steward | PHP libraries that makes Selenium WebDriver | Functional Testing library
kandi X-RAY | steward Summary
Support
Quality
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- Start the test cases .
- Create a ProcessSet from a list of files .
- Initialize the console .
- Downloads a specific version .
- Start the NullWebDriver .
- Save a screenshot of a test page .
- Publishes a test result to the API .
- Reads the XML file and returns it .
- Build out tree
- Configures the CapabilitiesResolver option .
steward Key Features
steward Examples and Code Snippets
Trending Discussions on steward
Trending Discussions on steward
QUESTION
I keep getting this error. I don't even know how to identify the row that is in error as the data I am requesting is jumbled. I can't provide a URL to the API but I will provide a sample of the first few lines of data.
My code:
url = "url"
payload={}
headers = {}
data = requests.request("GET", url, headers=headers, data=payload)
df = pd.read_csv(io.BytesIO(data.content))
print(df)
Error:
pandas.errors.ParserError: Error tokenizing data. C error: Expected 6 fields in line 5, saw 7
Data from API:
fieldId^raceId^tabNo^position^margin^horse^trainer^jockey^weight^barrier^inRun^flucs^priceSP^priceTAB^stewards^rating^priceBF^horseId^priceTABVic^gears^sex^age^rno^neural^sire^dam^foalDate^jockeyId^trainerId^claim
6043351^894992^3^1^0.1^Harley Street^Natalie Jarvis^Jack Martin^59.5^7^settling_down,1;m800,1;m400,1;^opening,2.10;starting,2.60;^2.6^2.5^^34^2.97625207901001^930781^2.7^^Gelding^3^5^6.38^Exceed And Excel^Avenue^01/08/2018^15238^25478^0^
6043349^894992^1^2^0.1^Eurosay^Todd Smart^Damon Budler^60^2^settling_down,5;m800,5;m400,5;^opening,7.50;starting,10.00;^10^8.2^Held up in straight.^43^13.4302415847778^880761^8.3^^Gelding^6^41^5.95^Eurozone^Magsaya^18/10/2015^16352^26343^1.5^
6043355^894992^7^3^0.3^Titan Star^M F Van Gestel^G Buckley^55.5^1^settling_down,4;m800,4;m400,3;^opening,8.00;starting,5.50;^5.5^6.2^Laid out at start.^60^6^924419^5.6^^Gelding^4^37^14.12^Rubick^Sporty Spur^14/10/2017^9670^3483^0^
6043350^894992^2^4^1.8^Vee Eight^Sue Laughton^Ms R Freeman-Key^61^5^settling_down,3;m800,3;m400,4;^opening,19.00;mid,21.00;starting,20.00;^20^23^^66^25^839743^18.8^^Gelding^8^43^5.29^Commands^Supamach^13/10/2013^12100^27227^0^
6043352^894992^4^5^3.2^Halliday Road^Ms T Bateup^Ms W Costin^58.5^4^settling_down,2;m800,2;m400,2;^opening,9.50;mid,13.00;starting,11.00;^11^11.4^Checked near 200m.^83^15^825899^11.7^^Gelding^8^77^4.49^Congrats^Nickynoo's Girl^12/08/2013^14984^23242^0^
6043353^894992^5^6^3.5^Monte Drifter^R & L Price^Brock Ryan^57.5^6^settling_down,7;m800,7;m400,7;^opening,5.00;mid,3.80;starting,4.00;^4^4^^71^4.5^944388^3.8^^Gelding^3^7^7.98^Capitalist^Belhamage^24/08/2018^15590^26970^0^
6043354^894992^6^7^3.8^Blackhill Kitty^Natalie Jarvis^Ms J Taylor^55.5^3^settling_down,6;m800,6;m400,6;^opening,7.00;mid,6.50;starting,9.00;^9^8.4^^43^9^921457^8.8^Bubble cheeker near side first time. ^Mare^4^11^14.85^Ready For Victory^Bad Kitty^16/10/2017^7901^25478^0^
ANSWER
Answered 2022-Apr-18 at 04:07Since you don't specify a separator for columns in the data, python has to guess and it guessed wrong. Be specific.
data = pd.read_csv(io.BytesIO(data.content), sep="^")
QUESTION
I have a json object (json string) which has values like this:
[
{
"id": 1,
"object_k_id": "",
"object_type": "report",
"object_meta": {
"source_id": 0,
"report": "Customers"
},
"description": "Daily metrics for all customers",
"business_name": "",
"business_logic": "",
"owners": [
"nn@abc.com",
null
],
"stewards": [
"nn@abc.com",
''
],
"verified_use_cases": [
null,
null,
"c4a48296-fd92-3606-bf84-99aacdf22a20",
null
],
"classifications": [
null
],
"domains": []
}
]
Bu the final format I want is something that has removed the nulls and the empty list items: something like this:
[
{
"id": 1,
"object_k_id": "",
"object_type": "report",
"object_meta": {
"source_id": 0,
"report": "Customers"
},
"description": "Daily metrics for all customers",
"business_name": "",
"business_logic": "",
"owners": [
"nn@abc.com"
],
"stewards": [
"nn@abc.com"
],
"verified_use_cases": [
"c4a48296-fd92-3606-bf84-99aacdf22a20"
],
"classifications": [],
"domains": []
}
]
I want the output to exclude nulls, empty strings and make it look more clean. I need to do this recursively for all the lists in all the jsons I have.
Even more than recursive, it would be helpful if I can do it at one stretch rather than looping through each element.
I need to clean only the lists though.
Can anyone please help me with this? Thanks in advance
ANSWER
Answered 2022-Apr-04 at 05:07You can convert your json
to dict
then use the function
below and convert it to json
again:
def clean_dict(input_dict):
output = {}
for key, value in input_dict.items():
if isinstance(value, dict):
output[key] = clean_dict(value)
elif isinstance(value, list):
output[key] = []
for item in value:
if isinstance(value, dict):
output[key].append(clean_dict(item))
elif value not in [None, '']:
output[key].append(item)
else:
output[key] = value
return output
Thanks to N.O
QUESTION
I'm trying to make a chart (either with lines or bars) to show periods of time in certain Stages. Using the data below, the closest I've gotten is to try to get a Gantt chart and turn off the color for the start date, only showing the duration. Rather than the duration in days on the x-axis, I'd like it just to be dates (months or years).
(screenshot - Gantt chart example - note the multiple appearances of "Cultivate")
It's close to what I want, but the stage can be reentered multiple times. So I would like those separate Cultivate periods/bars on one line. Something like this:
Data:
STAGE START END Cultivate 4/25/2008 3/29/2012 Qualify 3/30/2012 7/18/2012 Cultivate 7/19/2012 2/22/2015 Open 2/23/2015 4/17/2020 Cultivate 4/18/2020 6/24/2020 Steward 6/25/2020 3/31/2022ANSWER
Answered 2022-Feb-10 at 00:41Unfortunately, it's not possible to do it by the default chart creator.
A workaround would be building your Spreadsheet with the Gantt Chart in cells and apply conditional formatting for repeating tasks.
You can check it on this spreadsheet https://docs.google.com/spreadsheets/d/1VOxoDlL5auzigm1FSt2gmbjSSmkoRMhVlQiLsKwN4Kk/edit#gid=1539711303
The idea comes from https://infoinspired.com/google-docs/spreadsheet/split-a-task-in-gantt-chart-in-google-sheets/
I tested it out and it works well, but I think that it only accepts one repetitive task
QUESTION
I have some code that I could cross-compile with an older toolchain that used uClibc, but the project is moving to musl libc, and I can't seem to get the code to compile with that toolchain. It always fails during the linking stage with a bunch of errors along these lines:
/opt/miyoo/bin/../lib/gcc/arm-buildroot-linux-musleabi/11.2.0/../../../../arm-buildroot-linux-musleabi/bin/ld: objs/miyoo/src/touchscreen.o: in function `Touchscreen::poll()':
/__w/gmenunx/gmenunx/src/touchscreen.cpp:87: undefined reference to `SDL_PumpEvents'
/opt/miyoo/bin/../lib/gcc/arm-buildroot-linux-musleabi/11.2.0/../../../../arm-buildroot-linux-musleabi/bin/ld: /__w/gmenunx/gmenunx/src/touchscreen.cpp:89: undefined reference to `SDL_GetMouseState'
/opt/miyoo/bin/../lib/gcc/arm-buildroot-linux-musleabi/11.2.0/../../../../arm-buildroot-linux-musleabi/bin/ld: objs/miyoo/src/surface.o: in function `Surface::Surface(SDL_Surface*, SDL_PixelFormat*, unsigned int)':
/__w/gmenunx/gmenunx/src/surface.cpp:74: undefined reference to `SDL_ConvertSurface'
There are a couple that I'm not sure are SDL things, such as IMG_LoadPNG_RW
and TTF_Init
, but for the most part, it's all SDL_Whatever
that the linker can't find, right after the compiler just found it.
You can see the full output from the failing musl build (linking starts on line 857), and compare it to a working uClibc build (linking starts on line 863).
I tried messing around with changing the buildroot settings from static to dynamic, and also both, but that didn't change anything. I also tried adding SDL2, even though I'm fairly certain the code actually depends on SDL 1, but I couldn't get buildroot to make the toolchain when I had SDL2 enabled. I tried some other things like switching around argument orders, but none of it seemed to solve the issue.
For context, I'm trying to build a docker image that can be used to cross-compile software for MiyooCFW in GitHub Actions.
I tweaked a docker image with the old toolchain and created a new one with the new toolchain so that we could build both in GitHub Actions.
This is the buildroot repo I used for the musl toolchain: https://github.com/nfriedly/buildroot
The uClibc toolchain is available in a .7z file on google drive, but I'm not sure where the source for it is. There is also some (incomplete) documentation.
I'm a noob when it comes to most of this stuff, so there may very well be something obvious that I'm just missing.
ANSWER
Answered 2022-Feb-28 at 00:52@user17732522 helped me work through a couple of issues:
- several flags were out of order:
.o
files should come before-l
options-lfreetype
must come after-lSDL_ttf
)
- several flags were missing:
-ljpeg -lpng -lz
after-lSDL_image
-lvorbisfile -lvorbis -logg
after-lSDL_mixer
-lbz2 -lmpg123
at the end
This PR has the fixes that allow it to compile on the new toolchain (without breaking compiling on the old one): https://github.com/MiyooCFW/gmenunx/pull/12
QUESTION
I am new to regular expressions and I have a text as follows. How can I use the RegEx to extract all words with at least one digit in it? Really appreciate it.
text = '''The start of the Civil War in 1861 followed by Tennessee’s secession from the Union and the lodging of
wounded Confederate soldiers on campus did not close East Tennessee University. By spring 1862 when the
trustees finally suspended operations, the majority of students had joined the military, President Joseph
Ridley had resigned, and two professors had left the university. Wounded Confederate soldiers were lodged
at university buildings after the January 1862 Battle of Mill Springs in Kentucky, known as the Battle of
Fishing Creek to the Confederacy. In the fall of 1863, Union troops forced the Confederates out of
Knoxville. On the Hill, the Union Army enclosed the three university buildings with an earthen
fortification they named Fort Byington in honor of an officer from Michigan who was killed in the defense
of Knoxville. They used the buildings for their headquarters, barracks, and a hospital for Black troops.
Despite a Confederate attempt to retake the city by siege—climaxed by a bloody, abortive attack on Fort
Sanders on November 29, 1863—the Union held and occupied Knoxville for the rest of the war. During the
battle, the Hill was hit with artillery fire from Confederate guns located in a trench at the site of
UT’s present-day Sorority Village. Campus also sustained a great deal of damage caused by the Union Army.
Troops denuded the grounds of trees, ruined the steward’s house, and destroyed the gymnasium with
misdirected cannon fire aimed at Confederate troops across the river. After the Civil War ended in 1865
and the Union Army left campus, Thomas Humes was elected university president. The university reopened in
1866 and operated for six months downtown in the Deaf and Dumb Asylum while repairs began at the damaged
campus. A petition to the federal war department for monetary compensation for campus damage done by the
Union Army undoubtedly received more favorable consideration because of Humes’s known Union loyalty
throughout the war. A Senate committee which considered the bill for damages also noted that East
Tennessee University was “particularly deserving of the favorable consideration of Congress” because it
was “the only educational institution of known loyalty…in any of the seceding states.” However in 1873,
President Ulysses S. Grant vetoed the bill that would have provided $18,500 to the university because he
felt it would set a bad precedent. The bill was redrafted specifying that the payment was compensation
for aid East Tennessee University gave to the Union during the war. On June 22, 1874, President Grant
signed the new bill and the trustees accepted the funds the same day with an agreement to release the
government from all claims. (More than a century and a half later, a buried Union trench was located in
2019 on the north side of the present-day McClung Museum with the use of ground-penetrating radar.)
'''
ANSWER
Answered 2022-Feb-22 at 10:45You could use this pattern:
'\w*\d+\w*'
How does it work:
\w*
matches 0 or more characters (but not space)
\d+
matches 1 or more digits
\w*
matches 0 or more characters again
Using re
and findall we get:
re.findall('\w*\d+\w*',your_text)
we get:
['1861',
'1862',
'1862',
'1863',
'29',
'1863',
'1865',
'1866',
'1873',
'18',
'500',
'22',
'1874',
'2019']
QUESTION
I'm replacing an older cross-compile toolchain, and I can't figure out how to get buildroot to include host/.../sysroot/usr/include/boost
like the old toolchain had.
Context:
I'm trying to build a docker image that can be used to cross-compile software for MiyooCFW in GitHub Actions. Here is my current Dockerfile.
The project moved from uClibc to musl libc, which is why the toolchain needs to be updated.
The older toolchain that actually works is a .zip file on google drive. I think it was probably built using Makefile.legacy
in this buildroot fork. The newer one uses make sdk
with the main Makefile
there. (There is a bit of documentation, but it's incomplete.)
I installed libboost-all-dev
which puts the libraries in /usr/include/boost/
but just having them installed is apparently not enough.
GMenuNX is an example program I'm trying to cross-compile that depends on boost. The steward
branch uses a docker image with the older toolchain and compiles successfully. The ci
branch uses my new docker image and fails with:
/opt/miyoo/bin/arm-linux-g++ -ggdb -DTARGET_MIYOO -DTARGET=miyoo -D__BUILDTIME__="\"2022-02-19 18:33\"" -DLOG_LEVEL=3 -I/opt/miyoo/arm-buildroot-linux-musleabi/sysroot/usr/bin/../../usr/include/SDL -D_GNU_SOURCE=1 -D_REENTRANT -I/opt/miyoo/usr/include/ -I/opt/miyoo/arm-buildroot-linux-musleabi/sysroot/usr/include/ -I/opt/miyoo/arm-buildroot-linux-musleabi/sysroot/usr/include/SDL/ -o objs/miyoo/src/selector.o -c src/selector.cpp
src/selector.cpp:34:10: fatal error: boost/algorithm/string.hpp: No such file or directory
34 | #include
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [Makefile.miyoo:31: objs/miyoo/src/selector.o] Error 1
Error: Process completed with exit code 2.
I also tried copying the boost libs over manually, but that just got me a bunch of different errors.
Finally, if it wasn't apparent already, I am a complete noob when it comes to buildroot, cross compiling, etc. I don't even work with c++ very often. I's very possible that I missed something obvious.
ANSWER
Answered 2022-Feb-21 at 16:55If you want the Buildroot toolchain to include the Boost libraries, enable the Boost package in your Buildroot configuration: BR2_PACKAGE_BOOST=y. It has a number of sub-options, make sure to enable the ones that are relevant for you.
Installing Boost on your machine will have absolutely zero effect on which libraries are available in the toolchain sysroot.
QUESTION
According to (steward,1998). A matrix A which is invertible can be approximated by the formula A^{-1} = \sum^{inf}_{n=0} (I- A)^{n}
I tried implementing an algorithm to approximate a simple matrix's inverse, the loss function showed funny results. please look at the code below. more info about the Neumann series can be found here and here
here is my code.
A = np.array([[1,0,2],[3,1,-2],[-5,-1,9]])
class Neumann_inversion():
def __init__(self,A,rank):
self.A = A
self.rank = rank
self.eye = np.eye(len(A))
self.loss = []
self.loss2 =[]
self.A_hat = np.zeros((3,3),dtype = float)
#self.loss.append(np.linalg.norm(np.linalg.inv(self.A)-self.A_hat))
def approximate(self):
# self.A_hat = None
n = 0
L = (self.eye-self.A)
while n < self.rank:
self.A_hat += np.linalg.matrix_power(L,n)
loss = np.linalg.norm(np.linalg.inv(self.A) - self.A_hat)
self.loss.append(loss)
n+= 1
plt.plot(self.loss)
plt.ylabel('Loss')
plt.xlabel('rank')
# ax.axis('scaled')
return
Matrix = Neumann_inversion(A,200)
Matrix.approximate()
ANSWER
Answered 2022-Jan-28 at 09:54The formula is valid only if $A^n$ tends to zero as $n$ increase. So your matrix must satisfy
np.all(np.abs(np.linalg.eigvals(A)) < 1)
Try
Neumann_inversion(A/10, 200).approximate()
and you can take the loss seriously :)
The origin of the formula has something to do with
(1-x) * (1 + x + x^2 + ... x^n) = (1 - x^(n+1))
If, and only if, all the eigenvalues of the matrix have magnitude less than 1 the term x^(n+1) will be close to zero, so the sum will be approximately the inverse of (1-x).
QUESTION
I've done some searching on the internet but haven't be able to find an answer or solution. I'm wondering whether it is possible to apply logic within PhpMyAdmin to prevent certain users appearing in the aliases list on another table?
I have a "users" table and a "races" table. In the races table I have a column called "Steward" which is a foreign key (index) referencing the primary key of the user table. The problem is not all the users in the users table have the privilege of being a steward. Is there a way to stop the non-steward users appearing in the races table?
For further support, here's my users table:
In summary, I don't want the users who don't have the access level of "steward" in the users table appearing in the races "stewards" column of the races table.
ANSWER
Answered 2022-Jan-20 at 16:06Most developers handle this kind of business rule in application code. That is, just write your code to check a user's access_level
before inserting a row for that user in the races table.
If you need a database constraint to enforce that, you could do it this way:
- Add an index on the user table for the pair of columns
(user_id, access_level)
- Add a column
access_level
to the races table that is always 2. For example, you could do this by defining a stored virtual column that is fixed to the value 2, or by using a CHECK constraint. - Make a foreign key on the pair of columns
(race_steward, access_level)
referencing the index you created in the user table. Since theaccess_level
must match for the foreign key to be satisfied, and the value is forced to be 2 in the races table, then it can only reference users who are stewards.
QUESTION
I'm using R to work with the US county-level voting data that the good folks at MIT steward. I'd like to know the total votes each candidate got in each county. For some states, such as Wisconsin, that's easy:
"state", "county_name", "county_fips", "candidate", "party", "candidatevotes", "totalvotes", "mode"
"WISCONSIN", "WINNEBAGO", "55139", "JO JORGENSEN", "LIBERTARIAN", 1629, 94032, "TOTAL"
For other states, such as Utah, it's doable:
"UTAH", "WEBER", "49057", "DONALD J TRUMP", "REPUBLICAN", 0, 111403, "EARLY"
"UTAH", "WEBER", "49057", "DONALD J TRUMP", "REPUBLICAN", 0, 111403, "ELECTION DAY"
"UTAH", "WEBER", "49057", "DONALD J TRUMP", "REPUBLICAN", 0, 111403, "MAIL"
"UTAH", "WEBER", "49057", "DONALD J TRUMP", "REPUBLICAN", 65949, 111403, "TOTAL"
South Carolina, however, is problematic:
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 13656, 144050, "ABSENTEE BY MAIL"
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 22075, 144050, "ELECTION DAY"
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 18, 144050, "FAILSAFE"
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 176, 144050, "FAILSAFE PROVISIONAL"
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 22950, 144050, "IN-PERSON ABSENTEE"
"SOUTH CAROLINA", "YORK", "45091", "JOSEPH R BIDEN JR", "DEMOCRAT", 133, 144050, "PROVISIONAL"
It seems to me that there should be some way to loop over the FIPS codes and the party name to generate the totals for each county, but I'm stumped.
ANSWER
Answered 2022-Jan-20 at 03:15Does this solve your problem?
library(tidyverse)
df <- read_csv("~/Desktop/countypres_2000-2020.csv")
#> Rows: 72617 Columns: 12
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (8): state, state_po, county_name, county_fips, office, candidate, party...
#> dbl (4): year, candidatevotes, totalvotes, version
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
df %>%
filter(year == 2020) %>%
group_by(candidate, county_fips) %>%
summarise(
county_name,
total_votes_per_candidate_per_county = sum(candidatevotes)
) %>%
relocate(candidate, .before = 4) %>%
distinct() %>%
arrange(county_fips)
#> `summarise()` has grouped output by 'candidate', 'county_fips'. You can override using the `.groups` argument.
#> # A tibble: 11,902 × 4
#> # Groups: candidate, county_fips [11,898]
#> county_fips county_name candidate total_votes_per_candidate_per_coun…
#>
#> 1 01001 AUTAUGA DONALD J TRUMP 19838
#> 2 01001 AUTAUGA JOSEPH R BIDEN JR 7503
#> 3 01001 AUTAUGA OTHER 429
#> 4 01003 BALDWIN DONALD J TRUMP 83544
#> 5 01003 BALDWIN JOSEPH R BIDEN JR 24578
#> 6 01003 BALDWIN OTHER 1557
#> 7 01005 BARBOUR DONALD J TRUMP 5622
#> 8 01005 BARBOUR JOSEPH R BIDEN JR 4816
#> 9 01005 BARBOUR OTHER 80
#> 10 01007 BIBB DONALD J TRUMP 7525
#> # … with 11,892 more rows
Created on 2022-01-20 by the reprex package (v2.0.1)
QUESTION
Attempted Solution at bottom of post.
I have near-working code that extracts the sentence containing a phrase, across multiple lines.
However, some pages have columns. So respective outputs are incorrect; where separate texts are wrongly merged together as a bad sentence.
This problem has been addressed in the following posts:
Question:
How do I "if-condition" whether there are columns?
- Pages may not have columns,
- Pages may have more than 2 columns.
- Pages may also have headers and footers (that can be left out).
Example .pdf
with dynamic text layout: PDF (pg. 2).
Jupyter Notebook:
# pip install PyPDF2
# pip install pdfplumber
# ---
import pdfplumber
# ---
def scrape_sentence(phrase, lines, index):
# -- Gather sentence 'phrase' occurs in --
sentence = lines[index]
print("-- sentence --", sentence)
print("len(lines)", len(lines))
# Previous lines
pre_i, flag = index, 0
while flag == 0:
pre_i -= 1
if pre_i <= 0:
break
sentence = lines[pre_i] + sentence
if '.' in lines[pre_i] or '!' in lines[pre_i] or '?' in lines[pre_i] or ' • ' in lines[pre_i]:
flag == 1
print("\n", sentence)
# Following lines
post_i, flag = index, 0
while flag == 0:
post_i += 1
if post_i >= len(lines):
break
sentence = sentence + lines[post_i]
if '.' in lines[post_i] or '!' in lines[post_i] or '?' in lines[post_i] or ' • ' in lines[pre_i]:
flag == 1
print("\n", sentence)
# -- Extract --
sentence = sentence.replace('!', '.')
sentence = sentence.replace('?', '.')
sentence = sentence.split('.')
sentence = [s for s in sentence if phrase in s]
print(sentence)
sentence = sentence[0].replace('\n', '').strip() # first occurance
print(sentence)
return sentence
# ---
phrase = 'Gulf Petrochemical Industries Company'
with pdfplumber.open('GPIC_Sustainability_Report_2016-v9_(lr).pdf') as opened_pdf:
for page in opened_pdf.pages:
text = page.extract_text()
if text == None:
continue
lines = text.split('\n')
i = 0
sentence = ''
while i < len(lines):
if phrase in lines[i]:
sentence = scrape_sentence(phrase, lines, i)
i += 1
Example Incorrect Output:
-- sentence -- being a major manufacturer within the kingdom of In 2012, Gulf Petrochemical Industries Company becomes part of
len(lines) 47
Company (GPIC)gulf petrochemical industries company (gpic) is a leading joint venture setup and owned by the government of the kingdom of bahrain, saudi basic industries corporation (sabic), kingdom of saudi arabia and petrochemical industries company (pic), kuwait. gpic was set up for the purposes of manufacturing fertilizers and petrochemicals. being a major manufacturer within the kingdom of In 2012, Gulf Petrochemical Industries Company becomes part of
Company (GPIC)gulf petrochemical industries company (gpic) is a leading joint venture setup and owned by the government of the kingdom of bahrain, saudi basic industries corporation (sabic), kingdom of saudi arabia and petrochemical industries company (pic), kuwait. gpic was set up for the purposes of manufacturing fertilizers and petrochemicals. being a major manufacturer within the kingdom of In 2012, Gulf Petrochemical Industries Company becomes part of the global transformation for a sustainable future by committing to bahrain, gpic is also a proactive stakeholder within the United Nations Global Compact’s ten principles in the realms the kingdom and the region with our activities being of Human Rights, Labour, Environment and Anti-Corruption. represented by natural gas purchases, empowering bahraini nationals through training & employment, utilisation of local contractors and suppliers, energy consumption and other financial, commercial, environmental and social activities that arise as a part of our core operations within the kingdom.GPIC becomes an organizational stakeholder of Global Reporting for the purpose of clarity throughout this report, Initiative ( GRI) in 2014. By supporting GRI, Organizational ‘gpic’, ’we’ ‘us’, and ‘our’ refer to the gulf Stakeholders (OS) like GPIC, demonstrate their commitment to transparency, accountability and sustainability to a worldwide petrochemical industries company; ‘sabic’ refers to network of multi-stakeholders.the saudi basic industries corporation; ‘pic’ refers to the petrochemical industries company, kuwait; ‘nogaholding’ refers to the oil and gas holding company, kingdom of bahrain; and ‘board’ refers to our board of directors represented by a group formed by nogaholding, sabic and pic.the oil and gas holding company (nogaholding) is GPIC is a Responsible Care Company certified for RC 14001 since July 2010. We are committed to the safe, ethical and the business and investment arm of noga (national environmentally sound management of the petrochemicals oil and gas authority) and steward of the bahrain and fertilizers we make and export. Stakeholders’ well-being is government’s investment in the bahrain petroleum always a key priority at GPIC.company (bapco), the bahrain national gas company (banagas), the bahrain national gas expansion company (bngec), the bahrain aviation fuelling company (bafco), the bahrain lube base oil company, the gulf petrochemical industries company (gpic), and tatweer petroleum.GPIC SuStaInabIlIty RePoRt 2016 01ii GPIC SuStaInabIlIty RePoRt 2016 GPIC SuStaInabIlIty RePoRt 2016 01
[' being a major manufacturer within the kingdom of In 2012, Gulf Petrochemical Industries Company becomes part of the global transformation for a sustainable future by committing to bahrain, gpic is also a proactive stakeholder within the United Nations Global Compact’s ten principles in the realms the kingdom and the region with our activities being of Human Rights, Labour, Environment and Anti-Corruption']
being a major manufacturer within the kingdom of In 2012, Gulf Petrochemical Industries Company becomes part of the global transformation for a sustainable future by committing to bahrain, gpic is also a proactive stakeholder within the United Nations Global Compact’s ten principles in the realms the kingdom and the region with our activities being of Human Rights, Labour, Environment and Anti-Corruption
...
Attempted Minimal Solution: This will separate text into 2 columns; regardless if there are 2.
# pip install PyPDF2
# pip install pdfplumber
# ---
import pdfplumber
import decimal
# ---
with pdfplumber.open('GPIC_Sustainability_Report_2016-v9_(lr).pdf') as opened_pdf:
for page in opened_pdf.pages:
left = page.crop((0, 0, decimal.Decimal(0.5) * page.width, decimal.Decimal(0.9) * page.height))
right = page.crop((decimal.Decimal(0.5) * page.width, 0, page.width, page.height))
l_text = left.extract_text()
r_text = right.extract_text()
print("\n -- l_text --", l_text)
print("\n -- r_text --", r_text)
text = str(l_text) + " " + str(r_text)
Please let me know if there is anything else I should clarify.
ANSWER
Answered 2021-Dec-01 at 16:01This answer enables you to scrape text, in the intended order.
Towards Data Science article PDF Text Extraction in Python:
Compared with PyPDF2, PDFMiner’s scope is much more limited, it really focuses only on extracting the text from the source information of a pdf file.
from io import StringIO
from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
from pdfminer.pdfpage import PDFPage
def convert_pdf_to_string(file_path):
output_string = StringIO()
with open(file_path, 'rb') as in_file:
parser = PDFParser(in_file)
doc = PDFDocument(parser)
rsrcmgr = PDFResourceManager()
device = TextConverter(rsrcmgr, output_string, laparams=LAParams())
interpreter = PDFPageInterpreter(rsrcmgr, device)
for page in PDFPage.create_pages(doc):
interpreter.process_page(page)
return(output_string.getvalue())
file_path = '' # !
text = convert_pdf_to_string(file_path)
print(text)
Cleansing can be applied thereafter.
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