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_bootlocale.cpython-39.pyc
1.21
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2023-08-17 09:29
_collections_abc.cpython-39.pyc
31
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2023-08-17 09:29
_compat_pickle.cpython-39.pyc
5.37
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2023-08-17 09:29
_compression.cpython-39.pyc
4.11
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2023-08-17 09:29
_sitebuiltins.cpython-39.pyc
3.43
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2023-08-17 09:29
_weakrefset.cpython-39.pyc
7.55
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abc.cpython-39.pyc
5.65
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ast.cpython-39.pyc
51.09
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base64.cpython-39.pyc
16.08
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2023-08-17 09:29
bisect.cpython-39.pyc
2.3
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2023-08-17 09:29
bz2.cpython-39.pyc
11.28
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2023-08-17 09:29
calendar.cpython-39.pyc
26.41
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2023-08-17 09:29
codecs.cpython-39.pyc
33.1
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contextlib.cpython-39.pyc
19.09
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copyreg.cpython-39.pyc
4.34
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datetime.cpython-39.pyc
56.76
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2023-08-17 09:29
dis.cpython-39.pyc
15.46
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2023-08-17 09:29
enum.cpython-39.pyc
25.42
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2023-08-17 09:29
fnmatch.cpython-39.pyc
3.86
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functools.cpython-39.pyc
28.06
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2023-08-17 09:29
genericpath.cpython-39.pyc
3.94
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2023-08-17 09:29
hashlib.cpython-39.pyc
6.54
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2023-08-17 09:29
heapq.cpython-39.pyc
13.72
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2023-08-17 09:29
inspect.cpython-39.pyc
79.57
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2023-08-17 09:29
io.cpython-39.pyc
3.34
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2023-08-17 09:29
keyword.cpython-39.pyc
926
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2023-08-17 09:29
linecache.cpython-39.pyc
3.94
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2023-08-17 09:29
locale.cpython-39.pyc
33.89
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2023-08-17 09:29
lzma.cpython-39.pyc
11.82
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2023-08-17 09:29
ntpath.cpython-39.pyc
14.21
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2023-08-17 09:29
opcode.cpython-39.pyc
5.11
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2023-08-17 09:29
operator.cpython-39.pyc
13.47
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2023-08-17 09:29
os.cpython-39.pyc
30.91
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2023-08-17 09:29
pathlib.cpython-39.pyc
43.69
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2023-08-17 09:29
pickle.cpython-39.pyc
46
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2023-08-17 09:29
platform.cpython-39.pyc
25.81
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2023-08-17 09:29
posixpath.cpython-39.pyc
10.1
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2023-08-17 09:29
quopri.cpython-39.pyc
5.62
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2023-08-17 09:29
random.cpython-39.pyc
21.54
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2023-08-17 09:29
re.cpython-39.pyc
14.04
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reprlib.cpython-39.pyc
5.19
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selectors.cpython-39.pyc
16.85
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shutil.cpython-39.pyc
37.43
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signal.cpython-39.pyc
2.95
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2023-08-17 09:29
site.cpython-39.pyc
16.41
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2023-08-17 09:29
socket.cpython-39.pyc
28.5
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2023-08-17 09:29
sre_compile.cpython-39.pyc
14.81
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2023-08-17 09:29
sre_constants.cpython-39.pyc
6.2
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2023-08-17 09:29
sre_parse.cpython-39.pyc
21.31
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2023-08-17 09:29
ssl.cpython-39.pyc
43.56
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2023-08-17 09:29
stat.cpython-39.pyc
4.28
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2023-08-17 09:29
string.cpython-39.pyc
7.01
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2023-08-17 09:29
struct.cpython-39.pyc
316
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2023-08-17 09:29
subprocess.cpython-39.pyc
43.12
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2023-08-17 09:29
tempfile.cpython-39.pyc
22.88
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2023-08-17 09:29
threading.cpython-39.pyc
41.2
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2023-08-17 09:29
token.cpython-39.pyc
2.45
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2023-08-17 09:29
tokenize.cpython-39.pyc
16.77
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2023-08-17 09:29
types.cpython-39.pyc
9.03
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2023-08-17 09:29
typing.cpython-39.pyc
70.26
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2023-08-17 09:29
uu.cpython-39.pyc
3.59
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2023-08-17 09:29
warnings.cpython-39.pyc
13.3
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2023-08-17 09:29
weakref.cpython-39.pyc
19.82
KB
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2023-08-17 09:29
zipfile.cpython-39.pyc
57.69
KB
-rw-r--r--
2023-08-17 09:29
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Used to instantiate instances of Random to get generators that don't share state. Class Random can also be subclassed if you want to use a different basic generator of your own devising: in that case, override the following methods: random(), seed(), getstate(), and setstate(). Optionally, implement a getrandbits() method so that randrange() can cover arbitrarily large ranges. � Nc C s | � |� d| _dS )zeInitialize an instance. Optional argument x controls seeding, as for Random.seed(). N)r' � gauss_next)�self�x� r9 �(/usr/lib/mysqlsh/lib/python3.9/random.py�__init__u s zRandom.__init__r4 c s |dkr�t |ttf�r�t |t�r*|�d�n|}|rBt|d �d> nd}tt|�D ]}d| |A d@ }qP|t|�N }|dkr~dn|}nj|d kr�t |tttf�r�t |t�r�|�� }t � |t |�� � d �}n&t |t d �t ttttf�s�td td � t� �|� d | _d S ) a\ Initialize internal state from a seed. The only supported seed types are None, int, float, str, bytes, and bytearray. None or no argument seeds from current time or from an operating system specific randomness source if available. If *a* is an int, all bits are used. For version 2 (the default), all of the bits are used if *a* is a str, bytes, or bytearray. For version 1 (provided for reproducing random sequences from older versions of Python), the algorithm for str and bytes generates a narrower range of seeds. � zlatin-1r � iCB l ���� ������r4 �bigNz�Seeding based on hashing is deprecated since Python 3.9 and will be removed in a subsequent version. 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Nr< zuThe *random* parameter to shuffle() has been deprecated since Python 3.9 and will be removed in a subsequent version.r4 )rd �reversed�rangerG rO rP rp )r7 r8 r$ � randbelow�i�jr r9 r9 r: r) \ s �zRandom.shuffle)�countsc s� t �t�r tdtd� t���t �t�s0td��t��}|dur�tt |���t��|kr`t d���� � }t |t �sztd��|dkr�t d��| j t|�|d �}t� � ��fd d �|D �S | j}d| kr�|ks�n t d ��dg| }d } |dk�r | dtt|d d�� 7 } || k�r\t��} t|�D ]2} ||| �} | | || < | || d | | < �q&nNt� } | j}t|�D ]8} ||�} | | v �r�||�} �q||| � �| || < �qp|S )am Chooses k unique random elements from a population sequence or set. Returns a new list containing elements from the population while leaving the original population unchanged. The resulting list is in selection order so that all sub-slices will also be valid random samples. This allows raffle winners (the sample) to be partitioned into grand prize and second place winners (the subslices). Members of the population need not be hashable or unique. If the population contains repeats, then each occurrence is a possible selection in the sample. Repeated elements can be specified one at a time or with the optional counts parameter. For example: sample(['red', 'blue'], counts=[4, 2], k=5) is equivalent to: sample(['red', 'red', 'red', 'red', 'blue', 'blue'], k=5) To choose a sample from a range of integers, use range() for the population argument. This is especially fast and space efficient for sampling from a large population: sample(range(10000000), 60) z\Sampling from a set deprecated since Python 3.9 and will be removed in a subsequent version.r4 zAPopulation must be a sequence. 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N� c s g | ]}�� �� � � �qS r9 r9 �rY r� )r rm r� r$ r9 r: r� � r[ z"Random.choices.<locals>.<listcomp>z4The number of choices must be a keyword argument: k=z2Cannot specify both weights and cumulative weightsz3The number of weights does not match the populationr> z*Total of weights must be greater than zeror< c s$ g | ] }�� ��� � d �� �qS )r r9 r� )r r� �hir� r$ r� r9 r: r� � s �) r$ rG rp �_repeatr� r� r^ rA rJ r] r� )r7 r� Zweightsr� rn r9 )r r� r r� rm r� r$ r� r: r � s< �� �zRandom.choicesc C s ||| | � � S )zHGet a random number in the range [a, b) or [a, b] depending on rounding.�r$ r| r9 r9 r: r+ � s zRandom.uniformr� r1 c C sz | � � }z |du rdn|| || }W n ty> | Y S 0 ||krbd| }d| }|| }}||| t|| � S )z�Triangular distribution. Continuous distribution bounded by given lower and upper limits, and having a given mode value in-between. http://en.wikipedia.org/wiki/Triangular_distribution N� �?r1 )r$ �ZeroDivisionError�_sqrt)r7 �low�high�mode�urT r9 r9 r: r* s zRandom.triangularc C sP | j }|� }d|� }t|d | }|| d }|t|� krqDq||| S )z\Normal distribution. mu is the mean, and sigma is the standard deviation. r1 r� r0 )r$ � NV_MAGICCONSTr� )r7 �mu�sigmar$ �u1�u2�zZzzr9 r9 r: r s zRandom.normalvariatec C s` | j }| j}d| _|du rT|� t }tdtd|� � �}t|�| }t|�| | _||| S )z�Gaussian distribution. mu is the mean, and sigma is the standard deviation. This is slightly faster than the normalvariate() function. Not thread-safe without a lock around calls. Ng �r1 )r$ r6 �TWOPIr� r� �_cos�_sin)r7 r� r� r$ r� Zx2piZg2radr9 r9 r: r , s z Random.gaussc C s t | �||��S )z�Log normal distribution. If you take the natural logarithm of this distribution, you'll get a normal distribution with mean mu and standard deviation sigma. mu can have any value, and sigma must be greater than zero. )�_expr )r7 r� r� r9 r9 r: r R s zRandom.lognormvariatec C s t d| �� � | S )a^ Exponential distribution. lambd is 1.0 divided by the desired mean. It should be nonzero. (The parameter would be called "lambda", but that is a reserved word in Python.) Returned values range from 0 to positive infinity if lambd is positive, and from negative infinity to 0 if lambd is negative. r1 )r� r$ )r7 Zlambdr9 r9 r: r \ s zRandom.expovariatec C s� | j }|dkrt|� S d| }|td|| � }|� }tt| �}||| }|� } | d|| k s�| d| t|� kr4q�q4d| } | | d| | } |� } | dkr�|t| � t } n|t| � t } | S )aF Circular data distribution. mu is the mean angle, expressed in radians between 0 and 2*pi, and kappa is the concentration parameter, which must be greater than or equal to zero. If kappa is equal to zero, this distribution reduces to a uniform random angle over the range 0 to 2*pi. g���ư>r� r1 )r$ r� r� r� �_pir� �_acos)r7 r� Zkappar$ r� ro r� r� �dr� �q�fZu3Zthetar9 r9 r: r, m s$ $zRandom.vonmisesvariatec C s~ |dks|dkrt d��| j}|dkr�td| d �}|t }|| }|� }d| k r`dk sdqF qFd|� }t|d| �| } |t| � } || | } ||| | } | t d| dks�| t| �krF| | S qFn�|dkr�td|� � | S |� } t| t }|| }|dk�r$|d| } nt|| | � } |� }|dk�r^|| |d k�rp�qrq�|t| �kr�qrq�| | S dS ) aZ Gamma distribution. Not the gamma function! Conditions on the parameters are alpha > 0 and beta > 0. The probability distribution function is: x ** (alpha - 1) * math.exp(-x / beta) pdf(x) = -------------------------------------- math.gamma(alpha) * beta ** alpha r� z*gammavariate: alpha and beta must be > 0.0r1 r/ gH�����z>g�P���?r2 N)r] r$ r� �LOG4r� r� � SG_MAGICCONST�_e)r7 �alpha�betar$ ZainvZbbbZcccr� r� �vr8 r� ro r� r} �pr9 r9 r: r � s@ zRandom.gammavariatec C s( | � |d�}|r$||| � |d� S dS )z�Beta distribution. 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Not available on all systems (see os.urandom() for details). c C s t �td�d�d? t S )z3Get the next random number in the range [0.0, 1.0).r= r@ r5 )rJ rK �_urandom� RECIP_BPFrX r9 r9 r: r$ s zSystemRandom.randomc C s< |dk rt d��|d d }t�t|�d�}||d | ? S )z:getrandbits(k) -> x. Generates an int with k random bits.r z#number of bits must be non-negativer= rt r@ )r] rJ rK r� )r7 rn Znumbytesr8 r9 r9 r: r s zSystemRandom.getrandbitsc C s t |�S )rs )r� rw r9 r9 r: r" s zSystemRandom.randbytesc O s dS )z<Stub method. 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