Test locally. Add additional libraries iteratively to find the right combination of packages and their versions, before creating a requirements.txt file. To run the Amazon MWAA CLI utility, see the aws-mwaa-local-runner on GitHub.
Review the Apache Airflow package extras. For example, the core extras,provider extras,locally installed software extras,external service extras,"other" extras,bundle extras,doc extras, andsoftware extras have changed.To view a list of the packages installed for Apache Airflow v2 on Amazon MWAA, seeAmazon MWAA local runner requirements.txt on the GitHub website.
Add the constraints file. Add the constraints file for your Apache Airflow v2 environment to the top of your requirements.txt file. If the constraints file determines that xyz==1.0 package is not compatible with other packages on your environment, the pip3 install will fail to prevent incompatible libraries from being installed to your environment. In the following example, replace Airflow-version with your environment's version number, and Python-version with the version of Python that's compatible with your environment.
This example is provided for demonstration purposes. The boto and psycopg2-binary libraries are included with the Apache Airflow v2 base install and don't need to be specified in a requirements.txt file.
Add the constraints file. Add the constraints file for Apache Airflow v1.10.12 to the top of your requirements.txt file. If the constraints file determines that xyz==1.0 package is not compatible with other packages on your environment, the pip3 install will fail to prevent incompatible libraries from being installed to your environment.
The Apache Airflow scheduler, workers, and web server (for Apache Airflow v2.2.2 and later) look for custom plugins during startup on the AWS-managed Fargate container for your environment at/usr/local/airflow/plugins/*. This process begins prior to Amazon MWAA's pip3 install -r requirements.txt for Python dependencies and Apache Airflow service startup.A plugins.zip file be used for any files that you don't want continuously changed during environment execution, or that you may not want to grant access to users that write DAGs.For example, Python library wheel files, certificate PEM files, and configuration YAML files.
Download the necessary WHL files You can use pip download with your existing requirements.txt on the Amazon MWAA local-runner or another Amazon Linux 2 container to resolve and download the necessary Python wheel files.
Specify the path in your requirements.txt. Specify the plugins directory at the top of your requirements.txt using --find-links and instruct pip not to install from other sources using --no-index, as shown in the following
After running the DAG, use this new file as your Amazon MWAA plugins.zip, optionally, packaged with other plugins. Then, update your requirements.txt preceeded by --find-links /usr/local/airflow/plugins and --no-index without adding --constraint.
Create your requirements.txt file. Substitute the placeholders in the following example with your private URL, and the username and password you've added as Apache Airflow configuration options. For example:
You can enable Apache Airflow logs at the INFO, WARNING, ERROR, or CRITICAL level. When you choose a log level, Amazon MWAA sends logs for that level and all higher levels of severity. For example, if you enable logs at the INFO level, Amazon MWAA sends INFO logs and WARNING, ERROR, and CRITICAL log levels to CloudWatch Logs. We recommend enabling Apache Airflow logs at the INFO level for the Scheduler to view logs received for the requirements.txt.
My current setup isn't working properly, because adding to the Google Webmasters wouldn't work (because TXT record for the www subdomain doesn't exist), and adding (non-www version) will work (the TXT record for this subdomain exists), but this way Google Webmasters won't be able to read both sitemap.txt and robots.txt (because they both redirect to the www version of the site). The same story with Yandex.Metrika.
Example pages containing:tips resources functions/proceduresNCL: Reading ASCII dataThis document shows how to read various types of ASCII files using NCL.For examples of reading or writing other types of ASCII files, see:Reading CSV filesWriting ASCII filesWriting CSV filesHere are a list of functions that are useful for reading various typesof ASCII files:asciiread - reads a file that contains ASCIIrepresentations of basic data types.str_fields_count - Count thenumber of fields in a string, given a delimiter.str_get_cols - Retrieve a particularcolumn in a string, given a start and end index.str_get_field - Retrieve a particularfield in a string, given a delimiter.str_split_csv - Splits strings into an array ofstrings based on a single delimiter.str_sub_str - Replace a substring withanother substring.readAsciiHead - reads anASCII file and returns just the header.numAsciiCol - returns thenumber of columns in an ASCII file.numAsciiRow - returns thenumber of rows in an ASCII file.Unix "cut"command - allows you easily extract sections from a file.Here are the various ASCII files used by the examples on this page.asc1.txt - a very simplefile with 14 integers, one per line. (example)asc2.txt - a file with a header line,followed by 2 columns of integer and floating point data.(example)asc3.txt - a file with several columnsof integer, float, and string data.(example)asc4.txt - a file containingpopulation of cities, with some header and footer lines, and a mix ofnumeric data. The headers contain some numbers, and some of thenumeric data contain commas. The columns are separated by tabs.(example)asc5.txt - a file where the firstrow contains the name of each field separated by a delimiter, and therest of the file contains the values of each field separated by thesame delimiter.(example)string1.txt -a file containing lines of a poem (no numeric data).(example)pw.dat - a file with a header andfour columns of lined-up numeric and non-numeric data. The "ID" columnis non-numeric, but it does contain numbers as part of the the IDnames.(example)asc6.txt - a file with a header, and three columns of floating point data (lat, lon, temp).(example)stn_latlon.dat - a file with 980rows and 10 columns of floating point data.(example)istasyontablosu_son.txt- a mix of numeric and non-numeric data in columns that are not linedup nicely.(example)cygnss_test.txt - a file with an indeterminant number of headers that start with "%",followed by a single number containing a row count, followed bythat many rows of data with 9 columns each.(example)L3_aiavg_n7t_197901.txt- a file with a mix of text, integers, and floats and no delimiters.(example)NCDC.Central_Iowa.1895-2016.txt- a file with a mix of text, integers, and floats and no delimiters.This file was downloaded from the National Centers for Environmental Information (NCEI)which was previously known as the National Climatic Data Center (NCDC). Specifically, this file was downloaded via the Climate data division selection tool.(example)reading multiple ASCII files into one NCL variableasc1.txt - a file with14 integers, one per line.; Read data into a one-dimensional int array of length 14: data = asciiread("asc1.txt",14,"integer") npts = dimsizes(data) ; should be 14 print(data) ; Print the valuesIf you don't know how many data values you have, you can use thespecial "-1" value for the dimension size. When you use -1, datavalues will be read from left-to-right, top-to-bottom, into a 1Darray, until there are no values left.; Read data into a one-dimensional array of unknown length: data = asciiread("asc1.txt",-1,"integer") npts = dimsizes(data) ; should be 14string1.txt - a filewith no numerical data, just lines from a poem.Use the special -1 value again, and a type of "string" to read in eachline. When you read strings, each line in the file will be consideredone string, regardless if it contains spaces, tabs, or any other kindof white space.; Read poem into a one-dimensional string array of unknown length: filename = "string1.txt" poem = asciiread(filename,-1,"string") nlines = dimsizes(poem) print("The poem in '" + filename + "' has " + nlines + " lines.") print("This includes the title and the author.") print(poem) ; Print the linesasc2.txt - a file with a header line,followed by 2 columns of integer and floating point data.Even though this file contains multiple columns of data, when you usethe special "-1" value as a dimension size, the values will be readinto a one-dimensional array. The values will be read from from top tobottom, left to right.In this file, the header line will be ignored because it doesn'tcontain any numerical data. data = asciiread("asc2.txt",-1,"float") print(data) ; Print the valuesTo read this data into a 2D array dimensioned 17 x 2 (17 rows by 2 columns), use: data = asciiread("asc2.txt",(/17,2/),"float") print(data) ; Print the valuesstn_latlon.dat - a file with 980rows and 10 columns of floating point data.The first two methods show how to read this file if you know the exactnumber of rows and columns, and the third method shows how to readthis file if you don't.Method 1; Read data into a 980 x 10 float array. nrows = 980 ncols = 10 data = asciiread("stn_latlon.dat",(/nrows,ncols/),"float") printVarSummary(data) ; Print information about file only.; Two ways to print the data. print(data) ; Print data, one value per line write_matrix(data,ncols + "f7.2",0) ; Formatted outputMethod 2This file is actually a file of latitude and longitude values, eachdimensioned 70 x 70. The latitude values are written first on thefile, followed by the longitude values. Given this information, here'sanother way to read in this file: nlat = 70 nlon = 70 latlon2d = asciiread("stn_latlon.dat",(/2,nlat,nlon/),"float") ; 2 x 70 x 70 lat2d = latlon2d(0,:,:) ; 70 x 70 lon2d = latlon2d(1,:,:) ; 70 x 70Method 3Use the special contributedfunctions numAsciiCol andreadAsciiTable function to firstcalculate the number of columns, and then to read the data into anarray dimensioned nrows x ncols.load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl" ; This library is automatically loaded ; from NCL V6.2.0 onward. ; No need for user to explicitly load. filename = "stn_latlon.dat"; Calculate the number of columns. ncols = numAsciiCol(filename); Given the # of columns, we can use readAsciiTable to read this file. data = readAsciiTable(filename,ncols,"float",0) nrows = dimsizes(data(:,0)) ; calculate # of rows print("'" + filename + "' has " + nrows + " rows and " + ncols + \ " columns of data.")pw.dat - a file with a header lineand four columns of lined-up numeric and non-numeric data. The"ID" column is non-numeric, but it does contain numbers as part of thethe ID names.We need to parse out this first column so these numeric values don'tget mixed in with our real data.Note that as of version5.1.1, this kind of thing is much easier usingthe str_get_field function, which we'll demonstratefirst.New method, version 5.1.1 and later; Read data into a big 1D string array fname = "Data/asc/pw.dat" data = asciiread(fname,-1,"string"); Count the number of fields, just to show it can be done. nfields = str_fields_count(data(1)," ") print("number of fields = " + nfields);; Skip first row of "data" because it's just a header line.;; Use a space (" ") as a delimiter in str_get_field. The first; field is field=1 (unlike str_get_cols, in which the first column; is column=0).; lat = stringtofloat(str_get_field(data(1::), 2," ")) lon = stringtofloat(str_get_field(data(1::), 3," ")) pwv = stringtofloat(str_get_field(data(1::), 4," "))Old method, before version 5.1.1The following example will only work if your columns are lined up nicely.; Read data into a big 1D string array, and convert to a character array. data = asciiread("./pw.dat", -1, "string") cdata = stringtochar(data);; The first row is just a header, so we can discard this. ; The data starts in the second row, which is represented ; by index 1. ; ; The latitude values fall in columns 6-12 (indices 7:13) ; The longitude values fall in columns 13-21 (indices 14:22) ; The pwv data values fall in columns 22-31 (indices 23:end);; The "1:,"means start with the second row, and include all; values to the end.; lat = stringtofloat(charactertostring(cdata(1:,7:13))) lon = stringtofloat(charactertostring(cdata(1:,14:22))) pwv = stringtofloat(charactertostring(cdata(1:,23:)))This file can also be read by using a combination of the NCLsystemfunc function, and the Unix "cut"command. Again, however, the data must be lined up nicely. With"cut", the first character is considered to be column 1 (and not 0).Another old method, before version 5.1.1 fname = "pw.dat" clat = systemfunc("cut -c7-13 " + fname) clon = systemfunc("cut -c14-22 " + fname) cpw = systemfunc("cut -c23-31 " + fname) ; Ignore the first value, since this is just a header. lat = stringtofloat(clat(1:)) lon = stringtofloat(clon(1:)) pwv = stringtofloat(cpw(1:))asc3.txt - a file with severalcolumns of integer, float, and string data.The first column contains date values like "200306130209", which wewant to parse into separate year, month, day, hour, and minute arrays.We also want to read the third-from-the-last column, which are thestation names. We will again use the Unix "cut" command in orderto do this kind of parsing.Note that as of version5.1.1, this kind of thing is much easier usingthe str_get_cols function, which we'll demonstratefirst.New method, version 5.1.1 and later fname = "asc3.txt" data = asciiread(fname,-1,"string") year = stringtofloat(str_get_cols(data, 1,4)) month = stringtofloat(str_get_cols(data,5,6)) day = stringtofloat(str_get_cols(data,7,8)) hour = stringtofloat(str_get_cols(data,9,10)) minute = stringtofloat(str_get_cols(data,11,12)) sta = str_get_cols(data,100,102)Old method, before version 5.1.1 fname = "asc3.txt" year = stringtofloat(systemfunc("cut -c1-4 " + fname)) month = stringtofloat(systemfunc("cut -c5-6 " + fname)) day = stringtofloat(systemfunc("cut -c7-8 " + fname)) hour = stringtofloat(systemfunc("cut -c9-10 " + fname)) minute = stringtofloat(systemfunc("cut -c11-12 " + fname)) sta = systemfunc("cut -c100-102 " + fname)Note: you cannot use stringtointeger to convertnumbers like "09" to "9", because the preceding "0" causes NCL totreat the number as an octal value and "9" is not a valid octalvalue.istasyontablosu_son.txt -a mix of numeric and non-numeric data in columns that are not lined upnicely.This file is pretty easy to read, because the non-numeric columnsdon't have a mix of alpha and numeric characters. Here's a script toread the first, fifth, and sixth columns (latitude, longitude, andstation numbers) into separate variables: stationfile="istasyontablosu_son.txt"; Read all data into a one-dimensional variable. dummy = asciiread(stationfile,-1,"float") ncol = 6 ; # of columns npts = dimsizes(dummy)/ncol ; # of points stationdata = onedtond(dummy,(/npts,ncol/)) ; npts x ncol stn = stationdata(:,0) ; station numbers lat = stationdata(:,4) ; latitude values lon = stationdata(:,5) ; longitude values; Print the mins/maxs just to verify the data looks correct. print("min/max stn = " + min(stn) + "/" + max(stn)) print("min/max lat = " + min(lat) + "/" + max(lat)) print("min/max lon = " + min(lon) + "/" + max(lon))As of version 5.1.1, you canread fields from this file using str_get_field.; Read all data into a one-dimensional variable. stationfile = "istasyontablosu_son.txt" data = asciiread(stationfile,-1,"string"); Count the number of fields, just to show it can be done. nfields = str_fields_count(data(0)," ") print("number of fields = " + nfields) stn = stringtofloat(str_get_field(data,1," "))) ; station numbers lat = stringtofloat(str_get_field(data,6," ")) ; latitude values lon = stringtofloat(str_get_field(data,7," ")) ; longitude values; Print the mins/maxs just to verify the data looks correct. print("min/max stn = " + min(stn) + "/" + max(stn)) print("min/max lat = " + min(lat) + "/" + max(lat)) print("min/max lon = " + min(lon) + "/" + max(lon))cygnss_test.txt - a file with an indeterminant number of headers that start with "%",followed by a single number containing a row count, followed bythat many rows of data with 9 columns each.The original version of file had over a million lines of data, andseveral blocks of headers and data. This sample file only has oneblock of headers and data. The script below will handle either. To seean example that plots this data, see example #17 onthe primitives page.When reading large blocks of data that are nicely formatted into rowsand columns, it is best to use str_split_csv,rather than parsing one line at a timewith str_split or str_get_field.str_split_csv requires that each column beseparated by a single character delimiter,so str_sub_str is used to replace multiple spaceswith just one space. lines = asciiread("cygnss_test.txt",-1,"string") nlines = dimsizes(lines) ncols = 9 nl = 0 ; line counter do while(nl.lt.nlines);---Read the first character of this line first = str_get_cols(lines(nl),0,0);---If it's a "%", then increment to next line. if(first.eq."%") then nl = nl + 1 ; increment line counter continue else;---Otherwise, get the number of rows and read the data. nrows = toint(lines(nl)) nl = nl + 1 ; increment line counter print("==================================================") print("Reading " + nrows + " rows of data.");; Clean up the strings so there's only one space between; each string, and no extra space at beginning or end.; This allows us to use str_split_csv to parse this; chunk of data. str_split_csv expects a single character; delimiter (a space in this case).; lines(nl:nl+nrows-1) = str_sub_str(lines(nl:nl+nrows-1)," "," ") li