#!/usr/bin/env python
# coding: utf-8

# In[1]:


import pandas as pd
import dolphindb as ddb
import query


# In[2]:


s = ddb.session("127.0.0.1", 8848, 'testUser2', '123456')


# In[12]:


# Access all table data.
df = query.query(session=s, startDate='2015.01.01', endDate='2024.12.31')


# In[19]:


# Access data of the specified securities and columns for February 2024.
df = query.query(session=s, startDate='2024.02.01', endDate='2024.02.29', security='`000001', cols='`SecurityID`date`time`col1`col2`col3`col4`col5`col6`col7`col8`col9`col10')


# In[7]:


# Access all data from the last year.
df = query.queryRecentYear(session=s)


# In[29]:


# Access data from a specified start date and specified columns.
df = query.queryRecentYear(session=s, startDate='2023.07.01', cols='`SecurityID`date`time`col2`col3')


# In[33]:


# Access all accessible columns for the specified securities in 2023.
df = query.queryFirst10Col(session=s, startDate='2023.01.01', endDate='2023.12.31', security='`000008`000009`000010')


# In[35]:


# Access data of the specified columns for December 2022.
df = query.queryFirst10Col(session=s, startDate='2022.12.01', endDate='2022.12.31', cols='`SecurityID`date`time`col4`col5`col6')


# In[37]:


# Access all accessible columns for January 2021.
df = query.queryCond(session=s, startDate='2021.01.01', endDate='2021.01.31')


# In[39]:


# Access data of the specified columns in 2021.
df = query.queryCond(session=s, startDate='2021.01.01', endDate='2021.12.31', cols='`SecurityID`date`time`col47`col48`col49')