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a p�h�K � @ s� d Z ddlmZ ddlmZ ddlmZ ddlmZ ddlZddlmZ ddl Z ddl Z dd l mZ dd lmZ d d � Zd d� ZG dd� de�ZdS )z DataFrame client for InfluxDB.� )�absolute_import)�division)�print_function)�unicode_literalsN)� defaultdict� )�InfluxDBClient�� _escape_tagc C s< | }| dkrd}n| dkr d}n | dkr,d}|dv s8J �|S )N�m�ms�u�us�n�ns)�sr r r � )�time_precision�unitr r ��/root/rpmbuild/BUILDROOT/imh-python39-modules-3.9.7-92.el8.x86_64/opt/imh-python/lib/python3.9/site-packages/influxdb/_dataframe_client.py�_pandas_time_unit s r c C s | � dd� �S )Nc S s t | �S )Nr )�vr r r �<lambda> � z'_escape_pandas_series.<locals>.<lambda>)�apply�r r r r �_escape_pandas_series s r c st e Zd ZdZe�d�Zd� fdd� Zd� fd d � Zd dd�Z e d dd��Z d dd�Z e d dd��Z d dd�Z� ZS )!�DataFrameClienta DataFrameClient instantiates InfluxDBClient to connect to the backend. The ``DataFrameClient`` object holds information necessary to connect to InfluxDB. Requests can be made to InfluxDB directly through the client. The client reads and writes from pandas DataFrames. z 1970-01-01 00:00:00.000+00:00N�linec s |du r g }|du rg }| r�t t�t|�t| � ��} t| �D ]�} | | }| d | }| dkr�| j|j||� �� |||||| d�}n$| j |j||� �� |||||d�}t t | �j ||||| d� q>dS | dkr�| j||||||| d�}n| j ||||||d�}t t | �j ||||| d� dS ) a� Write to multiple time series names. :param dataframe: data points in a DataFrame :param measurement: name of measurement :param tags: dictionary of tags, with string key-values :param tag_columns: [Optional, default None] List of data tag names :param field_columns: [Options, default None] List of data field names :param time_precision: [Optional, default None] Either 's', 'ms', 'u' or 'n'. :param batch_size: [Optional] Value to write the points in batches instead of all at one time. Useful for when doing data dumps from one database to another or when doing a massive write operation :type batch_size: int :param protocol: Protocol for writing data. Either 'line' or 'json'. :param numeric_precision: Precision for floating point values. Either None, 'full' or some int, where int is the desired decimal precision. 'full' preserves full precision for int and float datatypes. Defaults to None, which preserves 14-15 significant figures for float and all significant figures for int datatypes. 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Only works in the ``WHERE`` clause and takes precedence over ``params['params']`` :param epoch: response timestamps to be in epoch format either 'h', 'm', 's', 'ms', 'u', or 'ns',defaults to `None` which is RFC3339 UTC format with nanosecond precision :param expected_response_code: the expected status code of response, defaults to 200 :param database: database to query, defaults to None :param raise_errors: Whether or not to raise exceptions when InfluxDB returns errors, defaults to True :param chunked: Enable to use chunked responses from InfluxDB. With ``chunked`` enabled, one ResultSet is returned per chunk containing all results within that chunk :param chunk_size: Size of each chunk to tell InfluxDB to use. :param dropna: drop columns where all values are missing :param data_frame_index: the list of columns that are used as DataFrame index :returns: the queried data :rtype: :class:`~.ResultSet` ) �params� bind_params�epoch�expected_response_code� raise_errors�chunkedr3 �method� chunk_sizeZSELECTr )�data_frame_indexN) �dictr/ r �query�strip�upper� startswithr) � _to_dataframe)r1 rE r; r< r= r> r3 r? r@ rB rA �dropnarC Z query_args�resultsr7 r r rE � s$ .� �zDataFrameClient.queryc s t t�}t|t�r6t| j|� fdd�tt|��D ��S |�� D ]�\}}|\}}|d u r\|}n|tt |�� ��f}t � |�} t � | j �| _ |r�| j|dd� n0| jddd� | jjd u r�| j�d�| _d | j_|| �| � q>|�� D ]4\}}t �|��� } � �r| jdddd � | ||< q�|S ) Nc s g | ]}� �qS r r )�.0�_�rJ r r � <listcomp>� r z1DataFrameClient._to_dataframe.<locals>.<listcomp>T)�inplace�time�UTC�allr )�how�axisrP )r �list� isinstance�maprI r+ r) �items�tuple�sorted�pd� DataFrame� to_datetimerQ Z set_index�index�tzinfo� tz_localize�name�append�concat� sort_indexrJ ) r1 �rsrJ rC �result�key�datarb r$ �dfr rN r rI � s2 � z DataFrameClient._to_dataframec sZ t | tj�s td�t| ����t | jtj�sBt | jtj�sBtd��|d urN|ng }|d ur^|ng }�d urn�ni �|s�t t | j �� t |���}t | jtj�s�t� | j�| _| jjd u r�| j�d�| _| j �d�| _ | �d�} dddd d d d ��|d��|�s$� �fd d�t| j| | �� �D �}|S � ��fdd�t| j| | �d�| | �� �D �}|S )N�%Must be DataFrame, but type was: {0}.�4Must be DataFrame with DatetimeIndex or PeriodIndex.rR �str�objectr � @�@� ��.A� e��A� ���+B� Ņ1�B�r r r r r �hc sH g | ]@\}\}}� |� tjtj gtj��� �� t�|j� �d ��qS ))r �fieldsrQ )�replace�np�inf�nanrJ �to_dict�int64�value)rL �tsrM �rec)r �precision_factorr r rO s � �z>DataFrameClient._convert_dataframe_to_json.<locals>.<listcomp>c sd g | ]\\}}\}}� t t|�� �t��� � �|�tjtj gtj��� �� t� |j � �d ��qS ))r r$ rv rQ ) rD rV rY rw rx ry rz rJ r{ r| r} )rL r~ �tagrM r �r r� r$ r r rO , s � ��record)rW r\ r] � TypeError�format�typer_ � PeriodIndex� DatetimeIndexrV �set�columns� differencer^ r` ra �astype�get�zipZiterrowsr{ )r2 r r$ r! r" r r6 r r� r r. � s\ � �� �� �� �� z*DataFrameClient._convert_dataframe_to_jsonc C s� |j dd��� }t|�dkr g S t|tj�s>td�t|����t|j tj �sbt|j tj �sbtd��|j dd� |j D �d�}t�|j �}|d u r�g }|d u r�g }|d u r�i }t|�r�t|�ng }t|�r�t|�ng }|r�|s�t||�|� �}|�st||�|� �}d d d d d dd��|d �} t|j tj ��rZ|j �� j�tj�| �tj��t�} n(t�|j �j�tj�| �tj��t�} |�r�|�r�|D ] } || || < |�| � �q�|| } | �d�} | jd d�} | j | |dd�} | � dd� �} | j d d�} ~ n8|�r0d� dd� t |�!� �D ��}tj||j d�} nd} || �"tj#tj# gtj$�}t�%|�}| j ||dd�}|j jd �&� | }d||j d d � ||j d d � < d||< |j d d��'d d� �}~t(|�}|| d | d | �&� }|S ) NrS )rT r rk rl c S s i | ]}|t |��qS r r )rL �itemr r r � <dictcomp>Q r z?DataFrameClient._convert_dataframe_to_lines.<locals>.<dictcomp>)r� r ro rp rq rr rs rt � )rU r� )�datatypec s � fdd�� D �S )Nc s& g | ] }|r d � j d | nd�qS )�,�=r� )rb )rL r r r r rO � r zQDataFrameClient._convert_dataframe_to_lines.<locals>.<lambda>.<locals>.<listcomp>r r r r r r � r z=DataFrameClient._convert_dataframe_to_lines.<locals>.<lambda>c S s, g | ]$\}}|d vr$d� |t|��nd�qS ))Nr� z,{}={}r� )r� r )rL �kr r r r rO � s ��z?DataFrameClient._convert_dataframe_to_lines.<locals>.<listcomp>)r_ �fieldr� r� c S s | � d�S )Nr� )�lstrip)�xr r r r � r � ))rJ r- r) rW r\ r] r� r� r� r_ r� r� �renamer� ZSeriesrV �isinr� Z to_timestamp�valuesr� rx r| rm r^ rc Zfillnare �_stringify_dataframer �sum�joinr[ rY rw ry rz Zisnull�tolistrX r )r1 r2 r r" r! r r r# Z column_seriesr� rQ r� Ztag_dfr$ Z tag_stringZfield_dfZnansrv r6 r r r r, ; s� � �� � � �� ������ �� �� �$ z+DataFrameClient._convert_dataframe_to_linesr� c C sh | � � } | jdgd�j}| jdgd�j}|d u r<| �t�} n�|dkr�| jdgd�j}| j| j�|� }| | �t�| |< | | �t�| |< n�t|t ��r | jdgd�j}| j| j�|� }| | � |�| |< |dkr�| | �t�| |< | | �t�| |< n | �t�} nt d��|dk�rB| | d 7 < d | | d | |< n|d k�rV| � t �} | j�t�| _| S ) N�integer)�includern �fullZfloating� zInvalid numeric precision.r� �i�"r� )r- Z select_dtypesr� r� rm r� Zapplymap�reprrW r& �round� ValueErrorr r )Zdframer# r� Z int_columnsZstring_columnsZ float_columnsZnonfloat_columnsr r r r� � sL � � � ��� z$DataFrameClient._stringify_dataframer c C sn || j �� }|dkr |d S |dkr.|d S |dkr:|S |dkrJ|d S |dkrZ|d S |d krj|d S d S ) Nru i r �< r r ro r rp r rq )�EPOCH� total_seconds)r1 �datetimer �secondsr r r �_datetime_to_epoch� s z"DataFrameClient._datetime_to_epoch) NNNNNNNr N) NNNr9 NTFr r: TN)TN)NNNN)NNNNN)r� )r )�__name__� __module__� __qualname__�__doc__r\ � Timestampr� r0 rE rI � staticmethodr. r, r� r� � __classcell__r r r7 r r # sP �e �A � L � u 3r )r� � __future__r r r r r' � collectionsr Zpandasr\ �numpyrx �clientr Z line_protocolr r r r r r r r �<module> s
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