diff --git "a/corpus.jsonl" "b/corpus.jsonl"
--- "a/corpus.jsonl"
+++ "b/corpus.jsonl"
@@ -10,7 +10,7 @@
{"_id": 9, "title": "", "text": "[`DataFrame.iterrows`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iterrows.html#pandas-dataframe-iterrows) is a generator which yields both the index and row (as a Series):
```python
import pandas as pd
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
df = df.reset_index() # make sure indexes pair with number of rows
for index, row in df.iterrows():
print(row['c1'], row['c2'])
```
```python
10 100
11 110
12 120
```"}
{"_id": 10, "title": "", "text": "```python
import pandas as pd
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
df = df.reset_index() # make sure indexes pair with number of rows
for index, row in df.iterrows():
print(row['c1'], row['c2'])
```"}
{"_id": 11, "title": "", "text": "Iteration
The behavior of basic iteration over pandas objects depends on the type. When iterating over a Series, it is regarded as array-like, and basic iteration produces the values. DataFrames follow the dict-like convention of iterating over the “keys” of the objects.
In short, basic iteration (for i in object) produces:
Series: values
DataFrame: column labels
pandas objects also have the dict-like items() method to iterate over the (key, value) pairs.
To iterate over the rows of a DataFrame, you can use the following methods:
iterrows(): Iterate over the rows of a DataFrame as (index, Series) pairs. This converts the rows to Series objects, which can change the dtypes and has some performance implications.
itertuples(): Iterate over the rows of a DataFrame as namedtuples of the values. This is a lot faster than iterrows(), and is in most cases preferable to use to iterate over the values of a DataFrame.
Warning
Iterating through pandas objects is generally slow. In many cases, iterating manually over the rows is not needed and can be avoided with one of the following approaches:
Look for a vectorized solution: many operations can be performed using built-in methods or NumPy functions, (boolean) indexing, …
When you have a function that cannot work on the full DataFrame/Series at once, it is better to use apply() instead of iterating over the values. See the docs on function application.
If you need to do iterative manipulations on the values but performance is important, consider writing the inner loop with cython or numba. See the enhancing performance section for some examples of this approach.
Warning
You should never modify something you are iterating over. This is not guaranteed to work in all cases. Depending on the data types, the iterator returns a copy and not a view, and writing to it will have no effect!"}
-{"_id": 12, "title": "", "text": "You can use a global variable within other functions by declaring it as `global` **within each function that assigns a value to it**:
```python
globvar = 0
def set_globvar_to_one():
global globvar # Needed to modify global copy of globvar
globvar = 1
def print_globvar():
print(globvar) # No need for global declaration to read value of globvar
set_globvar_to_one()
print_globvar() # Prints 1
```
Since it's unclear whether `globvar = 1` is creating a local variable or changing a global variable, Python defaults to creating a local variable, and makes you explicitly choose the other behavior with the `global` keyword.
See other answers if you want to share a global variable across modules."}
+{"_id": 12, "title": "", "text": "You can use a global variable within other functions by declaring it as `global` **within each function that assigns a value to it**:
```python
globvar = 0
def set_globvar_to_one():
global globvar # Needed to modify global copy of globvar
globvar = 1
def print_globvar():
print(globvar) # No need for global declaration to read value of globvar
set_globvar_to_one()
print_globvar() # Prints 1
```
Since it's unclear whether `globvar = 1` is creating a local variable or changing a global variable, Python defaults to creating a local variable, and makes you explicitly choose the other behavior with the `global` keyword.
See other answers if you want to share a global variable across modules.
"}
{"_id": 13, "title": "", "text": "```python
globvar = 0
def set_globvar_to_one():
global globvar # Needed to modify global copy of globvar
globvar = 1
def print_globvar():
print(globvar) # No need for global declaration to read value of globvar
set_globvar_to_one()
print_globvar() # Prints 1
```"}
{"_id": 14, "title": "", "text": "7.12. The global statement
global_stmt ::= \"global\" identifier (\",\" identifier)*
The global statement is a declaration which holds for the entire current code block. It means that the listed identifiers are to be interpreted as globals. It would be impossible to assign to a global variable without global, although free variables may refer to globals without being declared global.
Names listed in a global statement must not be used in the same code block textually preceding that global statement.
Names listed in a global statement must not be defined as formal parameters, or as targets in with statements or except clauses, or in a for target list, class definition, function definition, import statement, or variable annotation.
CPython implementation detail: The current implementation does not enforce some of these restrictions, but programs should not abuse this freedom, as future implementations may enforce them or silently change the meaning of the program.
Programmer’s note: global is a directive to the parser. It applies only to code parsed at the same time as the global statement. In particular, a global statement contained in a string or code object supplied to the built-in exec() function does not affect the code block containing the function call, and code contained in such a string is unaffected by global statements in the code containing the function call. The same applies to the eval() and compile() functions."}
{"_id": 15, "title": "", "text": "[Decode the `bytes` object](https://docs.python.org/3/library/stdtypes.html#bytes.decode) to produce a string:
```python
>>> b\"abcde\".decode(\"utf-8\")
'abcde'
```
The above example *assumes* that the `bytes` object is in UTF-8, because it is a common encoding. However, you should use the encoding your data is actually in!"}
@@ -71,7 +71,7 @@
{"_id": 70, "title": "", "text": "```python
df = df.drop('column_name', axis=1)
```"}
{"_id": 71, "title": "", "text": "# pandas.DataFrame.drop
**DataFrame.drop(*labels=None*, ***, *axis=0*, *index=None*, *columns=None*, *level=None*, *inplace=False*, *errors='raise'*)[[source]](https://github.com/pandas-dev/pandas/blob/v2.2.2/pandas/core/frame.py#L5433-L5589)**Drop specified labels from rows or columns.
Remove rows or columns by specifying label names and corresponding axis, or by directly specifying index or column names. When using a multi-index, labels on different levels can be removed by specifying the level. See the [user guide](https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced-shown-levels) for more information about the now unused levels."}
{"_id": 72, "title": "", "text": "Use [`Counter`](https://docs.python.org/3/library/collections.html#collections.Counter) if you are using Python 2.7 or 3.x and you want the number of occurrences for each element:
```python
>>> from collections import Counter
>>> z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> Counter(z)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
```"}
-{"_id": 73, "title": "", "text": "```python
>>> from collections import Counter
>>> z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> Counter(z)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
```"}
+{"_id": 73, "title": "", "text": "
```python
>>> from collections import Counter
>>> z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> Counter(z)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
```"}
{"_id": 74, "title": "", "text": "*class* collections.**Counter**([*iterable-or-mapping*])
A [`Counter`](https://docs.python.org/3/library/collections.html#collections.Counter) is a [`dict`](https://docs.python.org/3/library/stdtypes.html#dict) subclass for counting [hashable](https://docs.python.org/3/glossary.html#term-hashable) objects. It is a collection where elements are stored as dictionary keys and their counts are stored as dictionary values. Counts are allowed to be any integer value including zero or negative counts. The [`Counter`](https://docs.python.org/3/library/collections.html#collections.Counter) class is similar to bags or multisets in other languages.
Elements are counted from an *iterable* or initialized from another *mapping* (or counter):~~>>>~~
`c = Counter() *# a new, empty counter*c = Counter('gallahad') *# a new counter from an iterable*c = Counter({'red': 4, 'blue': 2}) *# a new counter from a mapping*c = Counter(cats=4, dogs=8) *# a new counter from keyword args*`
Counter objects have a dictionary interface except that they return a zero count for missing items instead of raising a [`KeyError`](https://docs.python.org/3/library/exceptions.html#KeyError):~~>>>~~
`c = Counter(['eggs', 'ham'])
c['bacon'] *# count of a missing element is zero*`
Setting a count to zero does not remove an element from a counter. Use `del` to remove it entirely:~~>>>~~
`c['sausage'] = 0 *# counter entry with a zero count***del** c['sausage'] *# del actually removes the entry*`
*Added in version 3.1.*
*Changed in version 3.7:* As a [`dict`](https://docs.python.org/3/library/stdtypes.html#dict) subclass, [`Counter`](https://docs.python.org/3/library/collections.html#collections.Counter) inherited the capability to remember insertion order. Math operations on *Counter* objects also preserve order. Results are ordered according to when an element is first encountered in the left operand and then by the order encountered in the right operand."}
{"_id": 75, "title": "", "text": "Set the mode in [`open()`](https://docs.python.org/3/library/functions.html#open) to `\"a\"` (append) instead of `\"w\"` (write):
```python
with open(\"test.txt\", \"a\") as myfile:
myfile.write(\"appended text\")
```
The [documentation](https://docs.python.org/3/library/functions.html#open) lists all the available modes."}
{"_id": 76, "title": "", "text": "```python
with open(\"test.txt\", \"a\") as myfile:
myfile.write(\"appended text\")
```"}
@@ -92,10 +92,10 @@
{"_id": 91, "title": "", "text": "```python
from matplotlib import pyplot as plt
plt.savefig('foo.png')
plt.savefig('foo.pdf')
```"}
{"_id": 92, "title": "", "text": "# matplotlib.pyplot.savefig
**matplotlib.pyplot.savefig(**args*, ***kwargs*)[[source]](https://github.com/matplotlib/matplotlib/blob/v3.9.1/lib/matplotlib/pyplot.py#L1223-L1230)**Save the current figure as an image or vector graphic to a file.
Call signature:
`savefig(fname, *, transparent=None, dpi='figure', format=None,
metadata=None, bbox_inches=None, pad_inches=0.1,
facecolor='auto', edgecolor='auto', backend=None,
**kwargs
)`
The available output formats depend on the backend being used.**Parameters:fnamestr or path-like or binary file-like**A path, or a Python file-like object, or possibly some backend-dependent object such as [**`matplotlib.backends.backend_pdf.PdfPages`**](https://matplotlib.org/stable/api/backend_pdf_api.html#matplotlib.backends.backend_pdf.PdfPages).
If *format* is set, it determines the output format, and the file is saved as *fname*. Note that *fname* is used verbatim, and there is no attempt to make the extension, if any, of *fname* match *format*, and no extension is appended.
If *format* is not set, then the format is inferred from the extension of *fname*, if there is one. If *format* is not set and *fname* has no extension, then the file is saved with [`rcParams[\"savefig.format\"]`](https://matplotlib.org/stable/users/explain/customizing.html?highlight=savefig.format#matplotlibrc-sample) (default: `'png'`) and the appropriate extension is appended to *fname*."}
{"_id": 93, "title": "", "text": "### Python 3.4+
Use [`pathlib.Path.stem`](https://docs.python.org/3/library/pathlib.html#pathlib.PurePath.stem)
```python
>>> from pathlib import Path
>>> Path(\"/path/to/file.txt\").stem
'file'
>>> Path(\"/path/to/file.tar.gz\").stem
'file.tar'
```
### Python < 3.4
Use [`os.path.splitext`](https://docs.python.org/3/library/os.path.html#os.path.splitext) in combination with [`os.path.basename`](https://docs.python.org/3/library/os.path.html#os.path.basename):
```python
>>> os.path.splitext(os.path.basename(\"/path/to/file.txt\"))[0]
'file'
>>> os.path.splitext(os.path.basename(\"/path/to/file.tar.gz\"))[0]
'file.tar'
```"}
-{"_id": 94, "title": "", "text": "```python
>>> from pathlib import Path
>>> Path(\"/path/to/file.txt\").stem
'file'
>>> Path(\"/path/to/file.tar.gz\").stem
'file.tar'
```"}
+{"_id": 94, "title": "", "text": "
```python
>>> from pathlib import Path
>>> Path(\"/path/to/file.txt\").stem
'file'
>>> Path(\"/path/to/file.tar.gz\").stem
'file.tar'
```"}
{"_id": 95, "title": "", "text": "PurePath.**stem**
The final path component, without its suffix:>>>
**`>>>** PurePosixPath('my/library.tar.gz').stem
'library.tar'
**>>>** PurePosixPath('my/library.tar').stem
'library'
**>>>** PurePosixPath('my/library').stem
'library'`"}
{"_id": 96, "title": "", "text": "Use [**`os.path.isdir`**](http://docs.python.org/dev/library/os.path.html#os.path.isdir) for directories only:
```python
>>> import os
>>> os.path.isdir('new_folder')
True
```
Use [**`os.path.exists`**](http://docs.python.org/dev/library/os.path.html#os.path.exists) for both files and directories:
```python
>>> import os
>>> os.path.exists(os.path.join(os.getcwd(), 'new_folder', 'file.txt'))
False
```
Alternatively, you can use [**`pathlib`**](https://docs.python.org/dev/library/pathlib.html):
```python
>>> from pathlib import Path
>>> Path('new_folder').is_dir()
True
>>> (Path.cwd() / 'new_folder' / 'file.txt').exists()
False
```"}
-{"_id": 97, "title": "", "text": "```python
>>> import os
>>> os.path.isdir('new_folder')
True
```"}
+{"_id": 97, "title": "", "text": "
```python
>>> import os
>>> os.path.isdir('new_folder')
True
```"}
{"_id": 98, "title": "", "text": "os.path.**isdir**(*path*)
Return `True` if *path* is an [`existing`](https://docs.python.org/dev/library/os.path.html#os.path.exists) directory. This follows symbolic links, so both [`islink()`](https://docs.python.org/dev/library/os.path.html#os.path.islink) and [`isdir()`](https://docs.python.org/dev/library/os.path.html#os.path.isdir) can be true for the same path.
*Changed in version 3.6:* Accepts a [path-like object](https://docs.python.org/dev/glossary.html#term-path-like-object)."}
{"_id": 99, "title": "", "text": "[`os.rename()`](http://docs.python.org/library/os.html#os.rename), [`os.replace()`](https://docs.python.org/library/os.html#os.replace), or [`shutil.move()`](http://docs.python.org/library/shutil.html#shutil.move)
All employ the same syntax:
```python
import os
import shutil
os.rename(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
os.replace(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
shutil.move(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
```
- The filename (`\"file.foo\"`) must be included in both the source and destination arguments. If it differs between the two, the file will be renamed as well as moved.
- The directory within which the new file is being created must already exist.
- On Windows, a file with that name must not exist or an exception will be raised, but `os.replace()` will silently replace a file even in that occurrence.
- `shutil.move` simply calls `os.rename` in most cases. However, if the destination is on a different disk than the source, it will instead copy and then delete the source file."}
{"_id": 100, "title": "", "text": "```python
import os
import shutil
os.rename(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
os.replace(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
shutil.move(\"path/to/current/file.foo\", \"path/to/new/destination/for/file.foo\")
```"}
@@ -116,7 +116,7 @@
{"_id": 115, "title": "", "text": "```python
import urllib.request
with urllib.request.urlopen('http://www.example.com/') as f:
html = f.read().decode('utf-8')
```"}
{"_id": 116, "title": "", "text": "urllib.request.**urlopen**(*url*, *data=None*, [*timeout*, ]***, *cafile=None*, *capath=None*, *cadefault=False*, *context=None*)
Open *url*, which can be either a string containing a valid, properly encoded URL, or a [`Request`](https://docs.python.org/3/library/urllib.request.html#urllib.request.Request) object.
*data* must be an object specifying additional data to be sent to the server, or `None` if no such data is needed. See [`Request`](https://docs.python.org/3/library/urllib.request.html#urllib.request.Request) for details.
urllib.request module uses HTTP/1.1 and includes `Connection:close` header in its HTTP requests.
The optional *timeout* parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used). This actually only works for HTTP, HTTPS and FTP connections.
If *context* is specified, it must be a [`ssl.SSLContext`](https://docs.python.org/3/library/ssl.html#ssl.SSLContext) instance describing the various SSL options. See [`HTTPSConnection`](https://docs.python.org/3/library/http.client.html#http.client.HTTPSConnection) for more details.
The optional *cafile* and *capath* parameters specify a set of trusted CA certificates for HTTPS requests. *cafile* should point to a single file containing a bundle of CA certificates, whereas *capath* should point to a directory of hashed certificate files. More information can be found in [`ssl.SSLContext.load_verify_locations()`](https://docs.python.org/3/library/ssl.html#ssl.SSLContext.load_verify_locations).
The *cadefault* parameter is ignored.
This function always returns an object which can work as a [context manager](https://docs.python.org/3/glossary.html#term-context-manager) and has the properties *url*, *headers*, and *status*. See [`urllib.response.addinfourl`](https://docs.python.org/3/library/urllib.request.html#urllib.response.addinfourl) for more detail on these properties.
For HTTP and HTTPS URLs, this function returns a [`http.client.HTTPResponse`](https://docs.python.org/3/library/http.client.html#http.client.HTTPResponse) object slightly modified. In addition to the three new methods above, the msg attribute contains the same information as the [`reason`](https://docs.python.org/3/library/http.client.html#http.client.HTTPResponse.reason) attribute — the reason phrase returned by server — instead of the response headers as it is specified in the documentation for [`HTTPResponse`](https://docs.python.org/3/library/http.client.html#http.client.HTTPResponse).
For FTP, file, and data URLs and requests explicitly handled by legacy [`URLopener`](https://docs.python.org/3/library/urllib.request.html#urllib.request.URLopener) and [`FancyURLopener`](https://docs.python.org/3/library/urllib.request.html#urllib.request.FancyURLopener) classes, this function returns a [`urllib.response.addinfourl`](https://docs.python.org/3/library/urllib.request.html#urllib.response.addinfourl) object.
Raises [`URLError`](https://docs.python.org/3/library/urllib.error.html#urllib.error.URLError) on protocol errors.
Note that `None` may be returned if no handler handles the request (though the default installed global [`OpenerDirector`](https://docs.python.org/3/library/urllib.request.html#urllib.request.OpenerDirector) uses [`UnknownHandler`](https://docs.python.org/3/library/urllib.request.html#urllib.request.UnknownHandler) to ensure this never happens).
In addition, if proxy settings are detected (for example, when a `*_proxy` environment variable like `http_proxy` is set), [`ProxyHandler`](https://docs.python.org/3/library/urllib.request.html#urllib.request.ProxyHandler) is default installed and makes sure the requests are handled through the proxy.
The legacy `urllib.urlopen` function from Python 2.6 and earlier has been discontinued; [`urllib.request.urlopen()`](https://docs.python.org/3/library/urllib.request.html#urllib.request.urlopen) corresponds to the old `urllib2.urlopen`. Proxy handling, which was done by passing a dictionary parameter to `urllib.urlopen`, can be obtained by using [`ProxyHandler`](https://docs.python.org/3/library/urllib.request.html#urllib.request.ProxyHandler) objects.
The default opener raises an [auditing event](https://docs.python.org/3/library/sys.html#auditing) `urllib.Request` with arguments `fullurl`, `data`, `headers`, `method` taken from the request object."}
{"_id": 117, "title": "", "text": "To delimit by a tab you can use the `sep` argument of [`to_csv`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html):
```python
df.to_csv(file_name, sep='\\t')
```
To use a specific encoding (e.g. 'utf-8') use the `encoding` argument:
```python
df.to_csv(file_name, sep='\\t', encoding='utf-8')
```
In many cases you will want to remove the index and add a header:
```python
df.to_csv(file_name, sep='\\t', encoding='utf-8', index=False, header=True)
```"}
-{"_id": 118, "title": "", "text": "```python
df.to_csv(file_name, sep='\\t')
```"}
+{"_id": 118, "title": "", "text": "
```python
df.to_csv(file_name, sep='\\t')
```"}
{"_id": 119, "title": "", "text": "pandas.DataFrame.to_csv
**DataFrame.to_csv(path_or_buf=None, ***, sep=',', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, mode='w', encoding=None, compression='infer', quoting=None, quotechar='\"', lineterminator=None, chunksize=None, date_format=None, doublequote=True, escapechar=None, decimal='.', errors='strict', storage_options=None)[source]**Write object to a comma-separated values (csv) file."}
{"_id": 120, "title": "", "text": "This to me sounds like a reasonably common problem that junior to intermediate developers tend to face at some point: they either don't know or don't trust the contracts they are participating in and defensively overcheck for nulls. Additionally, when writing their own code, they tend to rely on returning nulls to indicate something thus requiring the caller to check for nulls.
To put this another way, there are two instances where null checking comes up:
1. Where null is a valid response in terms of the contract; and
2. Where it isn't a valid response.
(2) is easy. As of Java 1.7 you can use [`Objects.requireNonNull(foo)`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/Objects.html#requireNonNull(T)). (If you are stuck with a previous version then [`assert`ions](https://docs.oracle.com/javase/7/docs/technotes/guides/language/assert.html) may be a good alternative.)
\"Proper\" usage of this method would be like below. The method returns the object passed into it and throws a `NullPointerException` if the object is null. This means that the returned value is always non-null. The method is primarily intended for validating parameters.
```java
public Foo(Bar bar) {
this.bar = Objects.requireNonNull(bar);
}
```
It can also be used like an `assert`ion though since it throws an exception if the object is null. In both uses, a message can be added which will be shown in the exception. Below is using it like an assertion and providing a message.
```java
Objects.requireNonNull(someobject, \"if someobject is null then something is wrong\");
someobject.doCalc();
```
Generally throwing a specific exception like `NullPointerException` when a value is null but shouldn't be is favorable to throwing a more general exception like `AssertionError`. This is the approach the Java library takes; favoring `NullPointerException` over `IllegalArgumentException` when an argument is not allowed to be null.
(1) is a little harder. If you have no control over the code you're calling then you're stuck. If null is a valid response, you have to check for it.
If it's code that you do control, however (and this is often the case), then it's a different story. Avoid using nulls as a response. With methods that return collections, it's easy: return empty collections (or arrays) instead of nulls pretty much all the time.
With non-collections it might be harder. Consider this as an example: if you have these interfaces:
```java
public interface Action {
void doSomething();
}
public interface Parser {
Action findAction(String userInput);
}
```
where Parser takes raw user input and finds something to do, perhaps if you're implementing a command line interface for something. Now you might make the contract that it returns null if there's no appropriate action. That leads the null checking you're talking about.
An alternative solution is to never return null and instead use the [Null Object pattern](https://en.wikipedia.org/wiki/Null_Object_pattern):
```java
public class MyParser implements Parser {
private static Action DO_NOTHING = new Action() {
public void doSomething() { /* do nothing */ }
};
public Action findAction(String userInput) {
// ...
if ( /* we can't find any actions */ ) {
return DO_NOTHING;
}
}
}
```
Compare:
```java
Parser parser = ParserFactory.getParser();
if (parser == null) {
// now what?
// this would be an example of where null isn't (or shouldn't be) a valid response
}
Action action = parser.findAction(someInput);
if (action == null) {
// do nothing
} else {
action.doSomething();
}
```
to
```java
ParserFactory.getParser().findAction(someInput).doSomething();
```
which is a much better design because it leads to more concise code.
That said, perhaps it is entirely appropriate for the findAction() method to throw an Exception with a meaningful error message -- especially in this case where you are relying on user input. It would be much better for the findAction method to throw an Exception than for the calling method to blow up with a simple NullPointerException with no explanation.
```java
try {
ParserFactory.getParser().findAction(someInput).doSomething();
} catch(ActionNotFoundException anfe) {
userConsole.err(anfe.getMessage());
}
```
Or if you think the try/catch mechanism is too ugly, rather than Do Nothing your default action should provide feedback to the user.
```java
public Action findAction(final String userInput) {
/* Code to return requested Action if found */
return new Action() {
public void doSomething() {
userConsole.err(\"Action not found: \" + userInput);
}
}
}
```"}
{"_id": 121, "title": "", "text": "```java
public Foo(Bar bar) {
this.bar = Objects.requireNonNull(bar);
}
```"}
@@ -125,7 +125,7 @@
{"_id": 124, "title": "", "text": "```java
// These two have the same value
new String(\"test\").equals(\"test\") // --> true
// ... but they are not the same object
new String(\"test\") == \"test\" // --> false
// ... neither are these
new String(\"test\") == new String(\"test\") // --> false
// ... but these are because literals are interned by
// the compiler and thus refer to the same object
\"test\" == \"test\" // --> true
// ... string literals are concatenated by the compiler
// and the results are interned.
\"test\" == \"te\" + \"st\" // --> true
// ... but you should really just call Objects.equals()
Objects.equals(\"test\", new String(\"test\")) // --> true
Objects.equals(null, \"test\") // --> false
Objects.equals(null, null) // --> true
```"}
{"_id": 125, "title": "", "text": "### Method Detail
- equals
```
public static boolean equals(Object a,
Object b)
```
Returns `true` if the arguments are equal to each other and `false` otherwise. Consequently, if both arguments are `null`, `true` is returned and if exactly one argument is `null`, `false` is returned. Otherwise, equality is determined by using the [`equals`](https://docs.oracle.com/javase/7/docs/api/java/lang/Object.html#equals(java.lang.Object)) method of the first argument.
**Parameters:**`a` - an object`b` - an object to be compared with `a` for equality**Returns:**`true` if the arguments are equal to each other and `false` otherwise**See Also:**[`Object.equals(Object)`](https://docs.oracle.com/javase/7/docs/api/java/lang/Object.html#equals(java.lang.Object))"}
{"_id": 126, "title": "", "text": "Since Java 5 you can use [`Arrays.toString(arr)`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/Arrays.html#toString(int%5B%5D)) or [`Arrays.deepToString(arr)`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/Arrays.html#deepToString(java.lang.Object%5B%5D)) for arrays within arrays. Note that the `Object[]` version calls `.toString()` on each object in the array. The output is even decorated in the exact way you're asking.
Examples:
- Simple Array:
```java
String[] array = new String[] {\"John\", \"Mary\", \"Bob\"};
System.out.println(Arrays.toString(array));
```
Output:
```java
[John, Mary, Bob]
```
- Nested Array:
```java
String[][] deepArray = new String[][] {{\"John\", \"Mary\"}, {\"Alice\", \"Bob\"}};
// Gives undesired output:
System.out.println(Arrays.toString(deepArray));
// Gives the desired output:
System.out.println(Arrays.deepToString(deepArray));
```
Output:
```java
[[Ljava.lang.String;@106d69c, [Ljava.lang.String;@52e922]
[[John, Mary], [Alice, Bob]]
```
- `double` Array:
```java
double[] doubleArray = { 7.0, 9.0, 5.0, 1.0, 3.0 };
System.out.println(Arrays.toString(doubleArray));
```
Output:
```java
[7.0, 9.0, 5.0, 1.0, 3.0 ]
```
- `int` Array:
```java
int[] intArray = { 7, 9, 5, 1, 3 };
System.out.println(Arrays.toString(intArray));
```
Output:
```java
[7, 9, 5, 1, 3 ]
```"}
-{"_id": 127, "title": "", "text": "```java
String[] array = new String[] {\"John\", \"Mary\", \"Bob\"};
System.out.println(Arrays.toString(array));
```"}
+{"_id": 127, "title": "", "text": "
```java
String[] array = new String[] {\"John\", \"Mary\", \"Bob\"};
System.out.println(Arrays.toString(array));
```"}
{"_id": 128, "title": "", "text": "
- toString
public static [String](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/lang/String.html) toString(int[] a)
Returns a string representation of the contents of the specified array. The string representation consists of a list of the array's elements, enclosed in square brackets (`\"[]\"`). Adjacent elements are separated by the characters `\", \"` (a comma followed by a space). Elements are converted to strings as by `String.valueOf(int)`. Returns `\"null\"` if `a` is `null`.
**Parameters:**`a` - the array whose string representation to return**Returns:**a string representation of `a`**Since:**1.5"}
{"_id": 129, "title": "", "text": "Use the appropriately named method [`String#split()`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/lang/String.html#split(java.lang.String)).
```java
String string = \"004-034556\";
String[] parts = string.split(\"-\");
String part1 = parts[0]; // 004
String part2 = parts[1]; // 034556
```
Note that `split`'s argument is assumed to be a [regular expression](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/regex/Pattern.html#sum), so remember to escape [special characters](https://www.regular-expressions.info/characters.html) if necessary.
> there are 12 characters with special meanings: the backslash \\, the caret ^, the dollar sign $, the period or dot ., the vertical bar or pipe symbol |, the question mark ?, the asterisk or star *, the plus sign +, the opening parenthesis (, the closing parenthesis ), and the opening square bracket [, the opening curly brace {, These special characters are often called \"metacharacters\".
>
For instance, to split on a period/dot `.` (which means \"[any character](https://www.regular-expressions.info/dot.html)\" in regex), use either [backslash `\\`](https://www.regular-expressions.info/characters.html) to escape the individual special character like so `split(\"\\\\.\")`, or use [character class `[]`](https://www.regular-expressions.info/charclass.html) to represent literal character(s) like so `split(\"[.]\")`, or use [`Pattern#quote()`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/regex/Pattern.html#quote(java.lang.String)) to escape the entire string like so `split(Pattern.quote(\".\"))`.
```java
String[] parts = string.split(Pattern.quote(\".\")); // Split on the exact string.
```
To test beforehand if the string contains certain character(s), just use [`String#contains()`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/lang/String.html#contains(java.lang.CharSequence)).
```java
if (string.contains(\"-\")) {
// Split it.
} else {
throw new IllegalArgumentException(\"String \" + string + \" does not contain -\");
}
```
Note, this does not take a regular expression. For that, use [`String#matches()`](https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/lang/String.html#matches(java.lang.String)) instead.
If you'd like to retain the split character in the resulting parts, then make use of [positive lookaround](https://www.regular-expressions.info/lookaround.html). In case you want to have the split character to end up in left hand side, use positive lookbehind by prefixing `?<=` group on the pattern.
```java
String string = \"004-034556\";
String[] parts = string.split(\"(?<=-)\");
String part1 = parts[0]; // 004-
String part2 = parts[1]; // 034556
```
In case you want to have the split character to end up in right hand side, use positive lookahead by prefixing `?=` group on the pattern.
```java
String string = \"004-034556\";
String[] parts = string.split(\"(?=-)\");
String part1 = parts[0]; // 004
String part2 = parts[1]; // -034556
```
If you'd like to limit the number of resulting parts, then you can supply the desired number as 2nd argument of `split()` method.
```java
String string = \"004-034556-42\";
String[] parts = string.split(\"-\", 2);
String part1 = parts[0]; // 004
String part2 = parts[1]; // 034556-42
```"}
{"_id": 130, "title": "", "text": "```java
String string = \"004-034556\";
String[] parts = string.split(\"-\");
String part1 = parts[0]; // 004
String part2 = parts[1]; // 034556
```"}
@@ -152,7 +152,7 @@
{"_id": 151, "title": "", "text": "```java
try {
Files.write(Paths.get(\"myfile.txt\"), \"the text\".getBytes(), StandardOpenOption.APPEND);
}catch (IOException e) {
//exception handling left as an exercise for the reader
}
```"}
{"_id": 152, "title": "", "text": "### Method Detail
- newInputStreamOpens a file, returning an input stream to read from the file. The stream will not be buffered, and is not required to support the [`mark`](https://docs.oracle.com/javase/7/docs/api/java/io/InputStream.html#mark(int)) or [`reset`](https://docs.oracle.com/javase/7/docs/api/java/io/InputStream.html#reset()) methods. The stream will be safe for access by multiple concurrent threads. Reading commences at the beginning of the file. Whether the returned stream is *asynchronously closeable* and/or *interruptible* is highly file system provider specific and therefore not specified.
```
public staticInputStream newInputStream(Path path,
OpenOption... options)
throwsIOException
```
The `options` parameter determines how the file is opened. If no options are present then it is equivalent to opening the file with the [`READ`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/StandardOpenOption.html#READ) option. In addition to the `READ` option, an implementation may also support additional implementation specific options.
**Parameters:**`path` - the path to the file to open`options` - options specifying how the file is opened**Returns:**a new input stream**Throws:**[`IllegalArgumentException`](https://docs.oracle.com/javase/7/docs/api/java/lang/IllegalArgumentException.html) - if an invalid combination of options is specified[`UnsupportedOperationException`](https://docs.oracle.com/javase/7/docs/api/java/lang/UnsupportedOperationException.html) - if an unsupported option is specified[`IOException`](https://docs.oracle.com/javase/7/docs/api/java/io/IOException.html) - if an I/O error occurs[`SecurityException`](https://docs.oracle.com/javase/7/docs/api/java/lang/SecurityException.html) - In the case of the default provider, and a security manager is installed, the [`checkRead`](https://docs.oracle.com/javase/7/docs/api/java/lang/SecurityManager.html#checkRead(java.lang.String)) method is invoked to check read access to the file.
- newOutputStreamOpens or creates a file, returning an output stream that may be used to write bytes to the file. The resulting stream will not be buffered. The stream will be safe for access by multiple concurrent threads. Whether the returned stream is *asynchronously closeable* and/or *interruptible* is highly file system provider specific and therefore not specified.
```
public staticOutputStream newOutputStream(Path path,
OpenOption... options)
throwsIOException
```
This method opens or creates a file in exactly the manner specified by the [`newByteChannel`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/Files.html#newByteChannel(java.nio.file.Path,%20java.util.Set,%20java.nio.file.attribute.FileAttribute...)) method with the exception that the [`READ`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/StandardOpenOption.html#READ) option may not be present in the array of options. If no options are present then this method works as if the [`CREATE`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/StandardOpenOption.html#CREATE), [`TRUNCATE_EXISTING`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/StandardOpenOption.html#TRUNCATE_EXISTING), and [`WRITE`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/StandardOpenOption.html#WRITE) options are present. In other words, it opens the file for writing, creating the file if it doesn't exist, or initially truncating an existing [`regular-file`](https://docs.oracle.com/javase/7/docs/api/java/nio/file/Files.html#isRegularFile(java.nio.file.Path,%20java.nio.file.LinkOption...)) to a size of `0` if it exists.
**Usage Examples:**
```
Path path = ...
// truncate and overwrite an existing file, or create the file if
// it doesn't initially exist
OutputStream out = Files.newOutputStream(path);
// append to an existing file, fail if the file does not exist
out = Files.newOutputStream(path, APPEND);
// append to an existing file, create file if it doesn't initially exist
out = Files.newOutputStream(path, CREATE, APPEND);
// always create new file, failing if it already exists
out = Files.newOutputStream(path, CREATE_NEW);
```
**Parameters:**`path` - the path to the file to open or create`options` - options specifying how the file is opened**Returns:**a new output stream**Throws:**[`IllegalArgumentException`](https://docs.oracle.com/javase/7/docs/api/java/lang/IllegalArgumentException.html) - if `options` contains an invalid combination of options[`UnsupportedOperationException`](https://docs.oracle.com/javase/7/docs/api/java/lang/UnsupportedOperationException.html) - if an unsupported option is specified[`IOException`](https://docs.oracle.com/javase/7/docs/api/java/io/IOException.html) - if an I/O error occurs[`SecurityException`](https://docs.oracle.com/javase/7/docs/api/java/lang/SecurityException.html) - In the case of the default provider, and a security manager is installed, the [`checkWrite`](https://docs.oracle.com/javase/7/docs/api/java/lang/SecurityManager.html#checkWrite(java.lang.String)) method is invoked to check write access to the file. The [`checkDelete`](https://docs.oracle.com/javase/7/docs/api/java/lang/SecurityManager.html#checkDelete(java.lang.String)) method is invoked to check delete access if the file is opened with the `DELETE_ON_CLOSE` option."}
{"_id": 153, "title": "", "text": "From the [Java Tutorial](http://java.sun.com/docs/books/tutorial/java/javaOO/nested.html):
> Nested classes are divided into two categories: static and non-static. Nested classes that are declared static are simply called static nested classes. Non-static nested classes are called inner classes.
>
Static nested classes are accessed using the enclosing class name:
```java
OuterClass.StaticNestedClass
```
For example, to create an object for the static nested class, use this syntax:
```java
OuterClass.StaticNestedClass nestedObject = new OuterClass.StaticNestedClass();
```
Objects that are instances of an inner class exist within an instance of the outer class. Consider the following classes:
```java
class OuterClass {
...
class InnerClass {
...
}
}
```
An instance of InnerClass can exist only within an instance of OuterClass and has direct access to the methods and fields of its enclosing instance.
To instantiate an inner class, you must first instantiate the outer class. Then, create the inner object within the outer object with this syntax:
```java
OuterClass outerObject = new OuterClass()
OuterClass.InnerClass innerObject = outerObject.new InnerClass();
```
see: [Java Tutorial - Nested Classes](http://download.oracle.com/javase/tutorial/java/javaOO/nested.html)
For completeness note that there is also such a thing as an [inner class *without* an enclosing instance](https://stackoverflow.com/questions/20468856/is-it-true-that-every-inner-class-requires-an-enclosing-instance):
```java
class A {
int t() { return 1; }
static A a = new A() { int t() { return 2; } };
}
```
Here, `new A() { ... }` is an *inner class defined in a static context* and does not have an enclosing instance."}
-{"_id": 154, "title": "", "text": "```java
class OuterClass {
...
class InnerClass {
...
}
}
```"}
+{"_id": 154, "title": "", "text": "
```java
class OuterClass {
...
class InnerClass {
...
}
}
```"}
{"_id": 155, "title": "", "text": "# **Nested Classes**
The Java programming language allows you to define a class within another class. Such a class is called a *nested class* and is illustrated here:
`class OuterClass {
...
class NestedClass {
...
}
}`
---
**Terminology:**
Nested classes are divided into two categories: non-static and static. Non-static nested classes are called
*inner classes*
. Nested classes that are declared
```
static
```
are called
*static nested classes*
.
---
`class OuterClass {
...
class InnerClass {
...
}
static class StaticNestedClass {
...
}
}`
A nested class is a member of its enclosing class. Non-static nested classes (inner classes) have access to other members of the enclosing class, even if they are declared private. Static nested classes do not have access to other members of the enclosing class. As a member of the `OuterClass`, a nested class can be declared `private`, `public`, `protected`, or *package private*. (Recall that outer classes can only be declared `public` or *package private*.)"}
{"_id": 156, "title": "", "text": "There are two types of array.
## One Dimensional Array
Syntax for default values:
```java
int[] num = new int[5];
```
Or (less preferred)
```java
int num[] = new int[5];
```
Syntax with values given (variable/field initialization):
```java
int[] num = {1,2,3,4,5};
```
Or (less preferred)
```java
int num[] = {1, 2, 3, 4, 5};
```
Note: For convenience int[] num is preferable because it clearly tells that you are talking here about array. Otherwise no difference. Not at all.
## Multidimensional array
### Declaration
```java
int[][] num = new int[5][2];
```
Or
```java
int num[][] = new int[5][2];
```
Or
```java
int[] num[] = new int[5][2];
```
### Initialization
```java
num[0][0]=1;
num[0][1]=2;
num[1][0]=1;
num[1][1]=2;
num[2][0]=1;
num[2][1]=2;
num[3][0]=1;
num[3][1]=2;
num[4][0]=1;
num[4][1]=2;
```
Or
```java
int[][] num={ {1,2}, {1,2}, {1,2}, {1,2}, {1,2} };
```
### Ragged Array (or Non-rectangular Array)
```java
int[][] num = new int[5][];
num[0] = new int[1];
num[1] = new int[5];
num[2] = new int[2];
num[3] = new int[3];
```
So here we are defining columns explicitly.
**Another Way:**
```java
int[][] num={ {1}, {1,2}, {1,2,3,4,5}, {1,2}, {1,2,3} };
```
## For Accessing:
```java
for (int i=0; i<(num.length); i++ ) {
for (int j=0;j System.out.println(num[i][j]);
}
```
Alternatively:
```java
for (int[] a : num) {
for (int i : a) {
System.out.println(i);
}
}
```
Ragged arrays are multidimensional arrays.
For explanation see multidimensional array detail at [the official java tutorials](http://docs.oracle.com/javase/tutorial/java/nutsandbolts/arrays.html)"}
{"_id": 157, "title": "", "text": "```java
int[] num = new int[5];
```"}
@@ -296,905 +296,905 @@
{"_id": 295, "title": "", "text": "```python
# evaluate model:
model.eval()
with torch.no_grad():
...
out_data = model(data)
...
```"}
{"_id": 296, "title": "", "text": "**eval()[[SOURCE]](https://pytorch.org/docs/stable/_modules/torch/nn/modules/module.html#Module.eval)**
**Set the module in evaluation mode.
This has any effect only on certain modules. See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g. [`Dropout`](https://pytorch.org/docs/stable/generated/torch.nn.Dropout.html#torch.nn.Dropout), `BatchNorm`, etc.
This is equivalent with [`self.train(False)`](https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.train).
See [Locally disabling gradient computation](https://pytorch.org/docs/stable/notes/autograd.html#locally-disable-grad-doc) for a comparison between .eval() and several similar mechanisms that may be confused with it.ReturnsselfReturn type[Module](https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module)**"}
{"_id": 297, "title": "", "text": "I'm referring to the question in the title as you haven't really specified anything else in the text, so just converting the DataFrame into a PyTorch tensor.
Without information about your data, I'm just taking float values as example targets here.
**Convert Pandas dataframe to PyTorch tensor?**
```python
import pandas as pd
import torch
import random
# creating dummy targets (float values)
targets_data = [random.random() for i in range(10)]
# creating DataFrame from targets_data
targets_df = pd.DataFrame(data=targets_data)
targets_df.columns = ['targets']
# creating tensor from targets_df
torch_tensor = torch.tensor(targets_df['targets'].values)
# printing out result
print(torch_tensor)
```
**Output:**
```python
tensor([ 0.5827, 0.5881, 0.1543, 0.6815, 0.9400, 0.8683, 0.4289,
0.5940, 0.6438, 0.7514], dtype=torch.float64)
```
*Tested with Pytorch 0.4.0.*
I hope this helps, if you have any further questions - just ask. :)"}
-{"_id": 298, "title": "", "text": "```python
import pandas as pd
import torch
import random
# creating dummy targets (float values)
targets_data = [random.random() for i in range(10)]
# creating DataFrame from targets_data
targets_df = pd.DataFrame(data=targets_data)
targets_df.columns = ['targets']
# creating tensor from targets_df
torch_tensor = torch.tensor(targets_df['targets'].values)
# printing out result
print(torch_tensor)
```"}
+{"_id": 298, "title": "", "text": "
```python
import pandas as pd
import torch
import random
# creating dummy targets (float values)
targets_data = [random.random() for i in range(10)]
# creating DataFrame from targets_data
targets_df = pd.DataFrame(data=targets_data)
targets_df.columns = ['targets']
# creating tensor from targets_df
torch_tensor = torch.tensor(targets_df['targets'].values)
# printing out result
print(torch_tensor)
```"}
{"_id": 299, "title": "", "text": "# TORCH.TENSOR
**torch.tensor(*data*, ***, *dtype=None*, *device=None*, *requires_grad=False*, *pin_memory=False*) → [Tensor](https://pytorch.org/docs/master/tensors.html#torch.Tensor)Constructs a tensor with no autograd history (also known as a “leaf tensor”, see [Autograd mechanics](https://pytorch.org/docs/master/notes/autograd.html)) by copying `data`.
WARNING
When working with tensors prefer using [`torch.Tensor.clone()`](https://pytorch.org/docs/master/generated/torch.Tensor.clone.html#torch.Tensor.clone), [`torch.Tensor.detach()`](https://pytorch.org/docs/master/generated/torch.Tensor.detach.html#torch.Tensor.detach), and [`torch.Tensor.requires_grad_()`](https://pytorch.org/docs/master/generated/torch.Tensor.requires_grad_.html#torch.Tensor.requires_grad_) for readability. Letting t be a tensor, `torch.tensor(t)` is equivalent to `t.clone().detach()`, and `torch.tensor(t, requires_grad=True)` is equivalent to `t.clone().detach().requires_grad_(True)`.
SEE ALSO
[`torch.as_tensor()`](https://pytorch.org/docs/master/generated/torch.as_tensor.html#torch.as_tensor) preserves autograd history and avoids copies where possible. [`torch.from_numpy()`](https://pytorch.org/docs/master/generated/torch.from_numpy.html#torch.from_numpy) creates a tensor that shares storage with a NumPy array.Parameters:data (*array_like*) – Initial data for the tensor. Can be a list, tuple, NumPy `ndarray`, scalar, and other types.Keyword Arguments:
• dtype ([`torch.dtype`](https://pytorch.org/docs/master/tensor_attributes.html#torch.dtype), optional) – the desired data type of returned tensor. Default: if `None`, infers data type from `data`.
• device ([`torch.device`](https://pytorch.org/docs/master/tensor_attributes.html#torch.device), optional) – the device of the constructed tensor. If None and data is a tensor then the device of data is used. If None and data is not a tensor then the result tensor is constructed on the CPU.
• requires_grad ([*bool](https://docs.python.org/3/library/functions.html#bool), optional*) – If autograd should record operations on the returned tensor. Default: `False`.
• pin_memory ([*bool](https://docs.python.org/3/library/functions.html#bool), optional*) – If set, returned tensor would be allocated in the pinned memory. Works only for CPU tensors. Default: `False`.
Example:
`>>> torch.tensor([[0.1, 1.2], [2.2, 3.1], [4.9, 5.2]])tensor([[ 0.1000, 1.2000],
[ 2.2000, 3.1000],
[ 4.9000, 5.2000]])
>>> torch.tensor([0, 1]) *# Type inference on data*tensor([ 0, 1])
>>> torch.tensor([[0.11111, 0.222222, 0.3333333]],... dtype=torch.float64,... device=torch.device('cuda:0')) *# creates a double tensor on a CUDA device*tensor([[ 0.1111, 0.2222, 0.3333]], dtype=torch.float64, device='cuda:0')
>>> torch.tensor(3.14159) *# Create a zero-dimensional (scalar) tensor*tensor(3.1416)
>>> torch.tensor([]) *# Create an empty tensor (of size (0,))*tensor([])`**"}
-{"_id": 0, "title": "", "text": "
```markdown
# How to access environment variables in Ruby?
To access environment variables in Ruby, you can use the `ENV` object.
```ruby
# Example
puts ENV['HOME'] # Outputs the home directory
```
More details can be found in the [Ruby documentation](https://ruby-doc.org/core-2.5.0/ENV.html).
```"}
-{"_id": 1, "title": "", "text": "```javascript
// Accessing environment variables in Node.js
console.log(process.env.MY_VARIABLE);
```"}
-{"_id": 2, "title": "", "text": "# Introduction to Environment Variables
Environment variables are a set of dynamic named values that can affect the way running processes will behave on a computer. These variables are part of the environment in which a process runs. They are used by the operating system to configure system behavior and the behavior of applications. Examples include `PATH`, `HOME`, `USER`, and many others. [Learn more on Wikipedia](https://en.wikipedia.org/wiki/Environment_variable)."}
-{"_id": 3, "title": "", "text": "## How to Read a File in Python?
I'm trying to read the contents of a file in Python. What is the best way to do this?
### Answer 1
You can use the `open()` function to read a file in Python. Here is an example:
```python
with open('example.txt', 'r') as file:
contents = file.read()
print(contents)
```
This code will open the file `example.txt` for reading, read its contents, and print them to the console."}
-{"_id": 4, "title": "", "text": "```java
import java.io.File;
public class CreateDirectory {
public static void main(String[] args) {
File dirs = new File(\"/path/to/parent/dirs\");
boolean result = dirs.mkdirs();
if(result) {
System.out.println(\"Directories created successfully\");
} else {
System.out.println(\"Failed to create directories\");
}
}
}
```"}
-{"_id": 5, "title": "", "text": "## Creating and Navigating Directories in Java
In Java, you can use the `Files` class to create directories. For example:
```java
import java.nio.file.Files;
import java.nio.file.Paths;
import java.io.IOException;
public class CreateDirectory {
public static void main(String[] args) {
try {
Files.createDirectories(Paths.get(\"/path/to/directory\"));
} catch (IOException e) {
e.printStackTrace();
}
}
}
```
This code creates a directory and any missing parent directories specified in the path."}
-{"_id": 6, "title": "", "text": "```markdown
## What is the difference between private, protected, and public class members in Python?
I'm trying to understand the different access modifiers in Python. Could someone explain private, protected, and public class members?
### Answer:
In Python, there isn't strict enforcement of private, protected, and public class members like in some other languages (e.g., Java or C++). However, there's a naming convention that indicates how these members should be accessed:
- **Public members**: These are accessible anywhere.
- **Protected members**: Indicated by a single underscore `_`, suggesting they're intended for internal use only and shouldn't be accessed from outside the class.
- **Private members**: Indicated by a double underscore `__`, making name mangling to prevent access from outside the class.
```"}
-{"_id": 7, "title": "", "text": "```javascript
class Example {
static staticMethod() {
console.log('This is a static method.');
}
static classMethod() {
return new this();
}
}
Example.staticMethod();
Example.classMethod();
```"}
-{"_id": 8, "title": "", "text": "```markdown
# Python Official Documentation: Built-in Functions
This section covers the built-in functions provided by Python. Built-in functions are always available for use. For a complete list, refer to the [official documentation](https://docs.python.org/3/library/functions.html).
## Commonly Used Functions
- **abs()**: Return the absolute value of a number.
- **all()**: Return True if all elements of the iterable are true.
- **any()**: Return True if any element of the iterable is true.
- **ascii()**: Return a string containing a printable representation of an object.
```
"}
-{"_id": 9, "title": "", "text": "### Title: How to filter rows in a Pandas DataFrame
**Question:**
I'm trying to filter rows in a Pandas DataFrame based on certain conditions. What is the best way to achieve this?
**Answer:**
You can use the `loc` or `iloc` methods to filter rows. For example:
```python
import pandas as pd
# Sample DataFrame
df = pd.DataFrame({'A': [10, 20, 30, 40], 'B': [50, 60, 70, 80]})
# Filter rows where column A is greater than 20
filtered_df = df.loc[df['A'] > 20]
print(filtered_df)
```
This will result in:
```
A B
2 30 70
3 40 80
```
You can also chain multiple conditions using `&` (and) and `|` (or)."}
-{"_id": 10, "title": "", "text": "```javascript
const data = [{ name: 'Alice', age: 25 }, { name: 'Bob', age: 30 }];
data.forEach(row => {
console.log(`${row.name} is ${row.age} years old`);
});
```"}
-{"_id": 11, "title": "", "text": "# Reading Data into a Pandas DataFrame
To begin working with data in a Pandas DataFrame, you first need to read the data into the DataFrame format. This can typically be done using the `read_csv` function for CSV files or `read_excel` for Excel files. Here is an example of how you can read a CSV file into a Pandas DataFrame:
```python
import pandas as pd
df = pd.read_csv('data.csv')
```
For more information, please refer to the [Pandas official documentation](https://pandas.pydata.org/pandas-docs/stable/).
"}
-{"_id": 12, "title": "", "text": "```markdown
### How to use variables in Python functions?
In Python, you can declare variables inside a function to limit their scope to that function. Here's an example of a local variable in a function:
```python
def my_function():
local_variable = 10
print(local_variable)
my_function() # This will print 10
print(local_variable) # This will raise an error as local_variable is not defined outside the function
```
```"}
-{"_id": 13, "title": "", "text": "```java
public class GlobalVarExample {
static int globalVar = 10;
public static void main(String[] args) {
modifyGlobalVar();
System.out.println(globalVar);
}
public static void modifyGlobalVar() {
globalVar = 20;
}
}
```"}
-{"_id": 14, "title": "", "text": "### Introduction to Python Variables
In Python, variables are used to store data that can be manipulated and referenced. They can hold values such as numbers, strings, lists, dictionaries, and more. Variables in Python are dynamically typed, meaning that their data type is inferred at runtime.
Example:
```python
x = 10
y = 'Hello, World!'
```
For more detailed information, you can refer to the [official Python documentation on variables](https://docs.python.org/3/tutorial/introduction.html#numbers-strings-and-variables)."}
-{"_id": 15, "title": "", "text": "```markdown
### How to Convert List to String in Python 3?
I'm trying to convert a list of integers to a single string in Python 3. What would be the best approach to achieve this?
#### Example:
```python
my_list = [1, 2, 3, 4, 5]
result = ''.join(map(str, my_list))
print(result) # Output: '12345'
```
Any help would be appreciated!
```"}
-{"_id": 16, "title": "", "text": "```javascript
let buffer = new Buffer('Hello World');
let str = buffer.toString('utf-8');
console.log(str);
```"}
-{"_id": 17, "title": "", "text": "# Understanding Bytes and Strings in Python 3
In Python 3, strings are sequences of Unicode characters. On the other hand, bytes are sequences of bytes (8-bit values). It is important to differentiate between the two as they serve different purposes in data handling and manipulation.
Refer to the [official Python documentation](https://docs.python.org/3) for more details on the differences between bytes and strings.
"}
-{"_id": 18, "title": "", "text": "# How to get the current time in Java
You can use the `java.time.LocalTime` class to get the current time in Java. Here's a simple example:
```java
import java.time.LocalTime;
public class CurrentTime {
public static void main(String[] args) {
LocalTime currentTime = LocalTime.now();
System.out.println(\"Current time: \" + currentTime);
}
}
```
This will print the current time in hours, minutes, and seconds."}
-{"_id": 19, "title": "", "text": "```javascript
let currentTime = new Date().toLocaleTimeString();
console.log(currentTime);
```"}
-{"_id": 20, "title": "", "text": "# String Methods in Python
Python provides a range of string methods which are useful for various text processing tasks. For instance, `str.lower()` converts a string to lowercase, whereas `str.upper()` converts a string to uppercase. Another useful method is `str.split(separator)` which splits a string into a list based on a given separator. These methods make string manipulation extremely easy and intuitive in Python."}
-{"_id": 21, "title": "", "text": "# Handling Multiple Exceptions in Python
Is it possible to catch multiple exceptions in Python in a single try block? I've been trying to handle different exception types differently but I don't want to repeat the same try-except structure. Any suggestions?"}
-{"_id": 22, "title": "", "text": "```java
try {
// some code that may throw exceptions
} catch (IOException | SQLException ex) {
// handle exceptions
}
```"}
-{"_id": 23, "title": "", "text": "# Exception Handling in Python
In Python, exceptions are errors that occur during the execution of a program. They disrupt the normal flow of the program's instructions. Exceptions need to be caught and handled to prevent the program from crashing.
To handle exceptions, Python provides the `try` and `except` blocks. The `try` block contains the code that may raise an exception, while the `except` block contains the code that handles the exception. If no exception occurs, the code inside the `except` block is not executed.
```python
try:
# code that may raise an exception
except ExceptionType:
# handle the exception
```"}
-{"_id": 24, "title": "", "text": "```markdown
### How to copy a list in Python?
I need to create a duplicate of a list in Python. What is the most efficient way to accomplish this?
**Answer:**
You can use the `copy` module or list slicing to duplicate a list.
```python
import copy
# Using copy
original_list = [1, 2, 3, 4]
duplicated_list = copy.copy(original_list)
# Using list slicing
duplicated_list = original_list[:]
```
```"}
-{"_id": 25, "title": "", "text": "```javascript
// Using JavaScript to copy a file
const fs = require('fs');
function copyFile(source, destination) {
fs.copyFile(source, destination, (err) => {
if (err) throw err;
console.log('File was copied to destination');
});
}
copyFile('source.txt', 'destination.txt');
```"}
-{"_id": 26, "title": "", "text": "```markdown
# Introduction to File Handling in Python
File handling is an important concept in programming. Python provides several functions to create, read, update, and delete files. File handling concept is mainly used in saving information on system memory or external memory, like text files or binary files.
### Opening a File in Python
To open a file, you can use the `open()` function. It requires a file name and a mode parameter to specify the actions you want to perform on the file.
```python
file = open('example.txt', 'r')
```
In this example, we open a file named 'example.txt' in read mode.
```"}
-{"_id": 27, "title": "", "text": "## How to split a string in Python?
I'm trying to split a string into a list in Python. For example, I want to split the string 'Hello, World, Python' by the comma character. How can I achieve this?
```python
s = 'Hello, World, Python'
list_of_words = s.split(', ')
print(list_of_words)
# Output: ['Hello', 'World', 'Python']
```"}
-{"_id": 28, "title": "", "text": "```java
public class Main {
public static void main(String[] args) {
String text = \"Hello, World!\";
if (text.contains(\"World\")) {
System.out.println(\"Text contains 'World'\");
}
}
}
```"}
-{"_id": 29, "title": "", "text": "# Overview of Strings in Java
In Java, you can check if a string contains a specific substring by using the `contains()` method of the `String` class.
```java
String str = \"Hello, world!\";
boolean contains = str.contains(\"world\");
System.out.println(contains); // Outputs true
```
This method returns `true` if and only if this string contains the specified sequence of char values."}
-{"_id": 30, "title": "", "text": "## How to Delete a File in JavaScript?
You can use the `fs` module in Node.js to delete a file. Here is an example:
```javascript
const fs = require('fs');
fs.unlink('path/to/file', (err) => {
if (err) {
console.error(err);
return;
}
console.log('File deleted');
});
```
Make sure you have the `path/to/file` set to the correct file path you want to delete."}
-{"_id": 31, "title": "", "text": "```java
import java.io.File;
public class DeleteFile {
public static void main(String[] args) {
File myFile = new File(\"filename.txt\");
if (myFile.delete()) {
System.out.println(\"Deleted the file: \" + myFile.getName());
} else {
System.out.println(\"Failed to delete the file.\");
}
}
}
```"}
-{"_id": 32, "title": "", "text": "# Introduction to Python Modules
Python offers a wide range of modules for performing various operations. Here, we are going to introduce some core modules like `numpy` for numerical operations, `pandas` for data manipulation, `requests` for making HTTP requests, and `os` for operating system-related tasks. Each module has its own documentation and examples, which are essential to understand for efficient programming."}
-{"_id": 33, "title": "", "text": "### How to determine if an array is empty in JavaScript?
To check if an array is empty in JavaScript, you can use the .length property:
```javascript
let array = [];
if (array.length === 0) {
console.log('Array is empty');
} else {
console.log('Array is not empty');
}
```
This code checks if the length of the array is zero."}
-{"_id": 34, "title": "", "text": "```javascript
let list = [];
if (list.length === 0) {
console.log('List is empty');
}
```"}
-{"_id": 35, "title": "", "text": "# Checking if a String is Empty in Python
In this section, we'll cover how to check if a string is empty in Python. An empty string is represented as `''`. You can use the `len()` function to check its length:
```python
my_string = ''
if len(my_string) == 0:
print('String is empty')
else:
print('String is not empty')
```
Alternatively, you can use a simple conditional check:
```python
my_string = ''
if not my_string:
print('String is empty')
else:
print('String is not empty')
```"}
-{"_id": 36, "title": "", "text": "## How to Check if a File Exists in JavaScript?
You can use the Node.js `fs` module to check if a file exists in JavaScript. Here’s a simple example:
```javascript
const fs = require('fs');
fs.access('path/to/file', fs.constants.F_OK, (err) => {
console.log(`${err ? 'no access!' : 'file exists'}`);
});
```"}
-{"_id": 37, "title": "", "text": "```javascript
const fs = require('fs');
fs.access('path/to/file', fs.constants.F_OK, (err) => {
if (err) {
console.error('File does not exist');
} else {
console.log('File exists');
}
});
```"}
-{"_id": 38, "title": "", "text": "## How to Handle File Exceptions in Java
To handle file exceptions in Java, you can use the `try-catch` block. Here is an example:
```java
try {
File file = new File(\"example.txt\");
if (file.exists() && !file.isDirectory()) {
System.out.println(\"File exists\");
}
} catch (IOException e) {
e.printStackTrace();
}
```This code checks if the file exists and prints a message to the console if it does."}
-{"_id": 39, "title": "", "text": "```markdown
### How do I concatenate two lists in Java?
To concatenate two lists in Java, you can use the `addAll()` method of the `ArrayList` class. Here's an example:
```java
import java.util.ArrayList;
import java.util.List;
public class Main {
public static void main(String[] args) {
List list1 = new ArrayList<>();
list1.add(1);
list1.add(2);
List list2 = new ArrayList<>();
list2.add(3);
list2.add(4);
list1.addAll(list2);
System.out.println(list1); // Output: [1, 2, 3, 4]
}
}
```
```"}
-{"_id": 40, "title": "", "text": "```java
// Concatenating two arrays in Java
int[] array1 = {1, 2, 3};
int[] array2 = {4, 5, 6};
int[] result = new int[array1.length + array2.length];
System.arraycopy(array1, 0, result, 0, array1.length);
System.arraycopy(array2, 0, result, array1.length, array2.length);
```"}
-{"_id": 41, "title": "", "text": "# Python Documentation: Lists
Lists in Python are ordered collections of elements. They can contain elements of different types, but typically contain elements of the same type. Lists are mutable, meaning that they can be modified after creation. Here is how you can create a list:
```python
my_list = [1, 2, 3, 4]
```
You can access elements using index notation:
```python
print(my_list[0]) # Outputs: 1
```"}
-{"_id": 42, "title": "", "text": "### How do I change the size of legends in Matplotlib?
I have a plot with several lines, and the legend is too large. How can I change the font size or overall size of the legend?
```python
import matplotlib.pyplot as plt
plt.plot(x, y, label='data')
plt.legend(fontsize='small')
plt.show()
```
**Answer:** You can change the size of the legend by adjusting the `fontsize` parameter in the `legend` function as shown above."}
-{"_id": 43, "title": "", "text": "```javascript
const data = [
{ x: 1, y: 5 },
{ x: 2, y: 10 },
{ x: 3, y: 15 }
];
const svg = d3.select('svg');
const width = 500;
const height = 300;
svg.attr('width', width).attr('height', height);
const xScale = d3.scaleLinear().domain([0, d3.max(data, d => d.x)]).range([0, width]);
const yScale = d3.scaleLinear().domain([0, d3.max(data, d => d.y)]).range([height, 0]);
const line = d3.line()
.x(d => xScale(d.x))
.y(d => yScale(d.y));
svg.append('path').datum(data).attr('d', line).attr('fill', 'none').attr('stroke', 'blue');
```"}
-{"_id": 44, "title": "", "text": "# Introduction to Matplotlib
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+."}
-{"_id": 45, "title": "", "text": "# How to change text color in C++ terminal?
I'm trying to print colored text to the terminal using C++. What libraries or methods can I use to achieve this? Any example code would be appreciated."}
-{"_id": 46, "title": "", "text": "```python
import os
# Check if the terminal supports color
if os.name == 'nt':
os.system('')
# This function does nothing related to coloring text
print('Hello, World!')
```"}
-{"_id": 47, "title": "", "text": "## Introduction to Python Printing
In Python, printing is performed using the `print()` function. The function can take any number of arguments, and it will convert them to a string representation and output them to the standard output (typically the console).
Example:
```python
print('Hello, World!')
```
This prints 'Hello, World!' to the terminal."}
-{"_id": 48, "title": "", "text": "### What is the difference between Python's list and tuple?
**Question:**
I am trying to understand the main differences between a list and a tuple in Python. Can someone explain?
**Answer:**
In Python, lists and tuples both are sequence data types that can store a collection of items. However, the key differences are:
- **List:** Lists are mutable, meaning you can change, add, or remove items after the list is created.
- **Tuple:** Tuples are immutable, meaning once a tuple is created, you can't change its content.
Use a list when you need a mutable, ordered collection of items. Use a tuple when you need an immutable ordered collection of items."}
-{"_id": 49, "title": "", "text": "```javascript
// This JavaScript snippet shows array methods for adding elements
let arr = [1, 2, 3];
arr.push(4); // Adds a single element to the end of the array
arr = arr.concat([5, 6]); // Merges the array with another array
console.log(arr); // Output: [1, 2, 3, 4, 5, 6]
```"}
-{"_id": 50, "title": "", "text": "# Understanding Python's list.insert Method
The `insert()` method inserts a given element at a specified index in the list. It is different from `append` and `extend` as it allows placement of elements at any position within the list.
```python
my_list = [1, 2, 3, 4]
my_list.insert(2, 'a')
print(my_list) # Output: [1, 2, 'a', 3, 4]
```
Refer to the [Python documentation](https://docs.python.org/3/tutorial/datastructures.html) for more details."}
-{"_id": 51, "title": "", "text": "```markdown
Title: How to get the current time in Python?
Question: I need to retrieve the current timestamp in my Python program. What's the best way to do this?
Answer: You can use the `datetime` module from the Python standard library to get the current time:
```python
import datetime
current_time = datetime.datetime.now()
print(current_time)
```
```"}
-{"_id": 52, "title": "", "text": "```javascript
const fs = require('fs');
const path = require('path');
// To get the current directory
const currentDir = process.cwd();
console.log(`Current directory: ${currentDir}`);
// To get the directory of the current file
const fileDir = __dirname;
console.log(`File directory: ${fileDir}`);
```"}
-{"_id": 53, "title": "", "text": "## Python's time Module Official Documentation
The `time` module provides various time-related functions. For more extensive functionality, consider the `datetime` module. `time.time()` returns the current time in seconds since the Epoch as a floating point number."}
-{"_id": 54, "title": "", "text": "### Question
How to create a new column in a Pandas DataFrame based on the values of another column?
I have a DataFrame in Python using Pandas. I want to create a new column that summarizes the information from an existing column. How can I achieve this?
### Answer
You can create a new column in a Pandas DataFrame by using the following method:
```python
import pandas as pd
data = {'existing_column': [1, 2, 3, 4, 5]}
df = pd.DataFrame(data)
df['new_column'] = df['existing_column'] * 2
print(df)
```
This code will create a new column in the DataFrame based on the values of `existing_column`."}
-{"_id": 55, "title": "", "text": "```r
# Renaming columns in an R data frame
colnames(dataframe) <- c('new_name1', 'new_name2', 'new_name3')
```"}
-{"_id": 56, "title": "", "text": "# DataFrame Creation
To create a DataFrame in pandas, you can use the `pd.DataFrame()` function, passing a dictionary where keys are the column names, and values are the data:
```python
import pandas as pd
data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)
print(df)
```
This will produce a DataFrame with the columns 'Name' and 'Age'."}
-{"_id": 57, "title": "", "text": "### How to iterate over a Python dictionary
To iterate over a dictionary in Python, you can use a for loop. For example:
```python
my_dict = {'a': 1, 'b': 2, 'c': 3}
for key, value in my_dict.items():
print(f'Key: {key}, Value: {value}')
```
This will output:
```
Key: a, Value: 1
Key: b, Value: 2
Key: c, Value: 3
```"}
-{"_id": 58, "title": "", "text": "```ruby
# Removing a key from a Hash in Ruby
hash = { a: 1, b: 2, c: 3 }
hash.delete(:b)
# {:a=>1, :c=>3}
```"}
-{"_id": 59, "title": "", "text": "## Introduction to Python Dictionaries
A dictionary is a collection which is unordered, changeable, and indexed. In Python, dictionaries are written with curly brackets, and they have keys and values.
Example:
```python
thisdict = {
\"brand\": \"Ford\",
\"model\": \"Mustang\",
\"year\": 1964
}
print(thisdict)
```"}
-{"_id": 60, "title": "", "text": "### How to remove duplicates from a list in Python?
I'm trying to remove duplicates from a list and keep the order of elements. How can I achieve this in Python?
```python
my_list = [1, 2, 2, 3, 4, 4, 5]
result = list(dict.fromkeys(my_list))
print(result)
```
This prints: `[1, 2, 3, 4, 5]`"}
-{"_id": 61, "title": "", "text": "```java
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class SortExample {
public static void main(String[] args) {
List