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Disclaimer:
These pages about different languages / apis / best practices were mostly jotted down quckily and rarely corrected afterwards. The languages / apis / best practices may have changed over time (e.g. the facebook api being a prime example), so what was documented as a good way to do something at the time might be outdated when you read it (some pages here are over 15 years old). Just as a reminder. Howto for using py2app on MacOsXDeveloper notes for how to use it and common installation problemsPy2app, how to use it on macosxInstallation of py2appIt already exist in Snow Leopard and later (not sure about before) , inSo normally no need to install it on Macosx. If you need to install it: Download the latest py2app Install it from source: Possible problemsAttributeError: 'NoneType' object has no attribute 'get_config_var'Solution: ? Cant recall the error message, but if it complains about argv emulation when trying to execute the app Set it to false in setup.py: 'argv_emulation': False
Links to relevant websitespy2app, MacPorts, Snow Leopard, and PIL: a match made in HellHow to make standalone OS X application bundles from PyQt apps using py2app Usage examples of py2appIncluding extra files (e.g. images)Edit setup.py to include the extra files in DATA_FILES Alternatives to py2appPlatypus, "Platypus is a developer tool for the Mac OS X operating system. It creates native Mac OS X applications from interpreted scripts such as shell scripts or Perl, Ruby and Python programs. This is done by wrapping the script in an application bundle along with a native executable binary that runs the script."Reload modulefrom importlib import reload # Python 3.4+ only. import foo foo = reload(foo)Python general notes#add a path so python will find modules in it from the code import sys sys.path.append("colaboratory_helpers")installing pgdb with mac portsMake sure you have the macports pip (and not the default one) sudo port install py27-pip install with pip: pip-2.7 install PyGreSQL If pg_config tool is not available: Make sure the postgres bin is in the path, e.g. export PATH=/usr/local/pgsql91/bin/:$PATH Timeout when waiting for user input
# Expect the user to type something
# if he does not type something within 5 seconds the script complains
import sys, signal
Timeout = 'Timeout exception.'
def timed_out(signo, frame):
raise Timeout
signal.signal(signal.SIGALRM, timed_out)
print "write something! "
buf = ''
try:
signal.alarm(5)
buf = sys.stdin.readline()
signal.alarm(0)
except Timeout:
print "\a----Are you still there?"
if buf:
print "Received: ", buf
Dump a dictionary
(to avoid "too many values to unpack" problem)
for field, possible_values in fields.iteritems():
print field, possible_values
Check syntax without executingpython -m py_compileConvert int to string and vice versa
str(42)
int('42')
Save image dlib
from skimage import io
io.imsave("somedir/{}_{}.jpg".format(itemid, idx), faces[0])
Save filefh = open("/tmp/somefile.txt", "w") fh.write("stuff") fh.close()Find methods of instance, parameters for functionimport inspect inspect.getargspec(flann.nn_index) dir(flann) Find out which version of package torch.__version__botoSending/Receiveing msgs to SQS automatically decode/encode base64jupyter notebook%matplotlib inline df.Age.plot(kind='hist')Pandasdf = pd.read_csv(filename, header=None, names=['Objectid', 'Name']) #iterate over df for index, row in df.iterrows(): print(row['c1']) df.dtypes df.Sex.value_counts() df.Sex.describe() #number of missing values for each attribute df.isnull().sum() #Select columsn to use df1 = df[['a','d']] #Drop column inplace df.drop('Colname', axis=1, inplace=True) #Drop duplicates based on column df.drop_duplicates(subset='Columnname', keep="first", inplace=True) #Drop rows if it exist in another dataframe https://stackoverflow.com/questions/60956063/remove-a-row-from-a-dataframe-if-any-row-value-is-in-another-dataframe df21k[~df21k['word'].isin(dfToRemove['word'].values.flatten())] #Fill missing values df.fillna('', inplace=True) #Selecting df[ df['ThisIsAcolumn'] == '9' ].head(5) #Change value of a column oldval = tmpdf['label'].values dfall.loc[ dfall['objectid'] == row['objectid'], 'label' ] = oldval[0] + "," + currentlabel #Change type of columns newdf = newdf.apply(pd.to_numeric) df['B'] = pd.to_numeric(df['B']) df['points'] = df['points'].astype(str) #convert column to int df['Weight'] = df['Weight'].astype(int) #Getting values dfAUto[ dfAUto['word'] == 'car' ]['suggestion'].values[0] # See if a value exist in a frame if 0 < len(df[ df['keyword'] == 'something' ].values): # Apply function df['ratio'] = df['stuff'].apply(lambda x: x / len(df.index)) #Selecting based on the index df['itemid'].iloc[3] #Selecting with regex, all rows where the MYCOL is not digits only df[ df.MYCOL.str.contains('^[^0-9]+$', regex=True, na=False) ] #Rename columns df.rename(columns={'How Many People': 'new_col_name'}, inplace=True) #Export specific columns, leaving out index header = ["somecol", "other_col", "blabablalbal"] merged2.to_csv('/tmp/output.csv', columns = header, sep='|', index=False) #Merging on a specific column df = pd.merge(df_new, df_n, on='subject_id') #Concatting two dataframes df = pd.concat([dfa,dfb]) #After concatting, reset index df.reset_index(drop=True, inplace=True) #Randomize dataframe df = df.sample(frac=1).reset_index(drop=True) #Assign result of groupby to new column dfsnow['TaxsumTotal'] = dfsnow['Taxsum'].groupby(dfsnow['Keyword']).transform('sum') https://mycheatsheets.com/pandas http://www.swegler.com/becky/blog/2014/08/06/useful-pandas-snippets/ #Dummy frame for quick copyNpaste import pandas as pd df = pd.DataFrame({'num_legs': [2, 4, 8, 0], 'num_wings': [2, 0, 0, 0], 'num_specimen_seen': [10, 2, 1, 8]}, index=['falcon', 'dog', 'spider', 'fish']) df = pd.DataFrame({'phrase': ['dog','cat','dolphin'])More programming related pages |
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