def write(year):
util.write_header()
st.markdown("---")
util.write_title("- DISCORD")
discord_text_df = get_discord_text(year)
discord_voice_df = get_discord_voice(year)
if discord_text_df.empty:
st.write("EM DESENVOLVIMENTO")
return None
messages = discord_text_df["messages"].sum()
minutes = round(discord_voice_df["speaking_minutes"].sum(), 2)
hours = round(minutes / 60, 2)
days = round(hours / 24, 2)
year = round(days / 365, 1)
st.markdown(
f"## - No Discord tivemos um total de **{(messages)}** enviadas ")
st.markdown(
f"## - Além disso, nas messas de bar e canais de áudios tivemos **{(minutes)} minutos** de conversas "
)
st.markdown(
f"## - Com um total de **{hours} horas** de áudios, o que dá **{days} dias** consecutivo ouvindo tudo !!"
)
plot_discord(discord_text_df, discord_voice_df)
def write(year):
util.write_header()
st.markdown("---")
util.write_title("- FEEDBACKS")
feedbacks_df = get_event_feedbacks(year)
if feedbacks_df.empty:
st.write("EM DESENVOLVIMENTO")
return None
total = feedbacks_df.shape[0]
st.markdown(
f"## Tivemos um total de **{total}** respostas ao formulário de feedback!!!"
)
plot_who(feedbacks_df)
def write(year):
util.write_header()
st.markdown("---")
util.write_title("- LIVES YOUTUBE")
lives_df = get_lives_tutorials(year)
if lives_df.empty:
st.write("EM DESENVOLVIMENTO")
return None
views = lives_df["Views"].sum()
hours = round(lives_df["Watch time (hours)"].sum(), 2)
days = round(lives_df["Watch time (days)"].sum(), 2)
year = round(days / 365, 1)
st.markdown(f"## - Tivemos um total de **{int(views)}** visualizações ")
st.markdown(
f"## - Com um total de **{hours} horas** de visualizações, o que dá **{days} dias** consecutivo assistindo tudo !!"
)
st.markdown(
f"## **ISSO DÁ PRATICAMENTE {year} ANOS DE CONTÉUDO SEM PARAR !!!**")
plot_youtube(lives_df)
def write(year):
util.write_header()
st.markdown("---")
util.write_title("- PALESTRAS")
tickest_df = get_event_tickets(year)
if tickest_df.empty:
return None
col = "Em qual país você reside?"
tickest_df[col] = tickest_df[col].str.strip()
tickest_df.loc[
tickest_df[col] ==
"Por favor, que formulário mais sem sentido. Querem também saber que orientação sexual vou querer ter na próxima encarnação? Isso não tem sentido.",
col, ] = "N/A"
tickest_df.loc[tickest_df[col] == ",", col] = "N/A"
tickest_df.loc[tickest_df[col] == "PNR", col] = "N/A"
tickest_df.loc[tickest_df[col] == "Prefiro não responder.", col] = "N/A"
tickest_df.loc[tickest_df[col] == "Alemanha, Berlin", col] = "Alemanha"
tickest_df.loc[tickest_df[col] == "Canada", col] = "Canadá"
tickest_df.loc[tickest_df[col] == "Dublin, Irlanda", col] = "Irlanda"
tickest_df.loc[tickest_df[col] == "Ireland", col] = "Irlanda"
tickest_df.loc[tickest_df[col] == "irlanda", col] = "Irlanda"
tickest_df.loc[tickest_df[col] == "Italy", col] = "Itália"
tickest_df.loc[tickest_df[col] == "Mocambique", col] = "Moçambique"
tickest_df.loc[tickest_df[col] == "Países Baixo", col] = "Países Baixos"
tickest_df.loc[tickest_df[col] == "Perú", col] = "Peru"
tickest_df.loc[tickest_df[col] == "US", col] = "EUA"
tickest_df.loc[tickest_df[col] == "USA", col] = "EUA"
tickest_df.loc[tickest_df[col] == "Usa", col] = "EUA"
tickest_df.loc[tickest_df[col] == "Estados Unidos", col] = "EUA"
tickest_df.loc[tickest_df[col] == "United States", col] = "EUA"
tickest_df.loc[tickest_df[col] == "CZ", col] = "República Tcheca"
tickest_df.loc[tickest_df[col] == "United Kingdom", col] = "Reino Unido"
tickest_df.loc[tickest_df[col] == "colombia", col] = "Colombia"
tickest_df.loc[tickest_df[col] == "portugal", col] = "Portugal"
tickest_df.loc[tickest_df[col] == "PT", col] = "Portugal"
tickest_df.loc[tickest_df[col] == "thailand", col] = "Tailandia"
tickest_df.loc[tickest_df[col] == "France", col] = "França"
tickest_df.loc[tickest_df[col] == "Japao", col] = "Japão"
OPTIONS = ["Inscrições", "Quem", "Onde", "Python"]
st.sidebar.title("Dados de Inscrições do Evento")
select_column = st.sidebar.selectbox("", OPTIONS)
if select_column == "Quem":
st.markdown(f"## Detalhes sobre as Quem")
plot_who(tickest_df)
elif select_column == "Onde":
st.markdown(f"## Detalhes sobre as Onde")
plot_where(tickest_df)
elif select_column == "Python":
st.markdown(f"## Detalhes sobre as Python")
plot_python(tickest_df)
elif select_column == "Inscrições":
total = tickest_df.shape[0]
st.markdown(
f"## Tivemos um total de **{total}** inscrições para o evento !!!")
st.markdown(f"## Selecione alguma opção na barra lateral em:")
st.markdown(f"## `Dados de Inscrições do Evento` para ver detalhes.")
else:
st.write("Escolha uma opção")
# Create scripts directory, if it does not exist yet, and cd to it.
if not os.path.exists("samtoolsIndex"):
os.mkdir("samtoolsIndex")
os.chdir("samtoolsIndex")
samplesFile = open("../samples.txt")
samplesLine = samplesFile.readlines()[1::2]
samples = []
lanes = []
for line in samplesLine:
samples.append(line.split()[3].split("_")[-2])
lanes.append(line.split()[2].split("_")[-1])
uniquesamples = list(set(samples))
for uniquesample in uniquesamples:
# Create script
script = open("samtoolsIndex_" + uniquesample + ".sh", "w")
util.write_header(script, config, "samtoolsIndex")
script.write("samtools sort ../../bismark/" + uniquesample + "/" +
uniquesample + "_bismark_pe.bam ../../bismark/" +
uniquesample + "/" + uniquesample + "_bismark_pe_sorted")
script.write("\n\n")
script.write("samtools index ../../bismark/" + uniquesample + "/" +
uniquesample + "_bismark_pe_sorted.bam \n")
script.close()
os.chdir("coverage_bedgraph")
# Read samples files
samplesFile = open("../samples.txt")
samplesLines = samplesFile.readlines()[1:]
samples = []
for line in samplesLines:
samples.append(line.split()[3])
# Keep only unique samples.
samples = list(set(samples))
for sample in samples:
# Open coverage file.
coverageFile = glob.glob("../../bismark/" + sample +
"/methylation_extractor/" + sample +
"_bismark_pe.deduplicated.bismark.cov")[0]
# Create script file.
scriptName = 'coverage_bedgraph_' + sample + '.sh'
script = open(scriptName, 'w')
util.write_header(script, config, "coverage_bedgraph")
script.write("coverage_bedgraph.py --file=" + coverageFile)
script.close()
if (args.submitJobsToQueue.lower() == "yes") | (args.submitJobsToQueue.lower()
== "y"):
subprocess.call("submitJobs.py", shell=True)
config = util.readConfigurationFiles()
# Create scripts directory, if it does not exist yet, and cd to it.
if not os.path.exists("picardSort"):
os.mkdir("picardSort")
os.chdir("picardSort")
samplesFile = open("../samples.txt")
samplesLine = samplesFile.readlines()[1::2]
samples = []
lanes = []
for line in samplesLine:
samples.append(line.split()[3].split("_")[-2])
uniquesamples = list(set(samples))
for uniquesample in uniquesamples:
# Create script
script = open("picardSort_" + uniquesample + ".sh", "w")
util.write_header(script, config, "picardSort")
script.write("samtools sort ../../bismark/" + uniquesample + "/" +
uniquesample + ".bam ../../bismark/" + uniquesample + "/" +
uniquesample + "_sorted")
script.write("\n\n")
script.write("samtools index ../../bismark/" + uniquesample + "/" +
uniquesample + "_sorted.bam \n")
script.close()
samples = []
for line in samplesLine:
samples.append(line.split()[3].split("_")[-2])
uniquesamples = list(set(samples))
for sample in uniquesamples:
# Create output directory
outputDirectory = "../../bismark/" + sample + "/methylation_extractor"
if not os.path.exists(outputDirectory):
os.mkdir(outputDirectory)
bamFile = str(glob.glob("../../bismark/" + sample + "/*.bam"))[2:-2]
# Create script file.
scriptName = 'methylation_extractor_' + sample + '.sh'
script = open(scriptName, 'w')
util.write_header(script, config, "methylation_extractor")
script.write(
"bismark_methylation_extractor --buffer_size 10G --paired --no_overlap --comprehensive --report "
+ "\\\n")
script.write("--bedGraph --CX --cutoff " +
config.get('methylation_extractor', 'cutoff') + " " + "\\\n")
script.write("--output " + outputDirectory + " " + "\\\n")
script.write(bamFile)
script.close()
if (args.submitJobsToQueue.lower() == "yes") | (args.submitJobsToQueue.lower()
== "y"):
subprocess.call("submitJobs.py", shell=True)