and more for each row in the | 3,801.119 | 4.801 |
reader what am I going to do well at the | 3,803.339 | 4.381 |
moment I'm going to do this I'm going to | 3,805.92 | 4.679 |
append to my students list the following | 3,807.72 | 5.399 |
dictionary a dictionary that has a name | 3,810.599 | 5.281 |
whose value is the current Row's First | 3,813.119 | 5.641 |
Column and whose house or rather home | 3,815.88 | 6.479 |
now is the Rose second column now it's | 3,818.76 | 6.299 |
worth noting that the reader for each | 3,822.359 | 4.861 |
line in the file indeed returns to me a | 3,825.059 | 4.381 |
row but it returns to me a row that's a | 3,827.22 | 4.079 |
list which is to say that the first | 3,829.44 | 3.599 |
element of that list is going to be the | 3,831.299 | 3.841 |
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